diff --git a/.github/workflows/codespell.yml b/.github/workflows/codespell.yml new file mode 100644 index 0000000000..e21712e4bd --- /dev/null +++ b/.github/workflows/codespell.yml @@ -0,0 +1,25 @@ +# Codespell configuration is within pyproject.toml +--- +name: Codespell + +on: + push: + branches: [master] + pull_request: + branches: [master] + +permissions: + contents: read + +jobs: + codespell: + name: Check for spelling errors + runs-on: ubuntu-latest + + steps: + - name: Checkout + uses: actions/checkout@v4 + - name: Annotate locations with typos + uses: codespell-project/codespell-problem-matcher@v1 + - name: Codespell + uses: codespell-project/actions-codespell@v2 diff --git a/pyproject.toml b/pyproject.toml index 7311ad3a36..0c68b7219d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,3 +23,11 @@ dependencies = [ "squarify>=0.4.4", ] line-length = 70 + +[tool.codespell] +# Ref: https://github.com/codespell-project/codespell#using-a-config-file +skip = '.git*,*.svg,package-lock.json,*.css,*.csv' +check-hidden = true +# ignore embedded images and super long lines +ignore-regex = '^\s*"image/\S+": ".*|.{400,}' +# ignore-words-list = '' diff --git a/src/components/Layout.js b/src/components/Layout.js index 7f2585dafe..ae727b23d2 100644 --- a/src/components/Layout.js +++ b/src/components/Layout.js @@ -15,7 +15,7 @@ import TableOfContent from '../components/TableOfContent'; // - add the table of content // Import Styles = bootstrap + custom -// Custom must be AFTER bootstrap. It makes sure custom style are not overriden +// Custom must be AFTER bootstrap. It makes sure custom style are not overridden import 'bootstrap/dist/css/bootstrap.min.css'; import '../styles/style.css'; import AdInjector from './AdInjector'; diff --git a/src/functions/kdeplot.js b/src/functions/kdeplot.js index 0812862282..156475cc78 100644 --- a/src/functions/kdeplot.js +++ b/src/functions/kdeplot.js @@ -147,7 +147,7 @@ const param5 = { name: 'fill', description: (

- Control wether or not the area under the curve is filled with color. See + Control whether or not the area under the curve is filled with color. See the color argument to control its color.

), diff --git a/src/notebooks/120-line-chart-with-matplotlib.ipynb b/src/notebooks/120-line-chart-with-matplotlib.ipynb index 32463344c6..a80a5218c3 100644 --- a/src/notebooks/120-line-chart-with-matplotlib.ipynb +++ b/src/notebooks/120-line-chart-with-matplotlib.ipynb @@ -30,7 +30,7 @@ "source": [ "## Basic Lineplot\n", "\n", - "You can create a **basic line chart** with the `plot()` function of matplotlib library. If you give only a serie of values, matplotlib will consider that these values are ordered and will use values from 1 to n to create the X axis (figure 1):" + "You can create a **basic line chart** with the `plot()` function of matplotlib library. If you give only a series of values, matplotlib will consider that these values are ordered and will use values from 1 to n to create the X axis (figure 1):" ] }, { diff --git a/src/notebooks/121-line-chart-customization.ipynb b/src/notebooks/121-line-chart-customization.ipynb index b6ba9621c3..51c907f18e 100644 --- a/src/notebooks/121-line-chart-customization.ipynb +++ b/src/notebooks/121-line-chart-customization.ipynb @@ -68,7 +68,7 @@ "plt.plot( 'x_values', 'y_values', data=df, color='skyblue')\n", "plt.show()\n", "\n", - "# Draw line chart by modifiying transparency of the line\n", + "# Draw line chart by modifying transparency of the line\n", "plt.plot( 'x_values', 'y_values', data=df, color='skyblue', alpha=0.3)\n", "\n", "# Show plot\n", diff --git a/src/notebooks/122-multiple-lines-chart.ipynb b/src/notebooks/122-multiple-lines-chart.ipynb index 2f17ae101f..763586ad24 100644 --- a/src/notebooks/122-multiple-lines-chart.ipynb +++ b/src/notebooks/122-multiple-lines-chart.ipynb @@ -52,7 +52,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Mutliple line charts\n", + "## Multiple line charts\n", "\n", "Here we display 3 different line charts with **different style properties**:" ] diff --git a/src/notebooks/123-highlight-a-line-in-line-plot.ipynb b/src/notebooks/123-highlight-a-line-in-line-plot.ipynb index 815dbbb708..bf9ea08287 100644 --- a/src/notebooks/123-highlight-a-line-in-line-plot.ipynb +++ b/src/notebooks/123-highlight-a-line-in-line-plot.ipynb @@ -43,7 +43,7 @@ "for column in df.drop('x', axis=1):\n", " plt.plot(df['x'], df[column], marker='', color='grey', linewidth=1, alpha=0.4)\n", "\n", - "# Now re do the interesting curve, but biger with distinct color\n", + "# Now re do the interesting curve, but bigger with distinct color\n", "plt.plot(df['x'], df['y5'], marker='', color='orange', linewidth=4, alpha=0.7)\n", " \n", "# Change x axis limit\n", diff --git a/src/notebooks/134-how-to-avoid-overplotting-with-python.ipynb b/src/notebooks/134-how-to-avoid-overplotting-with-python.ipynb index ce970411f9..08601859f3 100644 --- a/src/notebooks/134-how-to-avoid-overplotting-with-python.ipynb +++ b/src/notebooks/134-how-to-avoid-overplotting-with-python.ipynb @@ -552,7 +552,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Lastly, you can draw a marginal plot using seaborn in order to aviod overlapping in your graph. Note that you can check [this post](https://python-graph-gallery.com/82-marginal-plot-with-seaborn/) to find out details on marginal plots." + "Lastly, you can draw a marginal plot using seaborn in order to avoid overlapping in your graph. Note that you can check [this post](https://python-graph-gallery.com/82-marginal-plot-with-seaborn/) to find out details on marginal plots." ] }, { diff --git a/src/notebooks/174-change-background-colour-of-venn-diagram.ipynb b/src/notebooks/174-change-background-colour-of-venn-diagram.ipynb index 3dd3f51005..d071983ebb 100644 --- a/src/notebooks/174-change-background-colour-of-venn-diagram.ipynb +++ b/src/notebooks/174-change-background-colour-of-venn-diagram.ipynb @@ -31,7 +31,7 @@ "# Basic Venn\n", "v = venn2( (10, 20, 10), alpha = 1 )\n", " \n", - "# Change Backgroud\n", + "# Change Background\n", "plt.gca().set_facecolor('skyblue')\n", "plt.gca().set_axis_on()\n", " \n", diff --git a/src/notebooks/181-custom-lollipop-plot.ipynb b/src/notebooks/181-custom-lollipop-plot.ipynb index 3ed1ad22f5..af79323b03 100644 --- a/src/notebooks/181-custom-lollipop-plot.ipynb +++ b/src/notebooks/181-custom-lollipop-plot.ipynb @@ -73,7 +73,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The position of the baseline can be changed using `bottom` argument in the `stem()` functon. You can also customize the baseline: remove it, change its size, color, and so on using the `setp()` function." + "The position of the baseline can be changed using `bottom` argument in the `stem()` function. You can also customize the baseline: remove it, change its size, color, and so on using the `setp()` function." ] }, { diff --git a/src/notebooks/182-vertical-lollipop-plot.ipynb b/src/notebooks/182-vertical-lollipop-plot.ipynb index bc9aec90a6..279f339eab 100644 --- a/src/notebooks/182-vertical-lollipop-plot.ipynb +++ b/src/notebooks/182-vertical-lollipop-plot.ipynb @@ -46,7 +46,7 @@ " \n", "# Add titles and axis names\n", "plt.yticks(my_range, ordered_df['group'])\n", - "plt.title(\"A vertical lolipop plot\", loc='left')\n", + "plt.title(\"A vertical lollipop plot\", loc='left')\n", "plt.xlabel('Value of the variable')\n", "plt.ylabel('Group')\n", "\n", diff --git a/src/notebooks/197-available-color-palettes-with-matplotlib.ipynb b/src/notebooks/197-available-color-palettes-with-matplotlib.ipynb index e5a3a12f83..734daa6ba4 100644 --- a/src/notebooks/197-available-color-palettes-with-matplotlib.ipynb +++ b/src/notebooks/197-available-color-palettes-with-matplotlib.ipynb @@ -67,7 +67,7 @@ "z = x+np.random.rand(15)\n", "z=z*z\n", " \n", - "# call pallette in cmap\n", + "# call palette in cmap\n", "plt.scatter(x, y, s=z*2000, c=x, cmap=\"BuPu\", alpha=0.4, edgecolors=\"grey\", linewidth=2)\n", "plt.show()\n", " \n", diff --git a/src/notebooks/231-chord-diagram-with-bokeh.ipynb b/src/notebooks/231-chord-diagram-with-bokeh.ipynb index 195761bc2a..1da5c630a3 100644 --- a/src/notebooks/231-chord-diagram-with-bokeh.ipynb +++ b/src/notebooks/231-chord-diagram-with-bokeh.ipynb @@ -2127,7 +2127,7 @@ ], "metadata": { "chartType": "chordDiagram", - "description": "A chord chart is used for representing the relationships between data points. Each data points are arranged into a circle and their relationships are displayed with chords. This post describes how to draw a chord chart using bokeh library of pyhton.", + "description": "A chord chart is used for representing the relationships between data points. Each data points are arranged into a circle and their relationships are displayed with chords. This post describes how to draw a chord chart using bokeh library of python.", "family": "flow", "kernelspec": { "display_name": "Python 3 (ipykernel)", diff --git a/src/notebooks/241-improve-area-chart.ipynb b/src/notebooks/241-improve-area-chart.ipynb index a003ed75ad..40a992b856 100644 --- a/src/notebooks/241-improve-area-chart.ipynb +++ b/src/notebooks/241-improve-area-chart.ipynb @@ -6,7 +6,7 @@ "source": [ "It is highly advised to change the default **color** of [matplotlib](http://python-graph-gallery.com/matplotlib/). Moreover, it is quite common to use a color with **transparency**, and **add a line** with a stronger colour on the top of the area. \n", "\n", - "You can pass the `color` parameter to change the color of the area and the `alpha` parameter to change the color transparancy of the area to the `fill_between()` function. You can also add a line with the `plot()` function and change its color to make the edge of the area marked." + "You can pass the `color` parameter to change the color of the area and the `alpha` parameter to change the color transparency of the area to the `fill_between()` function. You can also add a line with the `plot()` function and change its color to make the edge of the area marked." ] }, { diff --git a/src/notebooks/260-basic-wordcloud.ipynb b/src/notebooks/260-basic-wordcloud.ipynb index 4907c471e4..3280d5199b 100644 --- a/src/notebooks/260-basic-wordcloud.ipynb +++ b/src/notebooks/260-basic-wordcloud.ipynb @@ -36,7 +36,7 @@ "# Create a list of word\n", "text=(\"\"\"Python Python Python Matplotlib Matplotlib Seaborn\n", " Network Plot Violin Chart Pandas Datascience Wordcloud\n", - " Spider Radar Parrallel Alpha Color Brewer Density Scatter\n", + " Spider Radar Parallel Alpha Color Brewer Density Scatter\n", " Barplot Barplot Boxplot Violinplot Treemap Stacked Area\n", " Chart Chart Visualization Dataviz Donut Pie Time-Series\n", " Wordcloud Wordcloud Sankey Bubble\"\"\")\n", diff --git a/src/notebooks/261-custom-python-wordcloud.ipynb b/src/notebooks/261-custom-python-wordcloud.ipynb index 1fa51dd016..6ecea97b78 100644 --- a/src/notebooks/261-custom-python-wordcloud.ipynb +++ b/src/notebooks/261-custom-python-wordcloud.ipynb @@ -38,7 +38,7 @@ "# Create a list of word\n", "text=(\"\"\"Python Python Python Matplotlib Matplotlib Seaborn\n", " Network Plot Violin Chart Pandas Datascience Wordcloud\n", - " Spider Radar Parrallel Alpha Color Brewer Density Scatter\n", + " Spider Radar Parallel Alpha Color Brewer Density Scatter\n", " Barplot Barplot Boxplot Violinplot Treemap Stacked Area\n", " Chart Chart Visualization Dataviz Donut Pie Time-Series\n", " Wordcloud Wordcloud Sankey Bubble\"\"\")\n", @@ -95,7 +95,7 @@ "# Create a list of word\n", "text=(\"\"\"Python Python Python Matplotlib Matplotlib Seaborn\n", " Network Plot Violin Chart Pandas Datascience Wordcloud\n", - " Spider Radar Parrallel Alpha Color Brewer Density Scatter\n", + " Spider Radar Parallel Alpha Color Brewer Density Scatter\n", " Barplot Barplot Boxplot Violinplot Treemap Stacked Area\n", " Chart Chart Visualization Dataviz Donut Pie Time-Series\n", " Wordcloud Wordcloud Sankey Bubble\"\"\")\n", @@ -152,7 +152,7 @@ "# Create a list of word\n", "text=(\"\"\"Python Python Python Matplotlib Matplotlib Seaborn\n", " Network Plot Violin Chart Pandas Datascience Wordcloud\n", - " Spider Radar Parrallel Alpha Color Brewer Density Scatter\n", + " Spider Radar Parallel Alpha Color Brewer Density Scatter\n", " Barplot Barplot Boxplot Violinplot Treemap Stacked Area\n", " Chart Chart Visualization Dataviz Donut Pie Time-Series\n", " Wordcloud Wordcloud Sankey Bubble\"\"\")\n", @@ -210,7 +210,7 @@ "# Create a list of word\n", "text=(\"\"\"Python Python Python Matplotlib Matplotlib Seaborn\n", " Network Plot Violin Chart Pandas Datascience Wordcloud\n", - " Spider Radar Parrallel Alpha Color Brewer Density Scatter\n", + " Spider Radar Parallel Alpha Color Brewer Density Scatter\n", " Barplot Barplot Boxplot Violinplot Treemap Stacked Area\n", " Chart Chart Visualization Dataviz Donut Pie Time-Series\n", " Wordcloud Wordcloud Sankey Bubble\"\"\")\n", @@ -239,7 +239,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "And finally you can change the color pallette of words with `colormap` parameter.\n" + "And finally you can change the color palette of words with `colormap` parameter.\n" ] }, { @@ -266,7 +266,7 @@ "# Create a list of word\n", "text=(\"\"\"Python Python Python Matplotlib Matplotlib Seaborn\n", " Network Plot Violin Chart Pandas Datascience Wordcloud\n", - " Spider Radar Parrallel Alpha Color Brewer Density Scatter\n", + " Spider Radar Parallel Alpha Color Brewer Density Scatter\n", " Barplot Barplot Boxplot Violinplot Treemap Stacked Area\n", " Chart Chart Visualization Dataviz Donut Pie Time-Series\n", " Wordcloud Wordcloud Sankey Bubble\"\"\")\n", diff --git a/src/notebooks/262-wordcloud-with-specific-shape.ipynb b/src/notebooks/262-wordcloud-with-specific-shape.ipynb index 6a749f3fbc..bb35ada345 100644 --- a/src/notebooks/262-wordcloud-with-specific-shape.ipynb +++ b/src/notebooks/262-wordcloud-with-specific-shape.ipynb @@ -43,7 +43,7 @@ "from wordcloud import WordCloud\n", "import matplotlib.pyplot as plt\n", " \n", - "text=(\"\"\"Python Python Python Matplotlib Matplotlib Seaborn Network Plot Violin Chart Pandas Datascience Wordcloud Spider Radar Parrallel Alpha Color Brewer Density Scatter Barplot Barplot Boxplot Violinplot Treemap Stacked Area Chart Chart Visualization Dataviz Donut Pie Time-Series Wordcloud Wordcloud Sankey Bubble\"\"\")\n", + "text=(\"\"\"Python Python Python Matplotlib Matplotlib Seaborn Network Plot Violin Chart Pandas Datascience Wordcloud Spider Radar Parallel Alpha Color Brewer Density Scatter Barplot Barplot Boxplot Violinplot Treemap Stacked Area Chart Chart Visualization Dataviz Donut Pie Time-Series Wordcloud Wordcloud Sankey Bubble\"\"\")\n", " \n", "# Create the wordcloud object\n", "wordcloud = WordCloud(\n", diff --git a/src/notebooks/270-basic-bubble-plot.ipynb b/src/notebooks/270-basic-bubble-plot.ipynb index 268239e745..bdac8a3104 100644 --- a/src/notebooks/270-basic-bubble-plot.ipynb +++ b/src/notebooks/270-basic-bubble-plot.ipynb @@ -117,7 +117,7 @@ "- `x` : The data position on the x axis\n", "- `y` : The data position on the y axis\n", "- `s` : The marker size\n", - "- `alpha` : Transparancy ratio\n" + "- `alpha` : Transparency ratio\n" ] }, { diff --git a/src/notebooks/281-basic-map-with-basemap.ipynb b/src/notebooks/281-basic-map-with-basemap.ipynb index 59a3cb66bb..d81aa664cd 100644 --- a/src/notebooks/281-basic-map-with-basemap.ipynb +++ b/src/notebooks/281-basic-map-with-basemap.ipynb @@ -38,7 +38,7 @@ "# Set the plot size for this notebook:\n", "plt.rcParams[\"figure.figsize\"]=13,13\n", "\n", - "# Always start witht the basemap function to initialize a map\n", + "# Always start with the basemap function to initialize a map\n", "m=Basemap()\n", " \n", "# Show the coast lines\n", @@ -468,7 +468,7 @@ }, { "source": [ - "I looks like `arcGis` background requires some sort of authentification now πŸ€”. The code below looks outdated" + "I looks like `arcGis` background requires some sort of authentication now πŸ€”. The code below looks outdated" ], "cell_type": "markdown", "metadata": {} diff --git a/src/notebooks/315-a-world-map-of-surf-tweets.ipynb b/src/notebooks/315-a-world-map-of-surf-tweets.ipynb index 8be44d9809..c3468da29a 100644 --- a/src/notebooks/315-a-world-map-of-surf-tweets.ipynb +++ b/src/notebooks/315-a-world-map-of-surf-tweets.ipynb @@ -106,7 +106,7 @@ }, { "source": [ - "Let's add each data point on the map thanks to the `scatter()` function. The scatter() funcion is described extensively in the [scatterplot section](https://python-graph-gallery.com/scatter-plot) of the gallery. `x` and `y` coordinates are longitude and latitude respectively. `s` is the size of each circle, it is mapped to the `n` color of the data frame." + "Let's add each data point on the map thanks to the `scatter()` function. The scatter() function is described extensively in the [scatterplot section](https://python-graph-gallery.com/scatter-plot) of the gallery. `x` and `y` coordinates are longitude and latitude respectively. `s` is the size of each circle, it is mapped to the `n` color of the data frame." ], "cell_type": "markdown", "metadata": {} diff --git a/src/notebooks/33-control-colors-of-boxplot-seaborn.ipynb b/src/notebooks/33-control-colors-of-boxplot-seaborn.ipynb index 3146ffa6ef..e3df563936 100644 --- a/src/notebooks/33-control-colors-of-boxplot-seaborn.ipynb +++ b/src/notebooks/33-control-colors-of-boxplot-seaborn.ipynb @@ -92,7 +92,7 @@ "source": [ "## Specifying a color for each distribution\n", "\n", - "Specifying colors 'by hand' is quickly performed by creating a dictionnary composed of 'category': 'color' pairs as key:value, such as we did in the following example with my_pal.\n" + "Specifying colors 'by hand' is quickly performed by creating a dictionary composed of 'category': 'color' pairs as key:value, such as we did in the following example with my_pal.\n" ] }, { @@ -130,7 +130,7 @@ "source": [ "## Highliting a particular group\n", "\n", - "You may want to highlight one distribution among others, and this can be done again by creating a custom palette dictionnary, such as before.\n" + "You may want to highlight one distribution among others, and this can be done again by creating a custom palette dictionary, such as before.\n" ] }, { diff --git a/src/notebooks/34-grouped-boxplot.ipynb b/src/notebooks/34-grouped-boxplot.ipynb index 053d491738..30c863e7b5 100644 --- a/src/notebooks/34-grouped-boxplot.ipynb +++ b/src/notebooks/34-grouped-boxplot.ipynb @@ -40,7 +40,7 @@ "- `hue`: the variable by which we want to separate our box plot (**smoker or not**), for each value in the other qualitative variable (**day of the week**)\n", "- `data`: the dataset where our variables are stored (**df**)\n", "\n", - "Optionnal:\n", + "Optional:\n", "\n", "- `palette`: the set of color we want to use\n", "- `width`: width of each boxplot\n" @@ -152,7 +152,7 @@ ], "metadata": { "chartType": "boxplot", - "description": "Drawing a grouped boxplot with Seaborn is a common way to show the distribution of mutliple groups for a variable.
In this post, we'll detail how to create these boxplots and how to customize them.", + "description": "Drawing a grouped boxplot with Seaborn is a common way to show the distribution of multiple groups for a variable.
In this post, we'll detail how to create these boxplots and how to customize them.", "family": "distribution", "kernelspec": { "display_name": "Python 3", diff --git a/src/notebooks/342-animation-on-3d-plot.ipynb b/src/notebooks/342-animation-on-3d-plot.ipynb index d682c702dd..3cdd97c9cd 100644 --- a/src/notebooks/342-animation-on-3d-plot.ipynb +++ b/src/notebooks/342-animation-on-3d-plot.ipynb @@ -76,7 +76,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The last line of the code chunck above is of high interest here. It set the angle the camera uses to display the figure (`70Β°` here).\n" + "The last line of the code chunk above is of high interest here. It set the angle the camera uses to display the figure (`70Β°` here).\n" ] }, { diff --git a/src/notebooks/35-control-order-of-boxplot.ipynb b/src/notebooks/35-control-order-of-boxplot.ipynb index 87b7ef442d..90ecb72fd6 100644 --- a/src/notebooks/35-control-order-of-boxplot.ipynb +++ b/src/notebooks/35-control-order-of-boxplot.ipynb @@ -42,7 +42,7 @@ "source": [ "## By decreasing median\n", "\n", - "In the example above, we directly specified the order in which we expected our distributions to appear (based on groups name). Not knowing beforehand, we could have decided to dispay the distributions by decreasing median. This can be achieved again by specifying the 'order' argument inside the boxplot() function. \n", + "In the example above, we directly specified the order in which we expected our distributions to appear (based on groups name). Not knowing beforehand, we could have decided to display the distributions by decreasing median. This can be achieved again by specifying the 'order' argument inside the boxplot() function. \n", "Using pandas groupby, median and slicing in reverse order (thanks to .iloc[::-1]), we are able to define a list of groups ordered by decreasing median, which is then used as a value for the 'order' argument.\n" ] }, diff --git a/src/notebooks/372-3d-pca-result.ipynb b/src/notebooks/372-3d-pca-result.ipynb index 0b95e7796e..61ce0c66fc 100644 --- a/src/notebooks/372-3d-pca-result.ipynb +++ b/src/notebooks/372-3d-pca-result.ipynb @@ -48,7 +48,7 @@ "my_dpi=96\n", "plt.figure(figsize=(480/my_dpi, 480/my_dpi), dpi=my_dpi)\n", " \n", - "# Keep the 'species' column appart + make it numeric for coloring\n", + "# Keep the 'species' column apart + make it numeric for coloring\n", "df['species']=pd.Categorical(df['species'])\n", "my_color=df['species'].cat.codes\n", "df = df.drop('species', 1)\n", diff --git a/src/notebooks/39-hidden-data-under-boxplot.ipynb b/src/notebooks/39-hidden-data-under-boxplot.ipynb index 1708c646a2..5d4593ba7d 100644 --- a/src/notebooks/39-hidden-data-under-boxplot.ipynb +++ b/src/notebooks/39-hidden-data-under-boxplot.ipynb @@ -231,7 +231,7 @@ ], "metadata": { "chartType": "caveats", - "description": "A boxplot summarizes the distribution of a numeric variable for several groups. The problem is that summarizing also might mean loosing information. This post is dedicated to explain methods in order to overcome a problem of hidden data under boxplot.", + "description": "A boxplot summarizes the distribution of a numeric variable for several groups. The problem is that summarizing also might mean losing information. This post is dedicated to explain methods in order to overcome a problem of hidden data under boxplot.", "family": "general", "kernelspec": { "display_name": "Python 3", diff --git a/src/notebooks/40-basic-scatterplot-seaborn.ipynb b/src/notebooks/40-basic-scatterplot-seaborn.ipynb index 73677843ca..4dc15799f3 100644 --- a/src/notebooks/40-basic-scatterplot-seaborn.ipynb +++ b/src/notebooks/40-basic-scatterplot-seaborn.ipynb @@ -139,7 +139,7 @@ "source": [ "## Scatter plot\n", "\n", - "A [scatterplot](/scatter-plot) can be made using `scatterplot()` function of [seaborn](/seaborn) library. An example dataset from seaborn repository, iris dataset, is used in the example. The plot shows the relationship between sepal lenght and width of plants. In order to show the most basic utilization of this function, the following parameters should be provided:\n", + "A [scatterplot](/scatter-plot) can be made using `scatterplot()` function of [seaborn](/seaborn) library. An example dataset from seaborn repository, iris dataset, is used in the example. The plot shows the relationship between sepal length and width of plants. In order to show the most basic utilization of this function, the following parameters should be provided:\n", "\n", "- `x` : positions of points on the X axis\n", "- `y` : positions of points on the Y axis\n" diff --git a/src/notebooks/402-color-dendrogram-labels.ipynb b/src/notebooks/402-color-dendrogram-labels.ipynb index d7e1292787..1c879c363a 100644 --- a/src/notebooks/402-color-dendrogram-labels.ipynb +++ b/src/notebooks/402-color-dendrogram-labels.ipynb @@ -46,7 +46,7 @@ "# Create a color palette with 3 colors for the 3 cyl possibilities\n", "my_palette = plt.cm.get_cmap(\"Accent\", 3)\n", " \n", - "# transforme the 'cyl' column in a categorical variable. It will allow to put one color on each level.\n", + "# transform the 'cyl' column in a categorical variable. It will allow to put one color on each level.\n", "df['cyl']=pd.Categorical(df['cyl'])\n", "my_color=df['cyl'].cat.codes\n", " \n", diff --git a/src/notebooks/404-dendrogram-with-heat-map.ipynb b/src/notebooks/404-dendrogram-with-heat-map.ipynb index 9341a84de6..c0b426c1b2 100644 --- a/src/notebooks/404-dendrogram-with-heat-map.ipynb +++ b/src/notebooks/404-dendrogram-with-heat-map.ipynb @@ -60,7 +60,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "It is possible to standardize or normalize the data you want to plot by passing the `standard_scale` or `z_score` aguments to the function:\n", + "It is possible to standardize or normalize the data you want to plot by passing the `standard_scale` or `z_score` arguments to the function:\n", "* `standard_scale` : Either 0 (rows) or 1 (columns)\n", "* `z_score` : Either 0 (rows) or 1 (columns)" ] diff --git a/src/notebooks/405-dendrogram-with-heatmap-and-coloured-leaves.ipynb b/src/notebooks/405-dendrogram-with-heatmap-and-coloured-leaves.ipynb index 7a7f593a70..546713b94a 100644 --- a/src/notebooks/405-dendrogram-with-heatmap-and-coloured-leaves.ipynb +++ b/src/notebooks/405-dendrogram-with-heatmap-and-coloured-leaves.ipynb @@ -5,7 +5,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In the example, mtcars dataset that shows the features of cars through numerical variables is used. While clustering cars, a color sheme is added to the left part of the plot. The 3 colours represent the 3 possible values of the β€˜cyl’ column. By using this feature, you can evaluate whether samples within a group are clustered together." + "In the example, mtcars dataset that shows the features of cars through numerical variables is used. While clustering cars, a color scheme is added to the left part of the plot. The 3 colours represent the 3 possible values of the β€˜cyl’ column. By using this feature, you can evaluate whether samples within a group are clustered together." ] }, { diff --git a/src/notebooks/406-chord-diagram_mne.ipynb b/src/notebooks/406-chord-diagram_mne.ipynb index 4c16917e64..816cbf619c 100644 --- a/src/notebooks/406-chord-diagram_mne.ipynb +++ b/src/notebooks/406-chord-diagram_mne.ipynb @@ -28,7 +28,7 @@ "source": [ "from mne.viz import plot_connectivity_circle\n", "\n", - "# only for the exemple\n", + "# only for the example\n", "import numpy as np" ] }, @@ -3136,7 +3136,7 @@ "id": "582cf8d9", "metadata": {}, "source": [ - "## Brocoli\n" + "## Broccoli\n" ] }, { @@ -3144,7 +3144,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let's get some fun and build a data art brocoli like chord diagram 😊 !\n" + "Let's get some fun and build a data art broccoli like chord diagram 😊 !\n" ] }, { diff --git a/src/notebooks/44-control-axis-limits-of-plot-seaborn.ipynb b/src/notebooks/44-control-axis-limits-of-plot-seaborn.ipynb index 8d66a3faf3..77922004eb 100644 --- a/src/notebooks/44-control-axis-limits-of-plot-seaborn.ipynb +++ b/src/notebooks/44-control-axis-limits-of-plot-seaborn.ipynb @@ -14,7 +14,7 @@ "You can control the limits of X and Y axis of your plots using [matplotlib](http://python-graph-gallery.com/matplotlib/) function `plt.xlim()` and `plt.ylim()`. In this example, `lmplot()` function of [seaborn](http://python-graph-gallery.com/40-basic-scatterplot-seaborn/) is used to plot a [basic scatterplot](http://python-graph-gallery.com/40-basic-scatterplot-seaborn/) with iris dataset. There are 2 arguments in these functions;\n", "\n", "- `plt.xlim()` : (left, right)\n", - "- `plt.ylim()` : (buttom, top)\n" + "- `plt.ylim()` : (bottom, top)\n" ] }, { diff --git a/src/notebooks/50-basic-violinplot-and-input-formats.ipynb b/src/notebooks/50-basic-violinplot-and-input-formats.ipynb index 3bf5ad21f6..6ce9178177 100644 --- a/src/notebooks/50-basic-violinplot-and-input-formats.ipynb +++ b/src/notebooks/50-basic-violinplot-and-input-formats.ipynb @@ -2067,7 +2067,7 @@ ], "metadata": { "chartType": "violin", - "description": "This post aims at describing how to realize basic violinplots. It explains how your input must be formated and which seaborn functions are to be used. Three input formats exist to draw a violinplot: one numerical variable only, one variable and several groups, and several variables.", + "description": "This post aims at describing how to realize basic violinplots. It explains how your input must be formatted and which seaborn functions are to be used. Three input formats exist to draw a violinplot: one numerical variable only, one variable and several groups, and several variables.", "family": "distribution", "kernelspec": { "display_name": "Python 3", diff --git a/src/notebooks/501-parallel-plot-seaborn.ipynb b/src/notebooks/501-parallel-plot-seaborn.ipynb index d819dcb06d..1cde734c71 100644 --- a/src/notebooks/501-parallel-plot-seaborn.ipynb +++ b/src/notebooks/501-parallel-plot-seaborn.ipynb @@ -7,7 +7,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the slope chart and for customization\n", "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the parallel plot\n", "- `pandas` is used for loading the dataset" diff --git a/src/notebooks/503-waffle-chart-introduction.ipynb b/src/notebooks/503-waffle-chart-introduction.ipynb index 9ee416e832..24e3bbf644 100644 --- a/src/notebooks/503-waffle-chart-introduction.ipynb +++ b/src/notebooks/503-waffle-chart-introduction.ipynb @@ -115,7 +115,7 @@ "source": [ "## Basic customizations\n", "\n", - "- colors: the `colors` argument changes the color of the grids and must be a list of colors of the same lenght than your number of categories \n", + "- colors: the `colors` argument changes the color of the grids and must be a list of colors of the same length than your number of categories \n", "- icons: the `icons` argument changes the shape of the grids and can be a list of icons" ] }, diff --git a/src/notebooks/505-Introduction-to-swarm-plot-in-seaborn.ipynb b/src/notebooks/505-Introduction-to-swarm-plot-in-seaborn.ipynb index f34d3d4bd7..64884be889 100644 --- a/src/notebooks/505-Introduction-to-swarm-plot-in-seaborn.ipynb +++ b/src/notebooks/505-Introduction-to-swarm-plot-in-seaborn.ipynb @@ -25,9 +25,9 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", - "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the chart witht the `swarmplot()` function\n", + "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the chart with the `swarmplot()` function\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot customization purposes\n", "- `numpy` is used to generate some data\n", "\n", @@ -194,7 +194,7 @@ "source": [ "### Plot\n", "\n", - "This time, both the `x` and `y` attributes must be provided. Also, it is common to use a categorical color sheme to color groups thanks to the `palette` argument to color groups.\n" + "This time, both the `x` and `y` attributes must be provided. Also, it is common to use a categorical color scheme to color groups thanks to the `palette` argument to color groups.\n" ] }, { diff --git a/src/notebooks/506-histogram-with-small-mutliples.ipynb b/src/notebooks/506-histogram-with-small-mutliples.ipynb index 0cd92bc875..a1c46665bd 100644 --- a/src/notebooks/506-histogram-with-small-mutliples.ipynb +++ b/src/notebooks/506-histogram-with-small-mutliples.ipynb @@ -17,7 +17,7 @@ "\n", "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the plot\n", "- `numpy` is used to generate some data\n", "- `pandas` for data manipulation\n", @@ -245,7 +245,7 @@ "source": [ "## Going further\n", "\n", - "This post explained how to create histograms with small mutliple using matplotlib.\n", + "This post explained how to create histograms with small multiple using matplotlib.\n", "\n", "For more examples of how to customize your histogram, check the [histogram section](https://python-graph-gallery.com/histogram/). You might be interested in how to make a histogram with [seaborn](https://python-graph-gallery.com/seaborn/) for a better looking chart or even how to show several distribution with a [mirror histogram](https://python-graph-gallery.com/density-mirror/)." ] diff --git a/src/notebooks/508-connected-scatter-plot-seaborn.ipynb b/src/notebooks/508-connected-scatter-plot-seaborn.ipynb index e1dbb465d2..33d22b8faf 100644 --- a/src/notebooks/508-connected-scatter-plot-seaborn.ipynb +++ b/src/notebooks/508-connected-scatter-plot-seaborn.ipynb @@ -25,8 +25,8 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", - "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the chart witht the `lineplot()` function\n", + "First, you need to install the following libraries:\n", + "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the chart with the `lineplot()` function\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot customization purposes\n", "- `numpy` is used to generate some data\n", "- `pandas` is used to store the data generated with numpy\n", diff --git a/src/notebooks/509-introduction-to-swarm-plot-in-matplotlib.ipynb b/src/notebooks/509-introduction-to-swarm-plot-in-matplotlib.ipynb index d1d9dae202..1e100dfa66 100644 --- a/src/notebooks/509-introduction-to-swarm-plot-in-matplotlib.ipynb +++ b/src/notebooks/509-introduction-to-swarm-plot-in-matplotlib.ipynb @@ -21,7 +21,7 @@ "\n", "Since [matplotlib](https://python-graph-gallery.com/matplotlib/) does not have a function for beeswarm plot, we will need to create our own. We will use (_slightly modified_) functions suggested by [MichaelClerx](https://stackoverflow.com/users/423420/michael-clerx) and [Roger Vadim](https://stackoverflow.com/users/6151828/roger-vadim) on Stackoverflow [here](https://stackoverflow.com/questions/36153410/how-to-create-a-swarm-plot-with-matplotlib).\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot customization purposes and display the chart\n", "- `numpy` is used to generate some data and create the chart\n", @@ -336,7 +336,7 @@ "tags": [] }, "source": [ - "## Bonus: add boxplots for better vizualisation\n", + "## Bonus: add boxplots for better visualisation\n", "\n", "To get an even clearer idea of the distribution of your data, it may be useful to add [box plots](https://python-graph-gallery.com/boxplot/) under the beeswarm plots, as suggested in the original function by Roger Vadim.\n", "\n", diff --git a/src/notebooks/51-horizontal-violinplot.ipynb b/src/notebooks/51-horizontal-violinplot.ipynb index 5aad7993be..4e3783584c 100644 --- a/src/notebooks/51-horizontal-violinplot.ipynb +++ b/src/notebooks/51-horizontal-violinplot.ipynb @@ -6,7 +6,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the chart\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for customization" ] diff --git a/src/notebooks/511-interactive-scatterplot-with-plotly.ipynb b/src/notebooks/511-interactive-scatterplot-with-plotly.ipynb index 598a2f570d..b8bc4c173b 100644 --- a/src/notebooks/511-interactive-scatterplot-with-plotly.ipynb +++ b/src/notebooks/511-interactive-scatterplot-with-plotly.ipynb @@ -1394,7 +1394,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/scatterplot-plotly-basic.html\")\n" ] }, @@ -2821,7 +2821,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/scatterplot-plotly-grouping.html\")\n" ] }, @@ -4638,7 +4638,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/scatterplot-plotly-trendline.html\")" ] }, diff --git a/src/notebooks/512-line-chart-seaborn.ipynb b/src/notebooks/512-line-chart-seaborn.ipynb index ac94ca99b1..1149f90b88 100644 --- a/src/notebooks/512-line-chart-seaborn.ipynb +++ b/src/notebooks/512-line-chart-seaborn.ipynb @@ -17,8 +17,8 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", - "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the chart witht the `lineplot()` function\n", + "First, you need to install the following libraries:\n", + "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the chart with the `lineplot()` function\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot customization purposes\n", "- `numpy` is used to generate some data\n", "- `pandas` is used to put the data into a dataframe\n", diff --git a/src/notebooks/513-add-logo-matplotlib.ipynb b/src/notebooks/513-add-logo-matplotlib.ipynb index 2abbd77426..e55389c7c0 100644 --- a/src/notebooks/513-add-logo-matplotlib.ipynb +++ b/src/notebooks/513-add-logo-matplotlib.ipynb @@ -19,7 +19,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) for displaying the chart and the logo\n", "- `numpy` is used for manipulating the image as an array\n", "- `PIL` for opening the image\n", @@ -52,7 +52,7 @@ "\n", "We'll look at two cases: using an **image stored locally** on your computer and using an **image from the Internet** using only the url address.\n", "\n", - "- Image stored locally: make sure you write the **right path** (in the following example, `/Users/josephbarbier/Desktop/python graph gallery/github_logo.png` is the location of the image on my computer). The image I chosed is just a basic png github logo. \n", + "- Image stored locally: make sure you write the **right path** (in the following example, `/Users/josephbarbier/Desktop/python graph gallery/github_logo.png` is the location of the image on my computer). The image I chose is just a basic png github logo. \n", "\n", "- Image from the Internet: we need to make sure we complete the objective with **some test**. With the `if` statement, we are checking whether the **HTTP response status code is equal to 200**. In the context of HTTP, a status code of 200 means *\"OK\"*, indicating that the request was successful and the server has responded with the **requested content**. If this test is passed, then we just have to get the content from the request and open the image!" ] @@ -81,7 +81,7 @@ "source": [ "# Open an image from the Internet\n", "def open_image_internet(url_adress):\n", - " response = requests.get(url_adress) # Send http request to the url adress\n", + " response = requests.get(url_adress) # Send http request to the url address\n", " \n", " # Make sure everything went right\n", " if response.status_code == 200:\n", @@ -183,7 +183,7 @@ ], "metadata": { "chartType": "colors", - "description": "This post explains how to insert an image into your matplotlib plot using the PIL and io libraries.
Two use cases are considered: your image beeing stored locally or somewhere on the web.", + "description": "This post explains how to insert an image into your matplotlib plot using the PIL and io libraries.
Two use cases are considered: your image being stored locally or somewhere on the web.", "family": "general", "kernelspec": { "display_name": "Python 3 (ipykernel)", diff --git a/src/notebooks/514-interactive-line-chart-plotly.ipynb b/src/notebooks/514-interactive-line-chart-plotly.ipynb index bc75127a5d..c7e55fdc69 100644 --- a/src/notebooks/514-interactive-line-chart-plotly.ipynb +++ b/src/notebooks/514-interactive-line-chart-plotly.ipynb @@ -25,7 +25,7 @@ "\n", "In our case, we'll use the `go` module (or `graph_objects`). We will also use `numpy` and `pandas` to **generate data** and put it into a dataframe.\n", "\n", - "- [plotlty](https://python-graph-gallery.com/seaborn/) is used for creating the chart witht the `Scatter()` function\n", + "- [plotlty](https://python-graph-gallery.com/seaborn/) is used for creating the chart with the `Scatter()` function\n", "- `numpy` is used to generate some data\n", "- `pandas` is used to put the data into a dataframe\n" ] @@ -95,7 +95,7 @@ "source": [ "## Basic line chart\n", "\n", - "The following code displays a simple line chart built wiht [Plotly](https://python-graph-gallery.com/plotly/), with a title and an axis name, thanks to the `Scatter()` function.\n" + "The following code displays a simple line chart built with [Plotly](https://python-graph-gallery.com/plotly/), with a title and an axis name, thanks to the `Scatter()` function.\n" ] }, { @@ -1050,7 +1050,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/linechart-plotly-basic.html\")" ] }, @@ -2079,7 +2079,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/linechart-plotly-custom.html\")" ] }, @@ -2125,7 +2125,7 @@ "tags": [] }, "source": [ - "## Line chart with mutliple variables\n", + "## Line chart with multiple variables\n", "\n", "It's quite common to want to have **several lines in a single graph**. In practice, all you need to do is write the `add_trace()` with `go.Scatter()` function code several times (**one for each variable**).\n", "\n", @@ -3306,7 +3306,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\n", " \"../../static/interactiveCharts/linechart-plotly-multigroup.html\")" ] diff --git a/src/notebooks/515-intro-pca-graph-python.ipynb b/src/notebooks/515-intro-pca-graph-python.ipynb index 67c38ce207..055c81f379 100644 --- a/src/notebooks/515-intro-pca-graph-python.ipynb +++ b/src/notebooks/515-intro-pca-graph-python.ipynb @@ -90,7 +90,7 @@ "source": [ "## Create the PCA object\n", "\n", - "With `scikit-learn`, it's easy to make a `PCA`. Simply initialize a `PCA` object (and optionnaly specify **the number of components** you want to keep). As it's difficult to create a **visualization on more than 2 axes** (3 is possible but more complex), we'll keep only the first 2 dimensions (see graph section below). " + "With `scikit-learn`, it's easy to make a `PCA`. Simply initialize a `PCA` object (and optionally specify **the number of components** you want to keep). As it's difficult to create a **visualization on more than 2 axes** (3 is possible but more complex), we'll keep only the first 2 dimensions (see graph section below). " ] }, { diff --git a/src/notebooks/516-line-chart-with-annotations.ipynb b/src/notebooks/516-line-chart-with-annotations.ipynb index 47dd85d1c0..bb6ac2c594 100644 --- a/src/notebooks/516-line-chart-with-annotations.ipynb +++ b/src/notebooks/516-line-chart-with-annotations.ipynb @@ -25,7 +25,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot creating the charts\n", "- `numpy` is used to generate some data\n", "- `pandas` is used to put the data into a dataframe" diff --git a/src/notebooks/520-the-two-plotly-APIs.ipynb b/src/notebooks/520-the-two-plotly-APIs.ipynb index d9ded6cd90..d9a4204875 100644 --- a/src/notebooks/520-the-two-plotly-APIs.ipynb +++ b/src/notebooks/520-the-two-plotly-APIs.ipynb @@ -88,7 +88,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/barplot-plotly-express.html\")" ] }, @@ -1030,7 +1030,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/barplot-plotly-go.html\")" ] }, diff --git a/src/notebooks/521-interactive-line-chart-with-plotly.ipynb b/src/notebooks/521-interactive-line-chart-with-plotly.ipynb index 993984c483..1fce9a90e6 100644 --- a/src/notebooks/521-interactive-line-chart-with-plotly.ipynb +++ b/src/notebooks/521-interactive-line-chart-with-plotly.ipynb @@ -2924,7 +2924,7 @@ "\n", "# Add annotation to a specific point\n", "fig.add_annotation(\n", - " x=2, y=11, # postion\n", + " x=2, y=11, # position\n", " text=\"Annotated Point\", # text\n", " showarrow=True,\n", " arrowhead=2,\n", @@ -2960,7 +2960,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## ⏱ Embeding a plotly chart\n", + "## ⏱ Embedding a plotly chart\n", "\n", "Once the chart has been saved, you can embed it in a html document using:" ] diff --git a/src/notebooks/522-plotly-customize-title.ipynb b/src/notebooks/522-plotly-customize-title.ipynb index c79d7f2bd5..93cd4a5f11 100644 --- a/src/notebooks/522-plotly-customize-title.ipynb +++ b/src/notebooks/522-plotly-customize-title.ipynb @@ -920,7 +920,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/plotly-customize-title-1.html\")" ] }, @@ -1869,7 +1869,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/plotly-customize-title-2.html\")" ] }, diff --git a/src/notebooks/523-plotly-add-annotation.ipynb b/src/notebooks/523-plotly-add-annotation.ipynb index 4a3caf9ed1..3d7a1528ce 100644 --- a/src/notebooks/523-plotly-add-annotation.ipynb +++ b/src/notebooks/523-plotly-add-annotation.ipynb @@ -925,7 +925,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/plotly-add-annotation-0.html\")" ] }, @@ -1876,7 +1876,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/plotly-add-annotation-1.html\")" ] }, @@ -2946,7 +2946,7 @@ "metadata": {}, "outputs": [], "source": [ - "# save this file as a standalong html file:\n", + "# save this file as a standalone html file:\n", "fig.write_html(\"../../static/interactiveCharts/plotly-add-annotation-2.html\")" ] }, diff --git a/src/notebooks/524-area-chart-over-flexible-baseline.ipynb b/src/notebooks/524-area-chart-over-flexible-baseline.ipynb index 5ab339bcad..5904ca873d 100644 --- a/src/notebooks/524-area-chart-over-flexible-baseline.ipynb +++ b/src/notebooks/524-area-chart-over-flexible-baseline.ipynb @@ -1198,7 +1198,7 @@ "source": [ "## Create the same plot using Plotly\n", "\n", - "Now we create the same plot using the `Python` library `Plotly`, which allows us to have interactive elements. We use the same data from befor. First, we define a figure with some basic settings." + "Now we create the same plot using the `Python` library `Plotly`, which allows us to have interactive elements. We use the same data from before. First, we define a figure with some basic settings." ] }, { @@ -1257,7 +1257,7 @@ "source": [ "### Plot percentile area\n", "\n", - "In Plotly the order of traces determines their position (abov/below). That's why we first plot the area between the 5/95 percentiles, then daily values for the year to display, and then percentile lines and mean (on top). \n", + "In Plotly the order of traces determines their position (above/below). That's why we first plot the area between the 5/95 percentiles, then daily values for the year to display, and then percentile lines and mean (on top). \n", "\n", "It's also possible to reorder the traces later, but this way we get it right from the beginning." ] diff --git a/src/notebooks/525-line-chart-log-transform.ipynb b/src/notebooks/525-line-chart-log-transform.ipynb index b8978f0524..ac1fc650d0 100644 --- a/src/notebooks/525-line-chart-log-transform.ipynb +++ b/src/notebooks/525-line-chart-log-transform.ipynb @@ -21,7 +21,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot creating the charts (and the `MultipleLocator` for showing the log scale)\n", "- `numpy` is used to generate some data\n", "- `pandas` is used to put the data into a dataframe" diff --git a/src/notebooks/532-customizing-circular-barplot-in-matplotlib.ipynb b/src/notebooks/532-customizing-circular-barplot-in-matplotlib.ipynb index 5c557a8914..df86237937 100644 --- a/src/notebooks/532-customizing-circular-barplot-in-matplotlib.ipynb +++ b/src/notebooks/532-customizing-circular-barplot-in-matplotlib.ipynb @@ -249,7 +249,7 @@ }, "outputs": [], "source": [ - "# calculate corect angular position in circular bar plot\n", + "# calculate correct angular position in circular bar plot\n", "x_max = 2*np.pi\n", "df['angular_pos'] = np.linspace(0, x_max, len(df), endpoint=False)" ] diff --git a/src/notebooks/532-linecharts-mutliple-groups-with-pandas.ipynb b/src/notebooks/532-linecharts-mutliple-groups-with-pandas.ipynb index 16aa7bfce1..377300f86d 100644 --- a/src/notebooks/532-linecharts-mutliple-groups-with-pandas.ipynb +++ b/src/notebooks/532-linecharts-mutliple-groups-with-pandas.ipynb @@ -244,7 +244,7 @@ "source": [ "## Going further\n", "\n", - "This post explains how to create a line chart with mutliple variables and groups, with [pandas](https://python-graph-gallery.com/pandas/).\n", + "This post explains how to create a line chart with multiple variables and groups, with [pandas](https://python-graph-gallery.com/pandas/).\n", "\n", "For more examples of **how to create or customize** your line charts, see the [line charts section](https://python-graph-gallery.com/line-chart/). You may also be interested in how to [customize a line chart](https://python-graph-gallery.com/531-customizing-linecharts-with-pandas) with pandas.\n" ] diff --git a/src/notebooks/533-introduction-boxplots-matplotlib.ipynb b/src/notebooks/533-introduction-boxplots-matplotlib.ipynb index 20da05734c..1aa93d7af2 100644 --- a/src/notebooks/533-introduction-boxplots-matplotlib.ipynb +++ b/src/notebooks/533-introduction-boxplots-matplotlib.ipynb @@ -6,7 +6,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the plot\n", "- `pandas` for data manipulation" ] diff --git a/src/notebooks/534-highly-customized-layout.ipynb b/src/notebooks/534-highly-customized-layout.ipynb index 9b12a92537..73a2f6f793 100644 --- a/src/notebooks/534-highly-customized-layout.ipynb +++ b/src/notebooks/534-highly-customized-layout.ipynb @@ -6,7 +6,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot creating the charts\n", "- `numpy` is used to generate some data\n", "- `pandas` is used to put the data into a dataframe" @@ -31,7 +31,7 @@ "source": [ "## Dataset\n", "\n", - "In order to be as exhaustive as possible, we need to create a dataset with enought variety.\n", + "In order to be as exhaustive as possible, we need to create a dataset with enough variety.\n", "\n", "- `Numeric1` and `Numeric2` are positively correlated variables, with `Numeric2` being calculated as **Numeric1 plus some random noise**.\n", "- `Numeric3` is a **negatively correlated** variable to `Numeric1`.\n", diff --git a/src/notebooks/54-grouped-violinplot.ipynb b/src/notebooks/54-grouped-violinplot.ipynb index 0706b3be0b..1a0e37d40f 100644 --- a/src/notebooks/54-grouped-violinplot.ipynb +++ b/src/notebooks/54-grouped-violinplot.ipynb @@ -7,7 +7,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the chart\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for customization\n" diff --git a/src/notebooks/541-waffle-chart-with-additionnal-grouping.ipynb b/src/notebooks/541-waffle-chart-with-additionnal-grouping.ipynb index 3a5c1d7985..1c722c4706 100644 --- a/src/notebooks/541-waffle-chart-with-additionnal-grouping.ipynb +++ b/src/notebooks/541-waffle-chart-with-additionnal-grouping.ipynb @@ -109,11 +109,11 @@ "source": [ "## Waffle chart with grouping\n", "\n", - "This example can be found in the [original documentation of PyWaffle](https://github.com/gyli/PyWaffle) (this one here is slighly different). \n", + "This example can be found in the [original documentation of PyWaffle](https://github.com/gyli/PyWaffle) (this one here is slightly different). \n", "\n", - "The very first thing to do is to create our `plot dictionnaries`. In our case, since we want 3 different charts, we create 3 plot dictionnaries with the **values and properties** we want them to have. We divide the values by 1000 only because we want to **reduce the size** of them but it's optionnal. \n", + "The very first thing to do is to create our `plot dictionaries`. In our case, since we want 3 different charts, we create 3 plot dictionaries with the **values and properties** we want them to have. We divide the values by 1000 only because we want to **reduce the size** of them but it's optional. \n", "\n", - "Then, we just have to add these dictionnaries into the `plot` argument of the `figure()` function from matplotlib. " + "Then, we just have to add these dictionaries into the `plot` argument of the `figure()` function from matplotlib. " ] }, { @@ -213,7 +213,7 @@ }, "seoDescription": "How to create a waffle chart with additional grouping", "slug": "541-waffle-chart-with-additionnal-grouping", - "title": "Waffle chart with additionnal grouping" + "title": "Waffle chart with additional grouping" }, "nbformat": 4, "nbformat_minor": 4 diff --git a/src/notebooks/542-custom-boxplots-matplotlib.ipynb b/src/notebooks/542-custom-boxplots-matplotlib.ipynb index 0e6c2f13c8..9b6885f162 100644 --- a/src/notebooks/542-custom-boxplots-matplotlib.ipynb +++ b/src/notebooks/542-custom-boxplots-matplotlib.ipynb @@ -6,7 +6,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the plot\n", "- `pandas` for data manipulation\n", "- `numpy` for data generation" @@ -184,9 +184,9 @@ "\n", "With [matplotlib](https://python-graph-gallery.com/matplotlib/), you can change the **color of *each element*** in our boxplot.\n", "\n", - "The **easiest and cleanest** way to do so is to create a dictionnary of dictionnaries with the **properties** we want for each element. Also, we have to add the `patch_artist=True` argument when using this technique since otherwise it will **raise an error**. \n", + "The **easiest and cleanest** way to do so is to create a dictionary of dictionaries with the **properties** we want for each element. Also, we have to add the `patch_artist=True` argument when using this technique since otherwise it will **raise an error**. \n", "\n", - "The advantage of this method is that it can be used to **add other properties** to the [boxplot](https://python-graph-gallery.com/boxplot/), such as bar size or outlier size/type (`flierprops` dictionnary). " + "The advantage of this method is that it can be used to **add other properties** to the [boxplot](https://python-graph-gallery.com/boxplot/), such as bar size or outlier size/type (`flierprops` dictionary). " ] }, { diff --git a/src/notebooks/543-grouped-boxplots-matplotlib.ipynb b/src/notebooks/543-grouped-boxplots-matplotlib.ipynb index 8b7dda77a5..3cf29c840c 100644 --- a/src/notebooks/543-grouped-boxplots-matplotlib.ipynb +++ b/src/notebooks/543-grouped-boxplots-matplotlib.ipynb @@ -6,7 +6,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the plot\n", "- `pandas` for data manipulation\n", "- `numpy` for data generation" diff --git a/src/notebooks/55-control-order-of-groups-in-violinplot-seaborn.ipynb b/src/notebooks/55-control-order-of-groups-in-violinplot-seaborn.ipynb index 4dfef6e992..5c1a5cc1d4 100644 --- a/src/notebooks/55-control-order-of-groups-in-violinplot-seaborn.ipynb +++ b/src/notebooks/55-control-order-of-groups-in-violinplot-seaborn.ipynb @@ -2,7 +2,7 @@ "cells": [ { "source": [ - "## Directly specyfing a list \n", + "## Directly specifying a list \n", "Thanks to the 'order' parameter of the violinplot function, you can set the order in which you expect the distributions to appear on the figure." ], "cell_type": "markdown", @@ -78,7 +78,7 @@ ], "metadata": { "title": "Manage the order of groups in seaborn violinplot", - "description": "One could decide to change the order in which groups appear in a given plot, wether it be for the sake of clarity or other reasons. This can be performed with the 'order' parameter, either by specifying directly the order of the groups through a list, or by generating an ordered list based on the groups corresponding mean for example.", + "description": "One could decide to change the order in which groups appear in a given plot, whether it be for the sake of clarity or other reasons. This can be performed with the 'order' parameter, either by specifying directly the order of the groups through a list, or by generating an ordered list based on the groups corresponding mean for example.", "family": "distribution", "chartType": "violin", "slug": "55-control-order-of-groups-in-violinplot-seaborn", diff --git a/src/notebooks/550-intro-table-with-pandas.ipynb b/src/notebooks/550-intro-table-with-pandas.ipynb index 2b93353083..f9a00b18a7 100644 --- a/src/notebooks/550-intro-table-with-pandas.ipynb +++ b/src/notebooks/550-intro-table-with-pandas.ipynb @@ -9,7 +9,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot creating the charts\n", "- [pandas](https://python-graph-gallery.com/pandas/) is used to put the data into a dataframe and custom the table\n", "- `numpy` is used to generate some data\n", diff --git a/src/notebooks/551-student-t-test-visualization.ipynb b/src/notebooks/551-student-t-test-visualization.ipynb index de570d32ee..1e3d2230fd 100644 --- a/src/notebooks/551-student-t-test-visualization.ipynb +++ b/src/notebooks/551-student-t-test-visualization.ipynb @@ -8,7 +8,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot creating the charts\n", "- [pandas](https://python-graph-gallery.com/pandas/) is used to put the data into a dataframe\n", "- `numpy` is used to generate some data\n", @@ -64,7 +64,7 @@ "source": [ "## Get statistical values\n", "\n", - "First, we'll start by retrive the values we want to add on the plot: the **p value** and the **t statistic**. For this, we need to use the `ttest_rel()` function from `scipy`.\n", + "First, we'll start by retrieve the values we want to add on the plot: the **p value** and the **t statistic**. For this, we need to use the `ttest_rel()` function from `scipy`.\n", "\n", "Also, we retrieve the **mean** of each group.\n", "\n", diff --git a/src/notebooks/552-table-combined-with-plot.ipynb b/src/notebooks/552-table-combined-with-plot.ipynb index 5f692e9307..0382b62885 100644 --- a/src/notebooks/552-table-combined-with-plot.ipynb +++ b/src/notebooks/552-table-combined-with-plot.ipynb @@ -8,7 +8,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot creating the charts\n", "- [pandas](https://python-graph-gallery.com/pandas/) is used to put the data into a dataframe and custom the table\n", "- `numpy` for data generation" @@ -194,7 +194,7 @@ "plt.xticks([])\n", "plt.title('Loss by Disaster')\n", "\n", - "# Dislay the chart\n", + "# Display the chart\n", "plt.show()" ] }, diff --git a/src/notebooks/555-candle-stick-with-moving-average-plotly.ipynb b/src/notebooks/555-candle-stick-with-moving-average-plotly.ipynb index a4d3a736a9..10f0cb3f7b 100644 --- a/src/notebooks/555-candle-stick-with-moving-average-plotly.ipynb +++ b/src/notebooks/555-candle-stick-with-moving-average-plotly.ipynb @@ -3018,7 +3018,7 @@ "\n", "To make our graph **easier to read** and **more informative**, we can change the `colors` of the bars and moving averages.\n", "\n", - "- **change color**: add a `line` argument (dictionnary) with the properties wanted (color, width and shape)\n", + "- **change color**: add a `line` argument (dictionary) with the properties wanted (color, width and shape)\n", "- **add legend**: add a `name` argument with the text we want" ] }, diff --git a/src/notebooks/556-visualize-linear-regression.ipynb b/src/notebooks/556-visualize-linear-regression.ipynb index 43006c4423..179a028d8e 100644 --- a/src/notebooks/556-visualize-linear-regression.ipynb +++ b/src/notebooks/556-visualize-linear-regression.ipynb @@ -8,7 +8,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot creating the charts\n", "- [pandas](https://python-graph-gallery.com/pandas/) is used to put the data into a dataframe\n", "- `scikit-learn` is used to create the linear regression\n", @@ -65,7 +65,7 @@ "source": [ "## Get model parameters\n", "\n", - "First, we'll start by **retrive the values** we want. For this, we need to use the `LinearRegression()` object from `scikit-learn` and fit it to our data. \n", + "First, we'll start by **retrieve the values** we want. For this, we need to use the `LinearRegression()` object from `scikit-learn` and fit it to our data. \n", "\n", "*This post does not cover any statistical/math details*" ] @@ -322,7 +322,7 @@ "\n", "This post explains how to represent the **results of a linear regression** in a [scatter plot](https://python-graph-gallery.com/scatter-plot/).\n", "\n", - "For more examples of **charts with statistics**, see the [statistics section](https://python-graph-gallery.com/statistics/). You may also be interested in how to [create a highly cutomized scatter plot with regression](https://python-graph-gallery.com/web-scatterplot-text-annotation-and-regression-matplotlib/)" + "For more examples of **charts with statistics**, see the [statistics section](https://python-graph-gallery.com/statistics/). You may also be interested in how to [create a highly customized scatter plot with regression](https://python-graph-gallery.com/web-scatterplot-text-annotation-and-regression-matplotlib/)" ] } ], diff --git a/src/notebooks/557-anova-visualization-with-matplotlib.ipynb b/src/notebooks/557-anova-visualization-with-matplotlib.ipynb index 717948a10e..dc7e8df490 100644 --- a/src/notebooks/557-anova-visualization-with-matplotlib.ipynb +++ b/src/notebooks/557-anova-visualization-with-matplotlib.ipynb @@ -9,7 +9,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for plot creating the charts\n", "- [pandas](https://python-graph-gallery.com/pandas/) is used to put the data into a dataframe\n", "- `numpy` is used to generate some data\n", diff --git a/src/notebooks/564-publication-ready-table-with-plottable.ipynb b/src/notebooks/564-publication-ready-table-with-plottable.ipynb index 42a2cc0534..356cde4e37 100644 --- a/src/notebooks/564-publication-ready-table-with-plottable.ipynb +++ b/src/notebooks/564-publication-ready-table-with-plottable.ipynb @@ -16,7 +16,7 @@ "- education and infrastructure\n", "\n", "## Libraries\n", - "First, you need to install `plottable` with the following command: `pip install plottable`. If you're not familar with `plottable` yet, the [table section of the gallery](https://python-graph-gallery.com/table/) has some great tutorials to get started.\n", + "First, you need to install `plottable` with the following command: `pip install plottable`. If you're not familiar with `plottable` yet, the [table section of the gallery](https://python-graph-gallery.com/table/) has some great tutorials to get started.\n", "\n", "We'll also need the following libraries:\n", "\n", diff --git a/src/notebooks/589-how-to-change-coordinate-system.ipynb b/src/notebooks/589-how-to-change-coordinate-system.ipynb index 499dd38214..de923fd8d4 100644 --- a/src/notebooks/589-how-to-change-coordinate-system.ipynb +++ b/src/notebooks/589-how-to-change-coordinate-system.ipynb @@ -32,7 +32,7 @@ "source": [ "## Coordinates\n", "\n", - "[Matplotlib](/matplotlib) provides a way to change and specify which coordinates system to use with exhaustive possibilites:\n", + "[Matplotlib](/matplotlib) provides a way to change and specify which coordinates system to use with exhaustive possibilities:\n", "\n", "- the figure?\n", "- the axes?\n", diff --git a/src/notebooks/592-non-contiguous-cartogram-in-python.ipynb b/src/notebooks/592-non-contiguous-cartogram-in-python.ipynb index 3490eec3f4..e8cb28d886 100644 --- a/src/notebooks/592-non-contiguous-cartogram-in-python.ipynb +++ b/src/notebooks/592-non-contiguous-cartogram-in-python.ipynb @@ -561,7 +561,7 @@ } ], "source": [ - "# adjustement mapping for label positions\n", + "# adjustment mapping for label positions\n", "adjustments = {\n", " 'Japan': (6, 0),\n", " 'Philippines': (8, 0),\n", diff --git a/src/notebooks/73-control-bandwidth-of-seaborn-density-plot.ipynb b/src/notebooks/73-control-bandwidth-of-seaborn-density-plot.ipynb index c6675948ea..8ff1324625 100644 --- a/src/notebooks/73-control-bandwidth-of-seaborn-density-plot.ipynb +++ b/src/notebooks/73-control-bandwidth-of-seaborn-density-plot.ipynb @@ -44,7 +44,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Defaut density plot\n", + "## Default density plot\n", "\n", "[Density plot](https://python-graph-gallery.com/density-plot/) differ from histogram in that they are **smoothed versions** of the [histogram](https://python-graph-gallery.com/histogram/).\n", "\n", diff --git a/src/notebooks/91-customize-seaborn-heatmap.ipynb b/src/notebooks/91-customize-seaborn-heatmap.ipynb index eff7999ea0..a3147e4e71 100644 --- a/src/notebooks/91-customize-seaborn-heatmap.ipynb +++ b/src/notebooks/91-customize-seaborn-heatmap.ipynb @@ -118,7 +118,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "`yticklabels` and `xticklabels` control the presence / abscence of labels for the Y and X axis respectively.\n" + "`yticklabels` and `xticklabels` control the presence / absence of labels for the Y and X axis respectively.\n" ] }, { diff --git a/src/notebooks/92-control-color-in-seaborn-heatmaps.ipynb b/src/notebooks/92-control-color-in-seaborn-heatmaps.ipynb index 36bfd65561..7dfd4963bd 100644 --- a/src/notebooks/92-control-color-in-seaborn-heatmaps.ipynb +++ b/src/notebooks/92-control-color-in-seaborn-heatmaps.ipynb @@ -47,7 +47,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can customize the colors in your heatmap with the `cmap` parameter of the `heatmap()` function in seaborn. The following examples show the appearences of different sequential color palettes.\n", + "You can customize the colors in your heatmap with the `cmap` parameter of the `heatmap()` function in seaborn. The following examples show the appearances of different sequential color palettes.\n", "\n", "It's non-exhaustive but it gives you an idea of what **available palettes** can look like.\n" ] diff --git a/src/notebooks/advanced-custom-annotations-matplotlib.ipynb b/src/notebooks/advanced-custom-annotations-matplotlib.ipynb index 714b2759a7..0d251caf49 100644 --- a/src/notebooks/advanced-custom-annotations-matplotlib.ipynb +++ b/src/notebooks/advanced-custom-annotations-matplotlib.ipynb @@ -16,7 +16,7 @@ "- provide **additional** information\n", "- simply **explain** the data in more depth\n", "\n", - "However, it can be quite technicaly challenging to customize annotations in [matplotlib](https://python-graph-gallery.com/matplotlib/), especially if you want specific text highlighting such as **word in bold, italic or colored differently**.\n", + "However, it can be quite technically challenging to customize annotations in [matplotlib](https://python-graph-gallery.com/matplotlib/), especially if you want specific text highlighting such as **word in bold, italic or colored differently**.\n", "\n", "Let's see how we can create nice annotations in a few examples.\n" ] diff --git a/src/notebooks/basic-barplot-with-seaborn.ipynb b/src/notebooks/basic-barplot-with-seaborn.ipynb index 20e5ba5b8f..8ae778c4f1 100644 --- a/src/notebooks/basic-barplot-with-seaborn.ipynb +++ b/src/notebooks/basic-barplot-with-seaborn.ipynb @@ -136,14 +136,14 @@ "# Set the figure size\n", "plt.figure(figsize=(14, 10))\n", "\n", - "# plot a bar chart with given order of bars [\"Fri\",\"Thur\",\"Sun\",\"Sat\"]\n", + "# plot a bar chart with given order of bars [\"Fri\",\"Their\",\"Sun\",\"Sat\"]\n", "sns.barplot(\n", " x=\"total_bill\", \n", " y=\"day\", \n", " data=tips, \n", " estimator=sum, \n", " ci=None, \n", - " order=[\"Fri\",\"Thur\",\"Sun\",\"Sat\"], \n", + " order=[\"Fri\",\"Their\",\"Sun\",\"Sat\"], \n", " color='#69b3a2'\n", ");" ] diff --git a/src/notebooks/basic-histogram-in-matplotlib.ipynb b/src/notebooks/basic-histogram-in-matplotlib.ipynb index b720c2580d..8a2150655f 100644 --- a/src/notebooks/basic-histogram-in-matplotlib.ipynb +++ b/src/notebooks/basic-histogram-in-matplotlib.ipynb @@ -308,7 +308,7 @@ "source": [ "## Add annotation\n", "\n", - "And finally, let's see how to add a vertical line indicating some interesting quantity. In this case, the line is going to reprsent the median hours of work per week.\n", + "And finally, let's see how to add a vertical line indicating some interesting quantity. In this case, the line is going to represent the median hours of work per week.\n", "\n", "Note: read this [specific blogpost](https://python-graph-gallery.com/193-annotate-matplotlib-chart) of the gallery for more on matplotlib annotation.\n" ] diff --git a/src/notebooks/basic-sankey-diagram-with-pysankey.ipynb b/src/notebooks/basic-sankey-diagram-with-pysankey.ipynb index 95dff103d5..fecce6215b 100644 --- a/src/notebooks/basic-sankey-diagram-with-pysankey.ipynb +++ b/src/notebooks/basic-sankey-diagram-with-pysankey.ipynb @@ -32,7 +32,7 @@ "\n", "Let's import the `fruits.txt` dataset that comes with the library. Here we download it from the [github repository](https://raw.githubusercontent.com/anazalea/pySankey/master/pysankey/fruits.txt).\n", "\n", - "The dataset has 2 columns only. Each row describes a connection, with the origin in the first column and the destination in the second. If a connection has several occurences in the dataset (the same row appears many times), its weight will be higher and the connection on the diagram will be bigger.\n", + "The dataset has 2 columns only. Each row describes a connection, with the origin in the first column and the destination in the second. If a connection has several occurrences in the dataset (the same row appears many times), its weight will be higher and the connection on the diagram will be bigger.\n", "\n", "The `sankey()` function is used to draw the diagram. It takes at least 2 arguments as input: the origin and destination columns:" ], diff --git a/src/notebooks/bubble-plot-with-seaborn.ipynb b/src/notebooks/bubble-plot-with-seaborn.ipynb index 991060d4a6..9e06f3298c 100644 --- a/src/notebooks/bubble-plot-with-seaborn.ipynb +++ b/src/notebooks/bubble-plot-with-seaborn.ipynb @@ -42,7 +42,7 @@ "- `x` : The data position on the x axis\n", "- `y` : The data position on the y axis\n", "- `size` : Grouping variable that will produce points with different sizes\n", - "- `alpha` : Transparancy ratio\n", + "- `alpha` : Transparency ratio\n", "\n", "Here, the **gapminder** data set is used and the relationship between life expectancy (y) and gdp per capita (x) of world countries is represented. The population of each country is represented through dot size.\n" ] diff --git a/src/notebooks/calendar-heatmaps-with-python-and-matplotlib.ipynb b/src/notebooks/calendar-heatmaps-with-python-and-matplotlib.ipynb index a2dc65ffe7..a6c59bdc56 100644 --- a/src/notebooks/calendar-heatmaps-with-python-and-matplotlib.ipynb +++ b/src/notebooks/calendar-heatmaps-with-python-and-matplotlib.ipynb @@ -170,7 +170,7 @@ "- `values`: value for each date\n", "- `start_date`: when should the calendar heatmap start?\n", "- `end_date`: when should the calendar heatmap end?\n", - "- `ax`: the matplotlib Axes to use. Optionnal but recommended to avoid unexpected results.\n" + "- `ax`: the matplotlib Axes to use. Optional but recommended to avoid unexpected results.\n" ] }, { diff --git a/src/notebooks/categorical-color-palette.ipynb b/src/notebooks/categorical-color-palette.ipynb index bac4b507ef..e9a1b01d05 100644 --- a/src/notebooks/categorical-color-palette.ipynb +++ b/src/notebooks/categorical-color-palette.ipynb @@ -270,7 +270,7 @@ } ], "source": [ - "# Iniate a figure for the scatter plot\n", + "# Initiate a figure for the scatter plot\n", "fig, ax = plt.subplots(dpi=300)\n", "\n", "# Define our colormap\n", diff --git a/src/notebooks/chord-diagram-python-chord.ipynb b/src/notebooks/chord-diagram-python-chord.ipynb index fff5b73489..fe0cb9d53d 100644 --- a/src/notebooks/chord-diagram-python-chord.ipynb +++ b/src/notebooks/chord-diagram-python-chord.ipynb @@ -168,7 +168,7 @@ "\n", "\n", "# Basic cord diagram\n", - "# TODO THIS WON'T WORK BECAUSE INPUT TYPE ISNT RECOGNIZE\n", + "# TODO THIS WON'T WORK BECAUSE INPUT TYPE ISN'T RECOGNIZE\n", "# Chord(data, names).to_html(\"../../static/interactiveCharts/chord-diagram-chord-library.html\")" ] }, diff --git a/src/notebooks/choropleth-map-plotly-python.ipynb b/src/notebooks/choropleth-map-plotly-python.ipynb index c1551dbe70..39d34c77a8 100644 --- a/src/notebooks/choropleth-map-plotly-python.ipynb +++ b/src/notebooks/choropleth-map-plotly-python.ipynb @@ -18755,7 +18755,7 @@ "COUNTY": "180", "GEO_ID": "0500000US02180", "LSAD": "CA", - "NAME": "Nome", + "NAME": "Gnome", "STATE": "02" }, "type": "Feature" @@ -55006,7 +55006,7 @@ "COUNTY": "285", "GEO_ID": "0500000US13285", "LSAD": "County", - "NAME": "Troup", + "NAME": "Troupe", "STATE": "13" }, "type": "Feature" @@ -57114,7 +57114,7 @@ "COUNTY": "033", "GEO_ID": "0500000US22033", "LSAD": "Parish", - "NAME": "East Baton Rouge", + "NAME": "East Baton Rogue", "STATE": "22" }, "type": "Feature" @@ -61513,7 +61513,7 @@ "COUNTY": "121", "GEO_ID": "0500000US22121", "LSAD": "Parish", - "NAME": "West Baton Rouge", + "NAME": "West Baton Rogue", "STATE": "22" }, "type": "Feature" @@ -61576,7 +61576,7 @@ "COUNTY": "127", "GEO_ID": "0500000US22127", "LSAD": "Parish", - "NAME": "Winn", + "NAME": "Win", "STATE": "22" }, "type": "Feature" @@ -311880,7 +311880,7 @@ "COUNTY": "165", "GEO_ID": "0500000US18165", "LSAD": "County", - "NAME": "Vermillion", + "NAME": "Vermilion", "STATE": "18" }, "type": "Feature" @@ -396422,7 +396422,7 @@ "COUNTY": "067", "GEO_ID": "0500000US31067", "LSAD": "County", - "NAME": "Gage", + "NAME": "Gauge", "STATE": "31" }, "type": "Feature" diff --git a/src/notebooks/circular-barplot-basic.ipynb b/src/notebooks/circular-barplot-basic.ipynb index c6b2e74c89..89be5cafd1 100644 --- a/src/notebooks/circular-barplot-basic.ipynb +++ b/src/notebooks/circular-barplot-basic.ipynb @@ -342,7 +342,7 @@ "ax = plt.subplot(111, polar=True)\n", "plt.axis('off')\n", "\n", - "# Constants = parameters controling the plot layout:\n", + "# Constants = parameters controlling the plot layout:\n", "upperLimit = 100\n", "lowerLimit = 30\n", "labelPadding = 4\n", diff --git a/src/notebooks/circular-packing-several-levels-of-hierarchy.ipynb b/src/notebooks/circular-packing-several-levels-of-hierarchy.ipynb index 253245fc8c..e3c4ee5357 100644 --- a/src/notebooks/circular-packing-several-levels-of-hierarchy.ipynb +++ b/src/notebooks/circular-packing-several-levels-of-hierarchy.ipynb @@ -120,7 +120,7 @@ "source": [ "Let's be honnest, that's quite a bit of code to get a decent graph 😞. The `circlize` library has a `bubble()` function that allows to do a simple circle pack with one line of code, but it does not allow to customize the chart.\n", "\n", - "So once more `matplotlib` is our best friend for the rendering part. Here I'm printing the layers from the bottom to the top of the figure: first the cirles for the highest level of hierarchy (continent), then circle and labels for countries, then continent labels.\n" + "So once more `matplotlib` is our best friend for the rendering part. Here I'm printing the layers from the bottom to the top of the figure: first the circles for the highest level of hierarchy (continent), then circle and labels for countries, then continent labels.\n" ] }, { diff --git a/src/notebooks/continuous-color-palette.ipynb b/src/notebooks/continuous-color-palette.ipynb index 50a19aa2c4..dc84dc16ba 100644 --- a/src/notebooks/continuous-color-palette.ipynb +++ b/src/notebooks/continuous-color-palette.ipynb @@ -273,7 +273,7 @@ } ], "source": [ - "# Iniate a figure for the scatter plot\n", + "# Initiate a figure for the scatter plot\n", "fig, axs = plt.subplots(ncols=2, dpi=300, figsize=(10, 5))\n", "\n", "# Define our colormaps\n", @@ -317,7 +317,7 @@ ], "metadata": { "chartType": "colors", - "description": "This post explains how to use matplotlib continuous palettes, how to use them in practice and how to create your own.

Matplotlib has built-in tools that make it easy to use continous palettes by having a set of predefined palettes and functions to create custom ones.", + "description": "This post explains how to use matplotlib continuous palettes, how to use them in practice and how to create your own.

Matplotlib has built-in tools that make it easy to use continuous palettes by having a set of predefined palettes and functions to create custom ones.", "family": "general", "kernelspec": { "display_name": "venv", diff --git a/src/notebooks/create-your-own-color-maps.ipynb b/src/notebooks/create-your-own-color-maps.ipynb index 50d92a1cee..e98c46a6d4 100644 --- a/src/notebooks/create-your-own-color-maps.ipynb +++ b/src/notebooks/create-your-own-color-maps.ipynb @@ -81,7 +81,7 @@ "x = np.random.randn(size),\n", "y = np.random.randn(size),\n", "\n", - "# Iniate a figure for the scatter plot\n", + "# Initiate a figure for the scatter plot\n", "fig, ax = plt.subplots(dpi=300)\n", "\n", "# Create a scatter plot\n", diff --git a/src/notebooks/custom-fonts-in-matplotlib.ipynb b/src/notebooks/custom-fonts-in-matplotlib.ipynb index def17b80a7..e31feb6b52 100644 --- a/src/notebooks/custom-fonts-in-matplotlib.ipynb +++ b/src/notebooks/custom-fonts-in-matplotlib.ipynb @@ -355,7 +355,7 @@ "font_manager.findSystemFonts(fontpaths=None, fontext=\"ttf\")\n", "```\n", "\n", - "6. Check the fonts are accesible by Matplotlib with\n", + "6. Check the fonts are accessible by Matplotlib with\n", "\n", "```python\n", "font_manager.findfont(\"Hydrophilia Iced\") # Test with \"Special Elite\" too\n", @@ -405,7 +405,7 @@ "source": [ "## Plot\n", "\n", - "Now that we've covered how to make fonts accesible by Matplotlib, it's a good time to plot something and see how these two new fonts look like!\n" + "Now that we've covered how to make fonts accessible by Matplotlib, it's a good time to plot something and see how these two new fonts look like!\n" ] }, { @@ -456,7 +456,7 @@ ], "metadata": { "chartType": "cheatSheets", - "description": "A blogpost showing how to use custom fonts in Python and Matplotlib. This blogpost contains a step-by-step guide showing how to make fonts accesible by Matplotlib and a examples with multiple fonts.", + "description": "A blogpost showing how to use custom fonts in Python and Matplotlib. This blogpost contains a step-by-step guide showing how to make fonts accessible by Matplotlib and a examples with multiple fonts.", "family": "general", "kernelspec": { "display_name": "venv", @@ -467,7 +467,7 @@ "language_info": { "name": "python" }, - "seoDescription": "This post explains how to import fonts in Matplotlib and use them to create better-looking visualizations. Step by step instructions on how to install fonts and make them accesible to matplotlib are provided.", + "seoDescription": "This post explains how to import fonts in Matplotlib and use them to create better-looking visualizations. Step by step instructions on how to install fonts and make them accessible to matplotlib are provided.", "slug": "custom-fonts-in-matplotlib", "title": "Custom fonts in Python and Matplotlib" }, diff --git a/src/notebooks/custom-legend-with-matplotlib.ipynb b/src/notebooks/custom-legend-with-matplotlib.ipynb index 89e39022c6..361f0a335e 100644 --- a/src/notebooks/custom-legend-with-matplotlib.ipynb +++ b/src/notebooks/custom-legend-with-matplotlib.ipynb @@ -570,7 +570,7 @@ "\n", "One can store the object returned by `ax.legend()` and do lot of interesting things with it.\n", "\n", - "The legend returned has a method `.get_texts()` that return a list of `matplotlib.text.Text` objects. These objects have **a lot** of methods one can use to customize the appearence of the text." + "The legend returned has a method `.get_texts()` that return a list of `matplotlib.text.Text` objects. These objects have **a lot** of methods one can use to customize the appearance of the text." ] }, { @@ -1045,7 +1045,7 @@ ], "metadata": { "chartType": "scatter", - "description": "This post explains how to customize the legend on a chart with matplotlib.

It provides many examples covering the most common use cases like controling the legend location, adding a legend title or customizing the legend markers and labels.", + "description": "This post explains how to customize the legend on a chart with matplotlib.

It provides many examples covering the most common use cases like controlling the legend location, adding a legend title or customizing the legend markers and labels.", "family": "correlation", "interpreter": { "hash": "dca0ade3e726a953b501b15e8e990130d2b7799f14cfd9f4271676035ebe5511" diff --git a/src/notebooks/density-chart-multiple-groups-seaborn.ipynb b/src/notebooks/density-chart-multiple-groups-seaborn.ipynb index bde972dd28..966e3fb4b0 100644 --- a/src/notebooks/density-chart-multiple-groups-seaborn.ipynb +++ b/src/notebooks/density-chart-multiple-groups-seaborn.ipynb @@ -11,7 +11,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "A **multi density** chart allows to compare the distribution of several groups. Unfortunatelly, this type of charts tend to get **cluttered**: groups overlap each other and the figure gets unreadable. An easy workaround is to use **transparency**. However, it won’t solve the issue completely and it is often better to consider other options suggested further in this post.\n" + "A **multi density** chart allows to compare the distribution of several groups. Unfortunately, this type of charts tend to get **cluttered**: groups overlap each other and the figure gets unreadable. An easy workaround is to use **transparency**. However, it won’t solve the issue completely and it is often better to consider other options suggested further in this post.\n" ] }, { @@ -312,7 +312,7 @@ "pygments_lexer": "ipython3", "version": "3.10.13" }, - "seoDescription": "Plotting multiple groups on a denstiy chart with annotations using seaborn", + "seoDescription": "Plotting multiple groups on a density chart with annotations using seaborn", "slug": "density-chart-multiple-groups-seaborn", "title": "Density Chart with Multiple Groups" }, diff --git a/src/notebooks/density-mirror.ipynb b/src/notebooks/density-mirror.ipynb index f48909d34f..7e066e4088 100644 --- a/src/notebooks/density-mirror.ipynb +++ b/src/notebooks/density-mirror.ipynb @@ -141,7 +141,7 @@ ], "metadata": { "chartType": "density", - "description": "It is a challange to compare the distribution of two variables in the same figure. This post shows how to tackle it with the mirror density and histogram charts using the seaborn and matplotlib libraries.", + "description": "It is a challenge to compare the distribution of two variables in the same figure. This post shows how to tackle it with the mirror density and histogram charts using the seaborn and matplotlib libraries.", "family": "distribution", "kernelspec": { "display_name": "Python 3", @@ -161,7 +161,7 @@ "pygments_lexer": "ipython3", "version": "3.8.3-final" }, - "seoDescription": "Plotting mirror denstiy and histogram charts to compare the distribution of two variables", + "seoDescription": "Plotting mirror density and histogram charts to compare the distribution of two variables", "slug": "density-mirror", "title": "Mirror Density and Histogram Chart" }, diff --git a/src/notebooks/heatmap-for-timeseries-matplotlib.ipynb b/src/notebooks/heatmap-for-timeseries-matplotlib.ipynb index 610b98ba6a..faf0c700bf 100644 --- a/src/notebooks/heatmap-for-timeseries-matplotlib.ipynb +++ b/src/notebooks/heatmap-for-timeseries-matplotlib.ipynb @@ -279,7 +279,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The white cell represents a **missing value**. There are 5 missings in this data." + "The white cell represents a **missing value**. There are 5 missing in this data." ] }, { diff --git a/src/notebooks/hexbin-map-from-geojson-python.ipynb b/src/notebooks/hexbin-map-from-geojson-python.ipynb index 6a4be590a8..ea7ded2b47 100644 --- a/src/notebooks/hexbin-map-from-geojson-python.ipynb +++ b/src/notebooks/hexbin-map-from-geojson-python.ipynb @@ -192,7 +192,7 @@ }, { "source": [ - "Let's transform the useless hexbin map above in a choropleth map, where each county is colored according to its mariage rate (# of mariage per 1000 inhabitants). The dataset is available [here](https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/master/static/data/State_mariage_rate.csv)" + "Let's transform the useless hexbin map above in a choropleth map, where each county is colored according to its marriage rate (# of marriage per 1000 inhabitants). The dataset is available [here](https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/master/static/data/State_mariage_rate.csv)" ], "cell_type": "markdown", "metadata": {} @@ -203,14 +203,14 @@ "metadata": {}, "outputs": [], "source": [ - "# Read the mariage data stored on github:\n", + "# Read the marriage data stored on github:\n", "import pandas as pd\n", "mariageData = pd.read_csv(\"https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/master/static/data/State_mariage_rate.csv\")\n", "\n", "# Add a new column to the geo dataframe that will be used for joining:\n", "geoData['state'] = geoData['google_name'].str.replace(' \\(United States\\)','')\n", "\n", - "# Merge the mariage dataset with the geospatial information\n", + "# Merge the marriage dataset with the geospatial information\n", "geoData = geoData.set_index('state').join(mariageData.set_index('state'))\n" ] }, diff --git a/src/notebooks/how-to-custom-title-matplotlib.ipynb b/src/notebooks/how-to-custom-title-matplotlib.ipynb index fb1b4d6ccb..aa757df580 100644 --- a/src/notebooks/how-to-custom-title-matplotlib.ipynb +++ b/src/notebooks/how-to-custom-title-matplotlib.ipynb @@ -15,7 +15,7 @@ "- provide **additional** information\n", "- simply **explain** the data in more depth\n", "\n", - "However, it can be quite technicaly challenging to customize annotations in [matplotlib](/matplotlib).\n", + "However, it can be quite technically challenging to customize annotations in [matplotlib](/matplotlib).\n", "\n", "Let's see how we can create nice titles in a few examples.\n" ] diff --git a/src/notebooks/how-to-remove-axis-in-matplotlib.ipynb b/src/notebooks/how-to-remove-axis-in-matplotlib.ipynb index bd40e6ad4f..e89a564062 100644 --- a/src/notebooks/how-to-remove-axis-in-matplotlib.ipynb +++ b/src/notebooks/how-to-remove-axis-in-matplotlib.ipynb @@ -246,7 +246,7 @@ ], "metadata": { "chartType": "correlogram", - "description": "The aim of this post is to show you how to remove certain axis from a vizualisation that is made up of multiple subplots. To do so, we build a pairplot or correlogram from scratch and show how to remove empty axis from the final chart.", + "description": "The aim of this post is to show you how to remove certain axis from a visualisation that is made up of multiple subplots. To do so, we build a pairplot or correlogram from scratch and show how to remove empty axis from the final chart.", "family": "correlation", "kernelspec": { "display_name": "plots", diff --git a/src/notebooks/pie-plot-matplotlib-basic.ipynb b/src/notebooks/pie-plot-matplotlib-basic.ipynb index fa01f0fe94..324e89833f 100644 --- a/src/notebooks/pie-plot-matplotlib-basic.ipynb +++ b/src/notebooks/pie-plot-matplotlib-basic.ipynb @@ -57,7 +57,7 @@ }, { "source": [ - "Labels are added thanks to the `labels` parameter that expect an array of strings. You also problably want to play with the `labeldistance` parameter that controls the distance between the circle edge and the label itself. (1= exactly on it, use something bigger to have the label further.)" + "Labels are added thanks to the `labels` parameter that expect an array of strings. You also probably want to play with the `labeldistance` parameter that controls the distance between the circle edge and the label itself. (1= exactly on it, use something bigger to have the label further.)" ], "cell_type": "markdown", "metadata": {} diff --git a/src/notebooks/ridgeline-graph-plotly.ipynb b/src/notebooks/ridgeline-graph-plotly.ipynb index 7c795e739e..5808be1ecc 100644 --- a/src/notebooks/ridgeline-graph-plotly.ipynb +++ b/src/notebooks/ridgeline-graph-plotly.ipynb @@ -1532,8 +1532,8 @@ ], "source": [ "# the idea behind this ridgeline plot with Plotly is to add traces manually, each trace corresponding to a particular year's temperature distribution\n", - "# thus, we are to store each year's data (temperatures and their respective count) in seperate arrays or pd.series that we store in a dictionnary to retrieve them easily\n", - "array_dict = {} # instantiating an empty dictionnary\n", + "# thus, we are to store each year's data (temperatures and their respective count) in separate arrays or pd.series that we store in a dictionary to retrieve them easily\n", + "array_dict = {} # instantiating an empty dictionary\n", "for year in year_list:\n", " array_dict[f'x_{year}'] = temp[temp['year']==year]['Mean_TemperatureC'] # storing the temperature data for each year\n", " array_dict[f'y_{year}'] = temp[temp['year']==year]['count'] # storing the temperature count for each year\n", diff --git a/src/notebooks/ridgeline-graph-seaborn.ipynb b/src/notebooks/ridgeline-graph-seaborn.ipynb index 91bc460f88..bf375e37dc 100644 --- a/src/notebooks/ridgeline-graph-seaborn.ipynb +++ b/src/notebooks/ridgeline-graph-seaborn.ipynb @@ -21,7 +21,7 @@ "temp = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2016-weather-data-seattle.csv') # we retrieve the data from plotly's GitHub repository\n", "temp['month'] = pd.to_datetime(temp['Date']).dt.month # we store the month in a separate column\n", "\n", - "# we define a dictionnary with months that we'll use later\n", + "# we define a dictionary with months that we'll use later\n", "month_dict = {1: 'january',\n", " 2: 'february',\n", " 3: 'march',\n", @@ -38,7 +38,7 @@ "# we create a 'month' column\n", "temp['month'] = temp['month'].map(month_dict)\n", "\n", - "# we generate a pd.Serie with the mean temperature for each month (used later for colors in the FacetGrid plot), and we create a new column in temp dataframe\n", + "# we generate a pd.Series with the mean temperature for each month (used later for colors in the FacetGrid plot), and we create a new column in temp dataframe\n", "month_mean_serie = temp.groupby('month')['Mean_TemperatureC'].mean()\n", "temp['mean_month'] = temp['month'].map(month_mean_serie)" ], diff --git a/src/notebooks/streamchart-basic-matplotlib.ipynb b/src/notebooks/streamchart-basic-matplotlib.ipynb index 7742d59929..00602fb10b 100644 --- a/src/notebooks/streamchart-basic-matplotlib.ipynb +++ b/src/notebooks/streamchart-basic-matplotlib.ipynb @@ -190,7 +190,7 @@ "source": [ "## Use a grid to make it smoother\n", "\n", - "It's definetely better than the previous result, but it's not the panacea either. The plot looks spiky yet. The problem is the Gaussian curve is evaluated at very few data points because we're using the values of `x`. In this case, it's possible to use a `grid` that spans the same range than `x`, but is much denser. The function and the plot then look as follows:" + "It's definitely better than the previous result, but it's not the panacea either. The plot looks spiky yet. The problem is the Gaussian curve is evaluated at very few data points because we're using the values of `x`. In this case, it's possible to use a `grid` that spans the same range than `x`, but is much denser. The function and the plot then look as follows:" ], "metadata": {} }, diff --git a/src/notebooks/web-animated-line-chart-with-annotation.ipynb b/src/notebooks/web-animated-line-chart-with-annotation.ipynb index 99fd2fa408..7fcd041d13 100644 --- a/src/notebooks/web-animated-line-chart-with-annotation.ipynb +++ b/src/notebooks/web-animated-line-chart-with-annotation.ipynb @@ -587,9 +587,9 @@ "\n", "- with this information, we can find **which event** should be currently highlighted and display the corresponding text. The function will ensure that **only one event** is highlighted at a time.\n", "\n", - "- this function is then used in the `update()` function to display the event that is currently happening. In pratice a `for` loop is used on each event to test whether it should be highlighted or not. This makes very easy to **add/remove** new events in the future.\n", + "- this function is then used in the `update()` function to display the event that is currently happening. In practice a `for` loop is used on each event to test whether it should be highlighted or not. This makes very easy to **add/remove** new events in the future.\n", "\n", - "- the loop uses the `dates_highlight`, `event_end_dates`, `adjustements`, `event_texts` lists to get all the information needed to highlight the events, and those lists are defined at the beginning of the script.\n", + "- the loop uses the `dates_highlight`, `event_end_dates`, `adjustments`, `event_texts` lists to get all the information needed to highlight the events, and those lists are defined at the beginning of the script.\n", "\n", "We also add the **years in the background** by using once again the `highlight_text` package. The code is right after:\n", "\n", @@ -642,7 +642,7 @@ "event_end_dates = dates_highlight[1:] + [end_date + delay_years]\n", "\n", "# position adjustments for each event\n", - "adjustements = [\n", + "adjustments = [\n", " (0, 0),\n", " (0, 10),\n", " (2, 5),\n", @@ -784,7 +784,7 @@ " )\n", "\n", " # annotate events\n", - " for event_date, end_date, adj, event_text in zip(dates_highlight, event_end_dates, adjustements, event_texts):\n", + " for event_date, end_date, adj, event_text in zip(dates_highlight, event_end_dates, adjustments, event_texts):\n", " annot_event(year, event_date, end_date, adj, event_text)\n", "\n", " return ax\n", @@ -872,7 +872,7 @@ "event_end_dates = dates_highlight[1:] + [end_date + delay_years]\n", "\n", "# position adjustments for each event\n", - "adjustements = [\n", + "adjustments = [\n", " (0, 0),\n", " (0, 10),\n", " (2, 5),\n", @@ -1042,7 +1042,7 @@ " else:\n", "\n", " # annotate events\n", - " for event_date, end_date, adj, event_text in zip(dates_highlight, event_end_dates, adjustements, event_texts):\n", + " for event_date, end_date, adj, event_text in zip(dates_highlight, event_end_dates, adjustments, event_texts):\n", " annot_event(year, event_date, end_date, adj, event_text)\n", "\n", " return ax\n", @@ -1265,7 +1265,7 @@ "event_end_dates = dates_highlight[1:] + [end_date + delay_years]\n", "\n", "# position adjustments for each event\n", - "adjustements = [\n", + "adjustments = [\n", " (0, 0),\n", " (0, 10),\n", " (2, 5),\n", @@ -1435,7 +1435,7 @@ " else:\n", "\n", " # annotate events\n", - " for event_date, end_date, adj, event_text in zip(dates_highlight, event_end_dates, adjustements, event_texts):\n", + " for event_date, end_date, adj, event_text in zip(dates_highlight, event_end_dates, adjustments, event_texts):\n", " annot_event(year, event_date, end_date, adj, event_text)\n", "\n", " return ax\n", @@ -1540,7 +1540,7 @@ "event_end_dates = dates_highlight[1:] + [end_date + delay_years]\n", "\n", "# position adjustments for each event\n", - "adjustements = [\n", + "adjustments = [\n", " (0, 0),\n", " (0, 10),\n", " (2, 5),\n", @@ -1710,7 +1710,7 @@ " else:\n", "\n", " # annotate events\n", - " for event_date, end_date, adj, event_text in zip(dates_highlight, event_end_dates, adjustements, event_texts):\n", + " for event_date, end_date, adj, event_text in zip(dates_highlight, event_end_dates, adjustments, event_texts):\n", " annot_event(year, event_date, end_date, adj, event_text)\n", "\n", " return ax\n", @@ -1796,7 +1796,7 @@ "pygments_lexer": "ipython3", "version": "3.10.13" }, - "seoDescription": "How to create an animation of a stacked area chart with matplotlib that dislays a text throughout the animation and highlights important events.", + "seoDescription": "How to create an animation of a stacked area chart with matplotlib that displays a text throughout the animation and highlights important events.", "slug": "web-animated-line-chart-with-annotation", "title": "Animation with text that highlights important events" }, diff --git a/src/notebooks/web-barplot-with-annotations-and-arrows.ipynb b/src/notebooks/web-barplot-with-annotations-and-arrows.ipynb index 82a2ab9911..e1a0a6a509 100644 --- a/src/notebooks/web-barplot-with-annotations-and-arrows.ipynb +++ b/src/notebooks/web-barplot-with-annotations-and-arrows.ipynb @@ -25,7 +25,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- [pandas](https://python-graph-gallery.com/pandas/) is used to put the data into a dataframe\n", "- `highlight_text` is used to add custom annotations to the chart\n", diff --git a/src/notebooks/web-bubble-map-with-arrows.ipynb b/src/notebooks/web-bubble-map-with-arrows.ipynb index adc3bd72fb..7af4f8c69d 100644 --- a/src/notebooks/web-bubble-map-with-arrows.ipynb +++ b/src/notebooks/web-bubble-map-with-arrows.ipynb @@ -345,7 +345,7 @@ "\n", "The next step is to **add earthquakes (bubbles)** on the map.\n", "\n", - "For this, we need to **transform the latitude and longitude into the choosen projection** (defined with `proj`) using the `transform_points()` function. Once we have done so, we just use the `scatter()` function from [matplotlib](/matplotlib):\n" + "For this, we need to **transform the latitude and longitude into the chosen projection** (defined with `proj`) using the `transform_points()` function. Once we have done so, we just use the `scatter()` function from [matplotlib](/matplotlib):\n" ] }, { @@ -394,7 +394,7 @@ "\n", "Now that the base of the map is here, we want to give it a **better style**. For this, we:\n", "\n", - "- change backround color with the `set_facecolor()` function\n", + "- change background color with the `set_facecolor()` function\n", "- change bubble color with the `color` argument\n", "- change map edge colors with the `edgecolor` argument\n" ] diff --git a/src/notebooks/web-bubble-plot-with-annotations-and-custom-features.ipynb b/src/notebooks/web-bubble-plot-with-annotations-and-custom-features.ipynb index 69132a55f5..6efedb0572 100644 --- a/src/notebooks/web-bubble-plot-with-annotations-and-custom-features.ipynb +++ b/src/notebooks/web-bubble-plot-with-annotations-and-custom-features.ipynb @@ -8,7 +8,7 @@ "source": [ "## About\n", "\n", - "This plot is a [bubble plot](https://python-graph-gallery.com/bubble-plot/). It shows the relation between CO2 emission, vulnerability and readiness to climate change. The size of the bubble is the CO2 emission per habitant in the country. \n", + "This plot is a [bubble plot](https://python-graph-gallery.com/bubble-plot/). It shows the relation between CO2 emission, vulnerability and readiness to climate change. The size of the bubble is the CO2 emission per inhabitant in the country. \n", "\n", "The chart was originally made with [React](https://www.react-graph-gallery.com). This post is a translation to Python by [Joseph B.](https://www.barbierjoseph.com). \n", "\n", @@ -25,7 +25,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- `pandas` is used to put the data into a dataframe\n", "\n", @@ -299,7 +299,7 @@ " x_axis = df.loc[df['Name']==country_name, ' ']\n", " y_axis = df.loc[df['Name']==country_name, ' .1']\n", " \n", - " # Add the text at the right position, slighly shift to the top for lisibility\n", + " # Add the text at the right position, slightly shift to the top for lisibility\n", " ax.text(x_axis, y_axis+0.025, # position\n", " country_name, # label\n", " size=6, # size of the text\n", @@ -359,7 +359,7 @@ "\n", "# Add title\n", "title = 'The countries with the highest vulnerability to climate change\\nhave the lowest CO2 emissions'\n", - "fig.text(0, 0.97, # relative postion\n", + "fig.text(0, 0.97, # relative position\n", " title, \n", " fontsize=11, # High font size for style\n", " ha='left', # align to the left\n", @@ -369,7 +369,7 @@ "\n", "# Add subtitle\n", "subtitle = 'All countries sorted by their vulnerability and readiness to climate change. The size shows the CO2 emission\\nper person in that country'\n", - "fig.text(0, 0.92, # relative postion\n", + "fig.text(0, 0.92, # relative position\n", " subtitle, \n", " fontsize=8, # High font size for style\n", " ha='left', # align to the left\n", diff --git a/src/notebooks/web-circular-barplot-with-matplotlib.ipynb b/src/notebooks/web-circular-barplot-with-matplotlib.ipynb index 2a716b95f4..494e48aaa2 100644 --- a/src/notebooks/web-circular-barplot-with-matplotlib.ipynb +++ b/src/notebooks/web-circular-barplot-with-matplotlib.ipynb @@ -491,7 +491,7 @@ "source": [ "## Customize guides and annotations\n", "\n", - "The plot above looks quite nice for a start. But so many reference lines are unnecesary. Let's remove these defaults and improve this chart with custom annotations and guides." + "The plot above looks quite nice for a start. But so many reference lines are unnecessary. Let's remove these defaults and improve this chart with custom annotations and guides." ] }, { @@ -512,7 +512,7 @@ } ], "source": [ - "# Remove unnecesary guides ---------------------------------------\n", + "# Remove unnecessary guides ---------------------------------------\n", "\n", "# Remove lines for polar axis (x)\n", "ax.xaxis.grid(False)\n", @@ -544,7 +544,7 @@ "\n", "# Add text to explain the meaning of the height of the bar and the\n", "# height of the dot\n", - "ax.text(ANGLES[0], 3100, \"Cummulative Length [FT]\", rotation=21, \n", + "ax.text(ANGLES[0], 3100, \"Cumulative Length [FT]\", rotation=21, \n", " ha=\"center\", va=\"center\", size=10, zorder=12)\n", "ax.text(ANGLES[0]+ 0.012, 1300, \"Mean Elevation Gain\\n[FASL]\", rotation=-69, \n", " ha=\"center\", va=\"center\", size=10, zorder=12)\n", @@ -557,7 +557,7 @@ "source": [ "## Final chart\n", "\n", - "The result looks much better! The clutter in the previous plot has dissapeared, that's great! The last step is to add a legend that makes the colors more meaningful and a good title and annotations that can easily transmit what this chart is about." + "The result looks much better! The clutter in the previous plot has disappeared, that's great! The last step is to add a legend that makes the colors more meaningful and a good title and annotations that can easily transmit what this chart is about." ] }, { @@ -624,7 +624,7 @@ "# Define title, subtitle, and caption\n", "title = \"\\nHiking Locations in Washington\"\n", "subtitle = \"\\n\".join([\n", - " \"This Visualisation shows the cummulative length of tracks,\",\n", + " \"This Visualisation shows the cumulative length of tracks,\",\n", " \"the amount of tracks and the mean gain in elevation per location.\\n\",\n", " \"If you are an experienced hiker, you might want to go\",\n", " \"to the North Cascades since there are a lot of tracks,\",\n", diff --git a/src/notebooks/web-dumbell-chart.ipynb b/src/notebooks/web-dumbell-chart.ipynb index a491353323..b9d861e8d6 100644 --- a/src/notebooks/web-dumbell-chart.ipynb +++ b/src/notebooks/web-dumbell-chart.ipynb @@ -711,7 +711,7 @@ "\n", "This article explains how to create a [lollipop chart](/lollipop-plot) in matplotlib.\n", "\n", - "You might also be interested in this [other beautiful dumbell chart](/web-lollipop-plot-with-python-mario-kart-64-world-records) and more generally by how to create [beautiful annotations in matplotlib](/advanced-custom-annotations-matplotlib)" + "You might also be interested in this [other beautiful dumbbell chart](/web-lollipop-plot-with-python-mario-kart-64-world-records) and more generally by how to create [beautiful annotations in matplotlib](/advanced-custom-annotations-matplotlib)" ] } ], @@ -724,7 +724,7 @@ "language": "python", "name": "python3" }, - "keywords": "lollipop, chart, plot, matplotlib, python, dumbell", + "keywords": "lollipop, chart, plot, matplotlib, python, dumbbell", "language_info": { "codemirror_mode": { "name": "ipython", @@ -737,9 +737,9 @@ "pygments_lexer": "ipython3", "version": "3.10.5" }, - "seoDescription": "How to create dumbelle, or lollipop, chart in Python with matplotlib. A dumbell chart is a variation of a barplot, where the bars are replaced by dots and lines.", + "seoDescription": "How to create dumbelle, or lollipop, chart in Python with matplotlib. A dumbbell chart is a variation of a barplot, where the bars are replaced by dots and lines.", "slug": "web-dumbell-chart", - "title": "Dumbell chart with custom annotations" + "title": "Dumbbell chart with custom annotations" }, "nbformat": 4, "nbformat_minor": 4 diff --git a/src/notebooks/web-ggbetweenstats-with-matplotlib.ipynb b/src/notebooks/web-ggbetweenstats-with-matplotlib.ipynb index 48778f297b..796456749b 100644 --- a/src/notebooks/web-ggbetweenstats-with-matplotlib.ipynb +++ b/src/notebooks/web-ggbetweenstats-with-matplotlib.ipynb @@ -301,7 +301,7 @@ "# estimator is computed via Silverman's rule of thumb. \n", "# More on this in the bonus track ;)\n", "\n", - "# The output is stored in 'violins', used to customize their appearence\n", + "# The output is stored in 'violins', used to customize their appearance\n", "violins = ax.violinplot(\n", " y_data, \n", " positions=POSITIONS,\n", @@ -393,7 +393,7 @@ " # Add dot representing the mean\n", " ax.scatter(i, mean, s=250, color=RED_DARK, zorder=3)\n", " \n", - " # Add line conecting mean value and its label\n", + " # Add line connecting mean value and its label\n", " ax.plot([i, i + 0.25], [mean, mean], ls=\"dashdot\", color=\"black\", zorder=3)\n", " \n", " # Add mean value label.\n", diff --git a/src/notebooks/web-heatmap-and-radial-barchart-plastics.ipynb b/src/notebooks/web-heatmap-and-radial-barchart-plastics.ipynb index cb8cc1b82c..04fbeca72b 100644 --- a/src/notebooks/web-heatmap-and-radial-barchart-plastics.ipynb +++ b/src/notebooks/web-heatmap-and-radial-barchart-plastics.ipynb @@ -1127,7 +1127,7 @@ ], "metadata": { "chartType": "radar", - "description": "This post shows how to create a vizualisation that is made of a heatmap and several radial barcharts arranged in a highly customized multi panel layout in Python and Matplotlib. This blogpost walks you through all the involved steps, from the data preparation to the final layout customizations.", + "description": "This post shows how to create a visualisation that is made of a heatmap and several radial barcharts arranged in a highly customized multi panel layout in Python and Matplotlib. This blogpost walks you through all the involved steps, from the data preparation to the final layout customizations.", "family": "ranking", "interpreter": { "hash": "3686ee99cf97e54b2221cc01a9163c2ecb8b74c86b397fcd00b705cd13cfc515" diff --git a/src/notebooks/web-heatmap-comparison.ipynb b/src/notebooks/web-heatmap-comparison.ipynb index 756715786c..cc11494352 100644 --- a/src/notebooks/web-heatmap-comparison.ipynb +++ b/src/notebooks/web-heatmap-comparison.ipynb @@ -236,7 +236,7 @@ "\n", "Now let's add a **legend** to the heatmaps so that it's more understandable.\n", "\n", - "We add both `Consommation d'Γ©nergie` and `Consommation d'Γ©nergie par habitant` to the legend using the `text()` function." + "We add both `Consommation d'Γ©nergie` and `Consommation d'Γ©nergie par inhabitant` to the legend using the `text()` function." ] }, { @@ -280,7 +280,7 @@ " if i==0: # first heatmap\n", " text = \"Consommation d'Γ©nergie\"\n", " else: # second heatmap\n", - " text = \"Consommation d'Γ©nergie par habitant\"\n", + " text = \"Consommation d'Γ©nergie par inhabitant\"\n", " ax_text(\n", " 0, 12.4,\n", " f\"<{text}>\",\n", @@ -383,7 +383,7 @@ " if i==0: # first heatmap\n", " text = \"Consommation d'Γ©nergie\"\n", " else: # second heatmap\n", - " text = \"Consommation d'Γ©nergie par habitant\"\n", + " text = \"Consommation d'Γ©nergie par inhabitant\"\n", " ax_text(\n", " 0, 12.4,\n", " f\"<{text}>\",\n", @@ -435,7 +435,7 @@ ")\n", "\n", "# subtitle\n", - "text = \"Consommation d'Γ©nergie et consommation d'Γ©nergie par habitant, de 2011 Γ  2021, par rΓ©gion (or Corse et territoires d'outre-mer)\"\n", + "text = \"Consommation d'Γ©nergie et consommation d'Γ©nergie par inhabitant, de 2011 Γ  2021, par rΓ©gion (or Corse et territories d'outre-mer)\"\n", "ax_text(\n", " 0, -3.5,\n", " text,\n", @@ -449,7 +449,7 @@ "text = \"\"\"\n", ": Joseph Barbier : data.gouv.fr\n", "Consommation de gaz et d'Γ©lectricitΓ© en France, mesurΓ© en MWh. Les donnΓ©es sont agrΓ©gΓ©es par rΓ©gion et par annΓ©e.\n", - "La population moyenne de 2008 et 2024 est utilisΓ©e pour normaliser la consommation d'Γ©nergie par habitant.\n", + "La population moyenne de 2008 et 2024 est utilisΓ©e pour normaliser la consommation d'Γ©nergie par inhabitant.\n", "AmΓ©liorer ce graphique: \n", "\"\"\"\n", "ax_text(\n", @@ -482,7 +482,7 @@ ")\n", "\n", "# right explanation\n", - "text = \"Relativement Γ  son nombre d'habitants,\\n est une rΓ©gion avec\\n\\n\"\n", + "text = \"Relativement Γ  son nombre d'habitants,\\n est une rΓ©gion avec\\n\\n\"\n", "ax_text(\n", " 12, -1.7,\n", " text,\n", diff --git a/src/notebooks/web-highlighted-lineplot-with-faceting.ipynb b/src/notebooks/web-highlighted-lineplot-with-faceting.ipynb index 00faf517c9..50ff705dc9 100644 --- a/src/notebooks/web-highlighted-lineplot-with-faceting.ipynb +++ b/src/notebooks/web-highlighted-lineplot-with-faceting.ipynb @@ -633,7 +633,7 @@ "source": [ "## Add title and caption\n", "\n", - "The final step is to add the appropiate title and caption. We start by creating some room for these annotations with the `fig.subplots_adjust()` method. This is also where width of the padding between subplots is adjusted. In the end, this chunk also sets the background color.\n" + "The final step is to add the appropriate title and caption. We start by creating some room for these annotations with the `fig.subplots_adjust()` method. This is also where width of the padding between subplots is adjusted. In the end, this chunk also sets the background color.\n" ] }, { @@ -715,7 +715,7 @@ "\n", "If we really want to reproduce the original chart, we cannot miss the Twitter logo next to Abdoul's Twitter handle. This logo, together with many other logos, can be obtained from the **Font Awesome Brands** fonts that you can download from [here](https://fontawesome.com/v5.15/how-to-use/on-the-desktop/setup/getting-started). Remember you can use [this](https://python-graph-gallery.com/custom-fonts-in-matplotlib) step-by-step guide to install and check the installation of this font.\n", "\n", - "Next, you can use [this cheatsheet](https://fontawesome.com/v5/cheatsheet/free/brands) to look for the unicode identifier of the Twitter logo, which is **f099**. Do you see how many logos there are? It's great we can now include any of them in our vizualisations!\n", + "Next, you can use [this cheatsheet](https://fontawesome.com/v5/cheatsheet/free/brands) to look for the unicode identifier of the Twitter logo, which is **f099**. Do you see how many logos there are? It's great we can now include any of them in our visualisations!\n", "\n", "On the other hand, unfortunately, it's not that easy to mix different font families in Matplotlib as it is in R with the `ggtext` package. But that doesn't mean it's impossible to make it look like we've done so. With a little of trial and error we can tweak the `x` coordinate and place the logo where it looks better.\n" ] diff --git a/src/notebooks/web-histogram-with-annotations.ipynb b/src/notebooks/web-histogram-with-annotations.ipynb index cc50bada89..9092454932 100644 --- a/src/notebooks/web-histogram-with-annotations.ipynb +++ b/src/notebooks/web-histogram-with-annotations.ipynb @@ -139,8 +139,8 @@ " )\n", "\n", "# Title of our graph \n", - "title = 'La pyramide des salaires'\n", - "fig.text(-0.08, 1.01, # relative postion\n", + "title = 'La pyramid des salaires'\n", + "fig.text(-0.08, 1.01, # relative position\n", " title, \n", " fontsize=25, # High font size for style\n", " fontweight = 'bold',\n", @@ -150,7 +150,7 @@ "\n", "# Subtitle of our graph\n", "subtitle = 'Distribution des salaires mensuels nets en France,\\nen Γ©quivalent temps plein (et pourcentage) en 2021*'\n", - "fig.text(-0.08, 0.94, # relative postion\n", + "fig.text(-0.08, 0.94, # relative position\n", " subtitle, \n", " fontsize=13, # High font size for style\n", " color='dimgrey',\n", @@ -160,7 +160,7 @@ "\n", "# Details and Credit\n", "text = '*France hors Mayotte, salariΓ©s du privΓ© et des entreprises publiques\\nSource Insee'\n", - "fig.text(-0.08, 0.05, # relative postion\n", + "fig.text(-0.08, 0.05, # relative position\n", " text, \n", " fontsize=10, # High font size for style\n", " color='dimgrey',\n", diff --git a/src/notebooks/web-line-chart-small-multiple.ipynb b/src/notebooks/web-line-chart-small-multiple.ipynb index 8e2676e39c..8930472a9b 100644 --- a/src/notebooks/web-line-chart-small-multiple.ipynb +++ b/src/notebooks/web-line-chart-small-multiple.ipynb @@ -31,7 +31,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- `pandas` is used to put the data into a dataframe\n", "- `datetime` is used for dealing with the date format of our time variable\n", diff --git a/src/notebooks/web-lineplots-and-area-chart-the-economist.ipynb b/src/notebooks/web-lineplots-and-area-chart-the-economist.ipynb index 51ab146dcf..c461f1ba77 100644 --- a/src/notebooks/web-lineplots-and-area-chart-the-economist.ipynb +++ b/src/notebooks/web-lineplots-and-area-chart-the-economist.ipynb @@ -50,7 +50,7 @@ "id": "a9e77630", "metadata": {}, "source": [ - "Let's define colors that are going to be used througout this blogpost:" + "Let's define colors that are going to be used throughout this blogpost:" ] }, { @@ -757,7 +757,7 @@ "source": [ "## Add stacked area chart\n", "\n", - "Similarily than with the linechart, this adds the stacked area chart to the layout." + "Similarly than with the linechart, this adds the stacked area chart to the layout." ] }, { @@ -930,7 +930,7 @@ ], "metadata": { "chartType": "line", - "description": "A custom vizualisation that combines a lineplot with a stacked area chart to explore the evolution of child labour made with Python and Matplotlib. This blogpost guides you through a step-by-step construction of every aspect of the plot, including a variety of custom color annotations, labels, and more!", + "description": "A custom visualisation that combines a lineplot with a stacked area chart to explore the evolution of child labour made with Python and Matplotlib. This blogpost guides you through a step-by-step construction of every aspect of the plot, including a variety of custom color annotations, labels, and more!", "family": "evolution", "kernelspec": { "display_name": "plots", diff --git a/src/notebooks/web-lollipop-with-background-image.ipynb b/src/notebooks/web-lollipop-with-background-image.ipynb index fdb45a78c0..841a44903c 100644 --- a/src/notebooks/web-lollipop-with-background-image.ipynb +++ b/src/notebooks/web-lollipop-with-background-image.ipynb @@ -853,7 +853,7 @@ "\n", "You might also be interested in\n", "\n", - "- this [great dumbell chart](/web-dumbell-chart), which is a variation of the lollipop plot\n", + "- this [great dumbbell chart](/web-dumbbell-chart), which is a variation of the lollipop plot\n", "- this [other really cool lollipop plot](/web-lollipop-plot-with-python-mario-kart-64-world-records) about Mario Kart 64 world records\n" ] } @@ -867,7 +867,7 @@ "language": "python", "name": "python3" }, - "keywords": "lollipop, dumbell, seaborn, python, annotation, image, background, plot, chart", + "keywords": "lollipop, dumbbell, seaborn, python, annotation, image, background, plot, chart", "language_info": { "codemirror_mode": { "name": "ipython", diff --git a/src/notebooks/web-lollipop-with-colormap-and-arrow.ipynb b/src/notebooks/web-lollipop-with-colormap-and-arrow.ipynb index 89f60361cf..214aaa1062 100644 --- a/src/notebooks/web-lollipop-with-colormap-and-arrow.ipynb +++ b/src/notebooks/web-lollipop-with-colormap-and-arrow.ipynb @@ -25,7 +25,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [matplotlib](/matplotlib) is used for creating the chart and add customization features\n", "- [pandas](/pandas) for loading the dataset\n", @@ -389,7 +389,7 @@ "\n", "You might be interested in:\n", "\n", - "- how to create a [dumbell chart](/web-lollipop-plot-with-python-mario-kart-64-world-records)\n", + "- how to create a [dumbbell chart](/web-lollipop-plot-with-python-mario-kart-64-world-records)\n", "- how to use a [lollipop for a time series](/web-lollipop-plot-with-python-the-office)\n", "- this tuto about [circular lollipop](/web-circular-lollipop-plot-with-matplotlib)\n" ] diff --git a/src/notebooks/web-map-europe-with-color-by-country.ipynb b/src/notebooks/web-map-europe-with-color-by-country.ipynb index 0e625354a3..9aadad437a 100644 --- a/src/notebooks/web-map-europe-with-color-by-country.ipynb +++ b/src/notebooks/web-map-europe-with-color-by-country.ipynb @@ -25,7 +25,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- [pandas](https://python-graph-gallery.com/pandas/) and `geopandas` are used to put the data into a dataframe and manipulate geographical data\n", @@ -132,7 +132,7 @@ "\n", "Thanks to the `geopandas` library, we can easily add a **background map** to our plot. We just need to call the `plot()` function on our `geo dataframe`.\n", "\n", - "With just a few lines of code, we can create a **syntetic map** that shows a European map.\n" + "With just a few lines of code, we can create a **synthetic map** that shows a European map.\n" ] }, { @@ -406,7 +406,7 @@ " {\"fontweight\": 'bold'}],\n", " ax=ax)\n", "\n", - "# bloc of text on the right\n", + "# block of text on the right\n", "fig.text(0.72, 0.51, 'Even geographical neighbors\\ncan have very different rates',\n", " fontsize=10,\n", " fontweight='ultralight',\n", @@ -422,7 +422,7 @@ " **kw)\n", "plt.gca().add_patch(a)\n", "\n", - "# bloc of text on the bottom\n", + "# block of text on the bottom\n", "fig.text(0.35, 0.14, 'Southern countries seem\\nto have lower rates than\\nnorthern ones',\n", " fontsize=10,\n", " fontweight='ultralight',\n", diff --git a/src/notebooks/web-map-usa-with-scatter-plot-on-top.ipynb b/src/notebooks/web-map-usa-with-scatter-plot-on-top.ipynb index 02c3c10e84..84bae8bb5d 100644 --- a/src/notebooks/web-map-usa-with-scatter-plot-on-top.ipynb +++ b/src/notebooks/web-map-usa-with-scatter-plot-on-top.ipynb @@ -25,7 +25,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- [pandas](https://python-graph-gallery.com/pandas/) and `geopandas` are used to put the data into a dataframe and manipulate geographical data\n", @@ -285,7 +285,7 @@ "\n", "Thanks to the `geopandas` library, we can easily add a **background map** to our plot. We just need to call the `plot()` function on our `geo dataframe`.\n", "\n", - "With just a few lines of code, we can create a **syntetic map** that shows a US map.\n" + "With just a few lines of code, we can create a **synthetic map** that shows a US map.\n" ] }, { @@ -415,7 +415,7 @@ "\n", "Colors is part of the most important part of a plot. Here we define lots of colors to make the plot more **readable** and **beautiful**.\n", "\n", - "Concretly, here is what we change:\n", + "Concretely, here is what we change:\n", "\n", "- **edgecolor** of the map and individual data points\n", "- **background color** of the plot\n", diff --git a/src/notebooks/web-map-with-custom-legend.ipynb b/src/notebooks/web-map-with-custom-legend.ipynb index d17211f031..4272f6426e 100644 --- a/src/notebooks/web-map-with-custom-legend.ipynb +++ b/src/notebooks/web-map-with-custom-legend.ipynb @@ -25,7 +25,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [matplotlib](/matplotlib) is used for creating the chart and add customization features\n", "- [pandas](/pandas) and `geopandas` are used to put the data into a dataframe and manipulate geographical data\n", diff --git a/src/notebooks/web-multiple-lines-and-panels.ipynb b/src/notebooks/web-multiple-lines-and-panels.ipynb index e2cf779a9d..acc0d8397b 100644 --- a/src/notebooks/web-multiple-lines-and-panels.ipynb +++ b/src/notebooks/web-multiple-lines-and-panels.ipynb @@ -311,7 +311,7 @@ "# Add title\n", "# Note this does not use the `.set_title()` method, but just a normal `.text()`\n", "# This is to gain more control of the position.\n", - "# `transform=ax.transAxes` means the coordintes are in terms of the Axis and not the data\n", + "# `transform=ax.transAxes` means the coordinates are in terms of the Axis and not the data\n", "ax.text(0, 1.025, \"Program 1\", weight=\"bold\", size=18, transform=ax.transAxes)\n", "\n", "fig" diff --git a/src/notebooks/web-multiple-maps.ipynb b/src/notebooks/web-multiple-maps.ipynb index 838f99f9cb..c4474b2d73 100644 --- a/src/notebooks/web-multiple-maps.ipynb +++ b/src/notebooks/web-multiple-maps.ipynb @@ -323,9 +323,9 @@ "source": [ "## Custom colors\n", "\n", - "For this chart, we define a `colors` dictionnary that contains column names as keys, and a **list of 2 colors** as values. We do so in order to then create colormaps (or cmap) based on those colors, thanks to the `create_gradient_colormap()` function, defined below.\n", + "For this chart, we define a `colors` dictionary that contains column names as keys, and a **list of 2 colors** as values. We do so in order to then create colormaps (or cmap) based on those colors, thanks to the `create_gradient_colormap()` function, defined below.\n", "\n", - "We also use the `set_facecolor()` to **change background color** of the figure and the lollipop axe. The first axe **does not need** it since it will be completly removed in the next step and will **have the figure color** as well.\n" + "We also use the `set_facecolor()` to **change background color** of the figure and the lollipop axe. The first axe **does not need** it since it will be completely removed in the next step and will **have the figure color** as well.\n" ] }, { @@ -958,7 +958,7 @@ "\n", "You might be interested in\n", "\n", - "- reproducing a [beautiful dumbell/lollipop chart](/web-dumbell-chart)\n", + "- reproducing a [beautiful dumbbell/lollipop chart](/web-dumbbell-chart)\n", "- how to create a fully customized [choropleth map](/web-map-europe-with-color-by-country).\n" ] } diff --git a/src/notebooks/web-ordered-mirror-barplot.ipynb b/src/notebooks/web-ordered-mirror-barplot.ipynb index 5e5688c998..158390e4ab 100644 --- a/src/notebooks/web-ordered-mirror-barplot.ipynb +++ b/src/notebooks/web-ordered-mirror-barplot.ipynb @@ -27,7 +27,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- `pandas` is used to put the data into a dataframe and data manipulation\n", "- `numpy` is used for adding noise to the positions of each marker\n", diff --git a/src/notebooks/web-population-pyramid.ipynb b/src/notebooks/web-population-pyramid.ipynb index a26829ae82..72e7c976ed 100644 --- a/src/notebooks/web-population-pyramid.ipynb +++ b/src/notebooks/web-population-pyramid.ipynb @@ -31,7 +31,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and for customization\n", "- `pandas` is used to put the data into a dataframe\n", "- `seaborn` will be used for its `barplot()` function." diff --git a/src/notebooks/web-radar-chart-with-matplotlib.ipynb b/src/notebooks/web-radar-chart-with-matplotlib.ipynb index 9c1783aed3..911c755409 100644 --- a/src/notebooks/web-radar-chart-with-matplotlib.ipynb +++ b/src/notebooks/web-radar-chart-with-matplotlib.ipynb @@ -412,7 +412,7 @@ "source": [ "## Customize guides and annotations\n", "\n", - "The plot above looks quite nice for a start. But so many lines and labels for the axes are unnecesary (and also boring!). Let's remove these defaults and improve this chart with more beautiful custom annotations and guides." + "The plot above looks quite nice for a start. But so many lines and labels for the axes are unnecessary (and also boring!). Let's remove these defaults and improve this chart with more beautiful custom annotations and guides." ] }, { diff --git a/src/notebooks/web-scatter-with-customized-annotations.ipynb b/src/notebooks/web-scatter-with-customized-annotations.ipynb index 412d327017..f2b472d49f 100644 --- a/src/notebooks/web-scatter-with-customized-annotations.ipynb +++ b/src/notebooks/web-scatter-with-customized-annotations.ipynb @@ -23,7 +23,7 @@ "source": [ "## Libraries\n", "\n", - "First, we need to install the following librairies:\n" + "First, we need to install the following libraries:\n" ] }, { @@ -197,7 +197,7 @@ "source": [ "## Basic scatter plot\n", "\n", - "The core of the chart is simply based on the `scatter()` funtion from [matplotlib](/matplotlib). You can learn more about it in the [dedicated section](/scatter-plot) of the gallery.\n" + "The core of the chart is simply based on the `scatter()` function from [matplotlib](/matplotlib). You can learn more about it in the [dedicated section](/scatter-plot) of the gallery.\n" ] }, { diff --git a/src/notebooks/web-scatterplot-text-annotation-and-regression-matplotlib.ipynb b/src/notebooks/web-scatterplot-text-annotation-and-regression-matplotlib.ipynb index 2d092c0a36..6b4125b9d9 100644 --- a/src/notebooks/web-scatterplot-text-annotation-and-regression-matplotlib.ipynb +++ b/src/notebooks/web-scatterplot-text-annotation-and-regression-matplotlib.ipynb @@ -60,7 +60,7 @@ "Today's chart uses the [`corruption`](https://wilkelab.org/practicalgg/reference/corruption.html) dataset in the practicalgg package. This data contains information about Corruption Perceptions Index (CPI) and Human Development Index (HDI) for 176 countries, from 2012 to 2015. \n", "\n", "The original source are the [Corruption Perceptions Index 2016](https://www.transparency.org/en/news/corruption-perceptions-index-2016#table) released by [Transparency International](https://transparency.org) and the [Human Development Index](http://hdr.undp.org/en/data#) made available in the \n", - "[Human Development Reports](http://hdr.undp.org/en/) by the [United Nations Development Programme](https://www.undp.org/). These datasets were merged and made available by [Claus O. Wilke](https://clauswilke.com/) as the `corruption` dataset in his `practicalgg` package. Thanks to Claus for all the work and making this possible!" + "[Human Development Reports](http://hdr.undp.org/en/) by the [United Nations Development Programme](https://www.undp.org/). These datasets were merged and made available by [Clause O. Wilke](https://clauswilke.com/) as the `corruption` dataset in his `practicalgg` package. Thanks to Clause for all the work and making this possible!" ] }, { diff --git a/src/notebooks/web-scatterplot-with-images-in-circles.ipynb b/src/notebooks/web-scatterplot-with-images-in-circles.ipynb index 26be77e9d1..6b4eb5ed1f 100644 --- a/src/notebooks/web-scatterplot-with-images-in-circles.ipynb +++ b/src/notebooks/web-scatterplot-with-images-in-circles.ipynb @@ -104,7 +104,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Now we can use this function to store the images in a dictionnary where the **keys are the names** and the **values are the images**." + "Now we can use this function to store the images in a dictionary where the **keys are the names** and the **values are the images**." ] }, { @@ -142,7 +142,7 @@ "\n", "The first we're gonna do is to **create the chart and add the figures**. Since the background of the initial chart is black, we put the `fig` and `ax` to black with the `set_facecolor()` function.\n", "\n", - "Then we **iterate over each image** of our dictionnary and add them to the plot using the `add_axes()` and `imshow()` functions from [matplotlib](https://python-graph-gallery.com/matplotlib/). \n", + "Then we **iterate over each image** of our dictionary and add them to the plot using the `add_axes()` and `imshow()` functions from [matplotlib](https://python-graph-gallery.com/matplotlib/). \n", "\n", "During the iteration, we also get the **name of the actor** in a rectangle. I'm using the `annotate()` function to add the **name along with a bounding box**. The `bbox_props` dictionary defines the **style of the bounding box**. This approach should help ensure that the rectangles appear around each name correctly." ] diff --git a/src/notebooks/web-slope-chart-matplotlib.ipynb b/src/notebooks/web-slope-chart-matplotlib.ipynb index 50538cc840..ef955a6abf 100644 --- a/src/notebooks/web-slope-chart-matplotlib.ipynb +++ b/src/notebooks/web-slope-chart-matplotlib.ipynb @@ -27,7 +27,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the slope chart and for customization\n", "- [seaborn](https://python-graph-gallery.com/seaborn/) is used for creating the parallel plot\n", "- `pandas` is used for loading the dataset" diff --git a/src/notebooks/web-small-multiple-with-highlights.ipynb b/src/notebooks/web-small-multiple-with-highlights.ipynb index ae73a10cbb..bc51164c76 100644 --- a/src/notebooks/web-small-multiple-with-highlights.ipynb +++ b/src/notebooks/web-small-multiple-with-highlights.ipynb @@ -458,7 +458,7 @@ "id": "434513af", "metadata": {}, "source": [ - "## Highligh first and last value\n", + "## Highlight first and last value\n", "\n", "For each subplot, we will highlight the **first and last value** of the line. This is done by adding a **dot** at the first and last value of the line. We also add a **text annotation** next to the dot to make it more explicit.\n" ] @@ -1267,7 +1267,7 @@ "source": [ "## Going further\n", "\n", - "You migth be interested in:\n", + "You might be interested in:\n", "\n", "- this beautiful small [multiple connected scatter plot](/web-highlighted-lineplot-with-faceting)\n", "- this [small multiple line chart](/web-line-chart-small-multiple) with reference lines\n" diff --git a/src/notebooks/web-stacked-area-charts-on-a-map.ipynb b/src/notebooks/web-stacked-area-charts-on-a-map.ipynb index cbcf20e3ca..1388c77fab 100644 --- a/src/notebooks/web-stacked-area-charts-on-a-map.ipynb +++ b/src/notebooks/web-stacked-area-charts-on-a-map.ipynb @@ -19,7 +19,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- `pandas` is used to put the data into a dataframe and data manipulation\n", "\n", @@ -328,7 +328,7 @@ "- the first argument specifies that the text must be at **30% to the right** and the second at **90% upwards**\n", "- we **center the text** using the `ha` and `va` arguments\n", "- we change the **text size** using the `fontsize` argument\n", - "- we use a dictionnary of properties `font_params` for the title that defines the **font and other properties** to use\n", + "- we use a dictionary of properties `font_params` for the title that defines the **font and other properties** to use\n", "\n", "To change the size of the 'AK' graph, we perform a **special case** in our loop at position (0,6) to apply the `set_position()` function. It specifies the **new position and dimensions** of the graph in question.\n", "\n", diff --git a/src/notebooks/web-stacked-line-chart-with-labels.ipynb b/src/notebooks/web-stacked-line-chart-with-labels.ipynb index 76ebc66f28..b90b903e0c 100644 --- a/src/notebooks/web-stacked-line-chart-with-labels.ipynb +++ b/src/notebooks/web-stacked-line-chart-with-labels.ipynb @@ -33,7 +33,7 @@ "source": [ "## Libraries\n", "\n", - "For this tutorial, you'll need to install the following librairies:\n", + "For this tutorial, you'll need to install the following libraries:\n", "\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is the main library used for both graphics and customization.\n", "- `pandas` will be used to open and manipulate our dataset\n", @@ -262,7 +262,7 @@ "tags": [] }, "source": [ - "## Add anotation\n", + "## Add annotation\n", "\n", "This step can take some time, as many of the texts and annotations are added manually. We're mainly using `plt.text()` function from [matplotlib](https://python-graph-gallery.com/matplotlib/), which makes it **super-easy to add text** to a graph.\n", "\n", diff --git a/src/notebooks/web-streamchart-with-matplotlib.ipynb b/src/notebooks/web-streamchart-with-matplotlib.ipynb index 6116e76894..57318accfc 100644 --- a/src/notebooks/web-streamchart-with-matplotlib.ipynb +++ b/src/notebooks/web-streamchart-with-matplotlib.ipynb @@ -91,7 +91,7 @@ "source": [ "## Load the dataset\n", "\n", - "This guide shows how to create a highly customized and beautiful streamchart to visualize the number of appearences of the most popular characters in Chris Claremont's sixteen-year run on Uncanny X-Men. \n", + "This guide shows how to create a highly customized and beautiful streamchart to visualize the number of appearances of the most popular characters in Chris Claremont's sixteen-year run on Uncanny X-Men. \n", "\n", "The original source of data for this week are the [Claremont Run Project](http://www.claremontrun.com/) and [Malcom Barret](https://twitter.com/malco_barrett) who put these datasets into a the R package [cleremontrun](https://github.com/malcolmbarrett/claremontrun). This guide uses the `character_visualization` dataset released for the [TidyTuesday](https://github.com/rfordatascience/tidytuesday) initiative on the week of 2021-06-30. You can find the original announcement and more information about the data [here](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-06-30/readme.md). Thank you all for making this possible! " ] @@ -150,7 +150,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Next, `df_char_vis` and `df_best_chars` are merged into `df_best_stream`. It also contains, for each issue, the number of appearences by character, costume, and type." + "Next, `df_char_vis` and `df_best_chars` are merged into `df_best_stream`. It also contains, for each issue, the number of appearances by character, costume, and type." ] }, { @@ -404,7 +404,7 @@ "\n", "For each combination of character and costume, there are a sequence of issues and the number of appearences for each issue. This first chart shows the `\"depicted\"` appearences only. The number of appearences are smoothed out using the Gaussian smoother defined as `gaussian_smooth()`. In few words, the number of appearences for a given issue is replaced with a weighted average of the number of appearences with the weights computed according to the Gaussian filter. For more information see [here](https://en.wikipedia.org/wiki/Kernel_smoother#Kernel_average_smoother).\n", "\n", - "Next, the data has to be put in the shape required by `ax.stackplot()`. The first argument, `x`, can be a one dimensional array. In this case, it is going to be the `grid` used to compute the weighted values. Then, `y` is going to be a list. Each element of the `values_smoothed` list is an array with the weigthed values, for each level in `\"char_costume\"`." + "Next, the data has to be put in the shape required by `ax.stackplot()`. The first argument, `x`, can be a one dimensional array. In this case, it is going to be the `grid` used to compute the weighted values. Then, `y` is going to be a list. Each element of the `values_smoothed` list is an array with the weighted values, for each level in `\"char_costume\"`." ] }, { @@ -659,7 +659,7 @@ ], "source": [ "# Add labels for each panel axis ---------------------------------\n", - "# These labels indicate which type of appearence is represented\n", + "# These labels indicate which type of appearance is represented\n", "# on each panel.\n", "\n", "levels = [\"depicted\", \"speech\", \"thought\", \"narrative\"]\n", @@ -847,7 +847,7 @@ " edgecolor=GREY40,\n", " labelspacing=-0.1,\n", " loc=\"center\", \n", - " ncol=5 # The 10 handles are splitted between 5 columns\n", + " ncol=5 # The 10 handles are split between 5 columns\n", ")\n", "\n", "# Change size and color of legend labels\n", @@ -855,7 +855,7 @@ " text.set_fontsize(8) \n", " text.set_color(GREY40)\n", "\n", - "# And finally give a rounded appearence to the frame of the legend\n", + "# And finally give a rounded appearance to the frame of the legend\n", "legend.get_frame().set_boxstyle(\"round\", rounding_size=0.4, pad=0.1) \n", "\n", "\n", @@ -893,7 +893,7 @@ "fig.text(\n", " 0.5, \n", " 0.02, \n", - " \"Visualization by CΓ©dric Scherer β€’ Data by Claremont Run Project via Malcom Barret β€’ Popularity Scores by ranker.com β€’ Logo by Comicraft\",\n", + " \"Visualization by CΓ©dric Scherer β€’ Data by Claremont Run Project via Malcolm Barret β€’ Popularity Scores by ranker.com β€’ Logo by Comicraft\",\n", " color=GREY40,\n", " fontsize=8,\n", " ha=\"center\"\n", diff --git a/src/notebooks/web-text-repel-with-matplotlib.ipynb b/src/notebooks/web-text-repel-with-matplotlib.ipynb index 0f8c755f4e..e4ac2dfb35 100644 --- a/src/notebooks/web-text-repel-with-matplotlib.ipynb +++ b/src/notebooks/web-text-repel-with-matplotlib.ipynb @@ -199,7 +199,7 @@ "id": "a28159b3", "metadata": {}, "source": [ - "Today's vizualisation does not require much data preparation. The only preparation step is to drop observations with missing values." + "Today's visualisation does not require much data preparation. The only preparation step is to drop observations with missing values." ] }, { @@ -326,7 +326,7 @@ "source": [ "## Add labels with no overlap\n", "\n", - "What's truely missing here are __labels__. It's very frustrating not knowing which item is hidden under a data point, isn't it!?\n", + "What's truly missing here are __labels__. It's very frustrating not knowing which item is hidden under a data point, isn't it!?\n", "\n", "It is pretty challenging to add many labels on a plot since labels tend to overlap each other, making the figure unreadable. Fortunately, the `adjustText` package is here to help us. It provides an algorithm that will automatically place the labels for us. Let's do it!" ] @@ -478,7 +478,7 @@ " text.set_fontname(\"Roboto\") # Change default font \n", " text.set_fontsize(16) # Change default font size\n", "\n", - "# Grab title and customize its appearence.\n", + "# Grab title and customize its appearance.\n", "legend.set_title(\"Species\")\n", "legend_title = legend.get_title()\n", "legend_title.set_fontname(\"Roboto\")\n", diff --git a/src/notebooks/web-time-series-and-facetting-with-matplotlib.ipynb b/src/notebooks/web-time-series-and-facetting-with-matplotlib.ipynb index 81f68ba356..45be6e2f94 100644 --- a/src/notebooks/web-time-series-and-facetting-with-matplotlib.ipynb +++ b/src/notebooks/web-time-series-and-facetting-with-matplotlib.ipynb @@ -870,7 +870,7 @@ } ], "source": [ - "# Itereate trough rows\n", + "# Iterate through rows\n", "for i in range(7):\n", " # Iterate through columns\n", " for j in range(8):\n", diff --git a/src/notebooks/web-tornado-chart.ipynb b/src/notebooks/web-tornado-chart.ipynb index 04f3d69b0b..25732ac512 100644 --- a/src/notebooks/web-tornado-chart.ipynb +++ b/src/notebooks/web-tornado-chart.ipynb @@ -124,7 +124,7 @@ " ----------\n", " labels : np.array()\n", " List of label titles used to identify the variables, y-axis of bar\n", - " chart. The lengh of labels is used to itereate through to generate \n", + " chart. The length of labels is used to iterate through to generate \n", " the bar charts.\n", " midpoint : float\n", " Center value for bar charts to extend from. In sensitivity analysis\n", diff --git a/src/notebooks/web-waffle-chart-as-share.ipynb b/src/notebooks/web-waffle-chart-as-share.ipynb index e43ef5352c..7ddd09dddf 100644 --- a/src/notebooks/web-waffle-chart-as-share.ipynb +++ b/src/notebooks/web-waffle-chart-as-share.ipynb @@ -24,7 +24,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- `pandas` is used to put the data into a dataframe\n", diff --git a/src/notebooks/web-waffle-chart-for-time-series.ipynb b/src/notebooks/web-waffle-chart-for-time-series.ipynb index 6cf932653b..c01e35a5ac 100644 --- a/src/notebooks/web-waffle-chart-for-time-series.ipynb +++ b/src/notebooks/web-waffle-chart-for-time-series.ipynb @@ -24,7 +24,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [matplotlib](/matplotlib) is used for creating the chart and add customization features\n", "- [pandas](/pandas) for data loading and manipulation\n", @@ -505,7 +505,7 @@ ], "metadata": { "chartType": "waffle", - "description": "This post explains how to reproduce a waffle chart that is used in the context of time series. It describe the evolution of number of storms, splitted by storm type throughout time.

It explains step-by-step how to replicate it with reproducible code and explanations", + "description": "This post explains how to reproduce a waffle chart that is used in the context of time series. It describe the evolution of number of storms, split by storm type throughout time.

It explains step-by-step how to replicate it with reproducible code and explanations", "family": "partOfAWhole", "kernelspec": { "display_name": "Python 3 (ipykernel)", diff --git a/src/notebooks/web-waffle-with-small-multiples.ipynb b/src/notebooks/web-waffle-with-small-multiples.ipynb index fa044411ac..ed0d8fa2dc 100644 --- a/src/notebooks/web-waffle-with-small-multiples.ipynb +++ b/src/notebooks/web-waffle-with-small-multiples.ipynb @@ -9,7 +9,7 @@ "source": [ "## About\n", "\n", - "This plot is a [waffle chart](/waffle-chart), with small mutliples. It shows the **recycling rates** per London borough. The size of each square is proportional to the recycling rate. The chart is made with the `pywaffle` library.\n", + "This plot is a [waffle chart](/waffle-chart), with small multiples. It shows the **recycling rates** per London borough. The size of each square is proportional to the recycling rate. The chart is made with the `pywaffle` library.\n", "\n", "The chart was made by [Lisa Hornung](https://inside-numbers.com/). Thanks to her for accepting sharing her work here!\n", "\n", @@ -25,7 +25,7 @@ "source": [ "## Libraries\n", "\n", - "First, you need to install the following librairies:\n", + "First, you need to install the following libraries:\n", "\n", "- [matplotlib](https://python-graph-gallery.com/matplotlib/) is used for creating the chart and add customization features\n", "- [pandas](https://python-graph-gallery.com/pandas/) is used to read the data\n", @@ -183,7 +183,7 @@ "source": [ "layout = [\n", " [\"___\",\"___\",\"___\",\"___\",\"ENF\",\"___\",\"___\",\"___\"],\n", - " [\"___\",\"___\",\"HRW\",\"BRN\",\"HGY\",\"WTH\",\"___\",\"___\"],\n", + " [\"___\",\"___\",\"HRW\",\"BRN\",\"HGY\",\"WITH\",\"___\",\"___\"],\n", " [\"HDN\",\"ELG\",\"BRT\",\"CMD\",\"ISL\",\"HCK\",\"RDB\",\"HVG\"],\n", " [\"HNS\",\"HMS\",\"KNS\",\"WST\",\"CTY\",\"TOW\",\"NWM\",\"BAR\"],\n", " [\"___\",\"RCH\",\"WNS\",\"LAM\",\"SWR\",\"LSH\",\"GRN\",\"BXL\"],\n", diff --git a/src/pages/about.js b/src/pages/about.js index f3861718ee..4fda682e0f 100644 --- a/src/pages/about.js +++ b/src/pages/about.js @@ -76,7 +76,7 @@ export default function About() {

πŸ’΅ Sponsoring

- If you run a buisness that is highly related with python, data science + If you run a business that is highly related with python, data science or a closely related field, I would love to communicate about it in exchange of a few πŸ’°. We all need to put some butter in the spinach (French expression, sorry) 🐸. @@ -245,7 +245,7 @@ export default function About() {

  • Improve an existing page. It can be anything from correcting - an english mistake to a python code reformating. + an english mistake to a python code reformatting.
    • πŸ‘πŸ½ Open an{' '} diff --git a/src/pages/all-charts.js b/src/pages/all-charts.js index 994f66e85d..9d1dec0e96 100644 --- a/src/pages/all-charts.js +++ b/src/pages/all-charts.js @@ -894,7 +894,7 @@ export default function AllCharts() { /> An arc diagram is a special kind of network graph. It is consituted by nodes that represent entities and by links that show relationships between entities. In arc diagrams, nodes are displayed along a single axis and links are represented with arcs."; + "

      An arc diagram is a special kind of network graph. It is constituted by nodes that represent entities and by links that show relationships between entities. In arc diagrams, nodes are displayed along a single axis and links are represented with arcs."; export const Head = () => (

      As often, note that the Seaborn alternative allows to - write less code to build the chart, but is slighlty more limited in + write less code to build the chart, but is slightly more limited in term of customization

      @@ -516,7 +516,7 @@ export default function Barplot() { 'web-horizontal-barplot-with-labels-the-economist-square' } caption={ - 'Lear how to mimick the style of the Economist on this horizontal barplot.' + 'Lear how to mimic the style of the Economist on this horizontal barplot.' } /> diff --git a/src/pages/best-dataviz-packages.js b/src/pages/best-dataviz-packages.js index 1aa7541c47..ed472c8782 100644 --- a/src/pages/best-dataviz-packages.js +++ b/src/pages/best-dataviz-packages.js @@ -43,7 +43,7 @@ import { SEO } from '../components/SEO'; // Geospatial // folium, geoplot, cartopy, basemap, geopandas -// Specfic chart type +// Specific chart type // networkX, wordcloud, suqarify, pywaffle, // Tables diff --git a/src/pages/candlestick.js b/src/pages/candlestick.js index 66216b1da7..c375df8bd8 100644 --- a/src/pages/candlestick.js +++ b/src/pages/candlestick.js @@ -143,7 +143,7 @@ export default function Boxplot() {

      Plotly is a python library made to create{' '} - interactive charts. It is particularly poweful when it comes to + interactive charts. It is particularly powerful when it comes to create interactive candlestick graphs.

      diff --git a/src/pages/cheat-sheets.js b/src/pages/cheat-sheets.js index c225317148..284710eeab 100644 --- a/src/pages/cheat-sheets.js +++ b/src/pages/cheat-sheets.js @@ -49,7 +49,7 @@ export default function CheatSheet() { Datacamp is also a great contributor.

      - Note that if you want to truely understand how matplotlib works, + Note that if you want to truly understand how matplotlib works, Matplotlib Journey {' '} diff --git a/src/pages/circular-packing.js b/src/pages/circular-packing.js index 2e81cffcbf..b6cf7d8c7f 100644 --- a/src/pages/circular-packing.js +++ b/src/pages/circular-packing.js @@ -39,7 +39,7 @@ export default function CircularPacking() {

      The circlify package is a pure Python implementation of - a circle packing layout algorithm. It has been developped by{' '} + a circle packing layout algorithm. It has been developed by{' '} Jerome Lecomte and lives on{' '} github. πŸ™πŸ™{' '}

      @@ -61,7 +61,7 @@ export default function CircularPacking() {

      Circlify can work without a hierarchical structure, i.e. - with just a set of numeric varialbles that will be each displayed as a + with just a set of numeric variables that will be each displayed as a bubble. Note that the package just compute the position and size of each bubble. Once that's done, matplotlib is used to make the chart itself with usual functions. diff --git a/src/pages/connected-scatter-plot.js b/src/pages/connected-scatter-plot.js index e63a938342..3c08e9c66f 100644 --- a/src/pages/connected-scatter-plot.js +++ b/src/pages/connected-scatter-plot.js @@ -56,7 +56,7 @@ export default function ConnectedScatter() {

      Building a connected scatterplot with Python and Matplotlib is a breeze thanks to the plot() function. The 2 first - argumenst are the X and Y values respectively, which can be stored + arguments are the X and Y values respectively, which can be stored in a pandas data frame.

      diff --git a/src/pages/dendrogram.js b/src/pages/dendrogram.js index 2a0ea13254..41401b6ef5 100644 --- a/src/pages/dendrogram.js +++ b/src/pages/dendrogram.js @@ -156,7 +156,7 @@ export default function Dendrogram() { -

      Dendrogram for hierarchical datasets

      +

      Dendrogram for hierarchical datasets

      Dendrogram can also be used to display a hierarchy. A hierarchy as a root node that gets divided in several children and so on. diff --git a/src/pages/density-plot.js b/src/pages/density-plot.js index 6c90c64519..57c93dee98 100644 --- a/src/pages/density-plot.js +++ b/src/pages/density-plot.js @@ -198,7 +198,7 @@ export default function DensityPlot() {

      It is possible to build a density chart with matplotlib, - but it is truely a struggle compared to making it with{' '} + but it is truly a struggle compared to making it with{' '} seaborn as shown above.

      diff --git a/src/pages/heatmap.js b/src/pages/heatmap.js index 872c7b79e0..73bb6aa5b3 100644 --- a/src/pages/heatmap.js +++ b/src/pages/heatmap.js @@ -82,7 +82,7 @@ export default function Heatmap() { section starts with a post describing the basic usage of the function based on any kind of data input. Next it will guide you through the different ways to customize the chart, like{' '} - controling color and{' '} + controlling color and{' '} data normalization.

      diff --git a/src/pages/hierarchical-edge-bundling.js b/src/pages/hierarchical-edge-bundling.js index 9e2de71a99..1519b1b7ad 100644 --- a/src/pages/hierarchical-edge-bundling.js +++ b/src/pages/hierarchical-edge-bundling.js @@ -37,7 +37,7 @@ export default function Arc() {

      As far as I know, there isn't any proper way to build a hierarchical edged bundling plot with python 😞. If you're aware of any tip to - build it, please let me knwo! My contact is provided below πŸ™πŸ½. + build it, please let me know! My contact is provided below πŸ™πŸ½.

      You now have 3 options!

        diff --git a/src/pages/histogram.js b/src/pages/histogram.js index 89e8d0e35e..e91bea7e20 100644 --- a/src/pages/histogram.js +++ b/src/pages/histogram.js @@ -243,7 +243,7 @@ export default function Histogram() {

        As usual matplotlib is perfectly skilled - to build nice histogram, but require some more work camparing to{' '} + to build nice histogram, but require some more work comparing to{' '} seaborn to get a good looking figure.

        diff --git a/src/pages/line-chart.js b/src/pages/line-chart.js index db420bf3f4..541747bbcc 100644 --- a/src/pages/line-chart.js +++ b/src/pages/line-chart.js @@ -26,7 +26,7 @@ const chartDescription = (

        A line chart{' '} displays the evolution of one or several numeric variables. - It is often used to represend time series. + It is often used to represent time series.

        The line chart is one of the most common chart type. As a result, @@ -382,7 +382,7 @@ export default function LinePlot() { diff --git a/src/pages/lollipop-plot.js b/src/pages/lollipop-plot.js index b6d08a001f..41a2a9ecd6 100644 --- a/src/pages/lollipop-plot.js +++ b/src/pages/lollipop-plot.js @@ -183,7 +183,7 @@ export default function Lollipop() { diff --git a/src/pages/matplotlib.js b/src/pages/matplotlib.js index 5452ec96b9..974af21be4 100644 --- a/src/pages/matplotlib.js +++ b/src/pages/matplotlib.js @@ -304,7 +304,7 @@ export default function Matplotlibs() {

        The post #190 goes in depth on how to customize the matplotlib - title. All the main types of change are descried: changing its color, + title. All the main types of change are described: changing its color, adding a subtitle, using math formulas and so on. Give it a go!

        @@ -881,7 +881,7 @@ export default function Matplotlibs() { If you have several colors or marker on your chart, you can't escape the hassle of building a nice legend. The blogpost linked below should help for all the most common use cases like positioning the legend, - adding and customizing a title to it, controling markers and labels + adding and customizing a title to it, controlling markers and labels and more.

        diff --git a/src/pages/plotly.js b/src/pages/plotly.js index b7c5083c92..aed3129857 100644 --- a/src/pages/plotly.js +++ b/src/pages/plotly.js @@ -178,7 +178,7 @@ export default function Plotlys() { -

        Embeding a plotly chart

        +

        Embedding a plotly chart

        Once the chart has been saved, you can embed it in a html document using: diff --git a/src/pages/plotnine.js b/src/pages/plotnine.js index 25bf73db79..22ea209cc1 100644 --- a/src/pages/plotnine.js +++ b/src/pages/plotnine.js @@ -247,7 +247,7 @@ export default function Post() { /> diff --git a/src/pages/python-colors.js b/src/pages/python-colors.js index 83ea1e1f3b..045ff323c4 100644 --- a/src/pages/python-colors.js +++ b/src/pages/python-colors.js @@ -272,7 +272,7 @@ export default function Colors() {

        User-friendly API

        - pypalettes is pretty straightfoward to use. For instance, + pypalettes is pretty straightforward to use. For instance, this is how to use a palette called Acadia once the library is installed:

        diff --git a/src/pages/stacked-area-plot.js b/src/pages/stacked-area-plot.js index 80f324e566..469a6da72f 100644 --- a/src/pages/stacked-area-plot.js +++ b/src/pages/stacked-area-plot.js @@ -121,7 +121,7 @@ export default function StackedAreaPlot() { Matplotlib is the most common way to build a stacked area chart with Python. The examples below start by explaining to basics of the stackplot() function. The also describe the most - common type of customization like changing colors, controling group + common type of customization like changing colors, controlling group order and more.

        @@ -271,7 +271,7 @@ export default function StackedAreaPlot() { diff --git a/src/pages/table.js b/src/pages/table.js index acc7a08de9..cecf155fd9 100644 --- a/src/pages/table.js +++ b/src/pages/table.js @@ -25,7 +25,7 @@ const chartDescription = ( clear, organized manner for quick comparison and interpretation.

        - Several strategies exist to build table wih Python. Tweaking{' '} + Several strategies exist to build table with Python. Tweaking{' '} matplotlib functions is doable but very verbose.{' '} pandas has a couple of utility functions. But{' '} plottable is definitely the best option. It is a powerful diff --git a/src/pages/timeseries.js b/src/pages/timeseries.js index 282cf98efe..0a721b7dcb 100644 --- a/src/pages/timeseries.js +++ b/src/pages/timeseries.js @@ -256,7 +256,7 @@ export default function Pie() { />

        The squarify library is a pure Python implementation of the squarify - treemap layout algorithm. It is a project developped by{' '} + treemap layout algorithm. It is a project developed by{' '} Uri Laserson that has its documentation on{' '} github. diff --git a/src/pages/venn-diagram.js b/src/pages/venn-diagram.js index a890d585c8..23bf8afdbe 100644 --- a/src/pages/venn-diagram.js +++ b/src/pages/venn-diagram.js @@ -114,7 +114,7 @@ export default function Venn() { />

        Matplotlib, as usual, is another great - otion to build violin charts with python. It comes with a{' '} + option to build violin charts with python. It comes with a{' '} violinplot() function that does all the hard work for us.

        Here are a couple of examples:

        diff --git a/src/pages/waffle-chart.js b/src/pages/waffle-chart.js index dfe831e318..35d516c908 100644 --- a/src/pages/waffle-chart.js +++ b/src/pages/waffle-chart.js @@ -125,7 +125,7 @@ export default function Waffle() { /> However, it is important to consider the caveats associated to them. For instance, - longer words will take more space on the figure by + longer words will tache more space on the figure by construction which distorts reality. Moreover, it is impossible to{' '} translate a font size to an accurate value.

        diff --git a/src/util/list-of-best-charts.js b/src/util/list-of-best-charts.js index 05d71343d1..52773eeab8 100644 --- a/src/util/list-of-best-charts.js +++ b/src/util/list-of-best-charts.js @@ -165,7 +165,7 @@ export const listOfBestCharts = [ link: 'web-dumbell-chart', title: 'Dumbell chart', description: - 'Advanced dumbell chart about wins and losses in the Bundesliga.', + 'Advanced dumbbell chart about wins and losses in the Bundesliga.', img: 'web-dumbell-chart.png', alt: 'lollipop plot', author: 'CΓ©dric Scherer', @@ -346,7 +346,7 @@ export const listOfBestCharts = [ description: 'A reproduction of an horizontal barplot made by The Economist to showcase the power of Python for dataviz', img: 'web-horizontal-barplot-with-labels-the-economist-square.png', - alt: "Horizonal barplot with the Economist's style", + alt: "Horizontal barplot with the Economist's style", author: 'The Economist', }, { @@ -425,7 +425,7 @@ export const listOfBestCharts = [ link: 'web-scatterplot-text-annotation-and-regression-matplotlib', title: 'Scatterplot with regression fit', description: - 'A custom scatterplot with an overlayed regression fit and auto-positioned labels to explore the relationship between the Corruption Perceptions Index and Human Development Index', + 'A custom scatterplot with an overlaid regression fit and auto-positioned labels to explore the relationship between the Corruption Perceptions Index and Human Development Index', img: 'web-scatterplot-text-annotation-and-regression-matplotlib-square.png', alt: 'Scatterplot with regression fit', author: 'C. O. Wilke', diff --git a/static/graph/script_reformat_img_color.sh b/static/graph/script_reformat_img_color.sh index 9de4c9f64c..a6f897c02c 100755 --- a/static/graph/script_reformat_img_color.sh +++ b/static/graph/script_reformat_img_color.sh @@ -7,7 +7,7 @@ COLOR=$2 convert Screenshot*.png -resize 480x480 new.png -# Image magick make me stuggle to provide a color. It needs to have a '' around +# Image magick make me struggle to provide a color. It needs to have a '' around # the color name. The only way I found was to build the string and eval it later on myComand="convert -size 480x480 xc:'#"${COLOR}"' new.png -gravity center -composite output.png" eval $myComand diff --git a/static/interactiveCharts/593-customize-bubble-map-with-folium-2.html b/static/interactiveCharts/593-customize-bubble-map-with-folium-2.html index d1dce69b79..8df7ae0610 100644 --- a/static/interactiveCharts/593-customize-bubble-map-with-folium-2.html +++ b/static/interactiveCharts/593-customize-bubble-map-with-folium-2.html @@ -57458,7 +57458,7 @@
        Date: 10/11/2018
        circle_marker_ec0ccd607a902c15a8c2c7288bff3d31.bindTooltip( `
        -
        Location: Nothern Colombia
        +
        Location: Northern Colombia
        Magnitude: 5.5
        Depth: 150 km
        Date: 07/08/2018
        @@ -60327,7 +60327,7 @@
        Date: 17/07/2023
        circle_marker_bd4972581789f5b0f3ff747984c94c88.bindTooltip( `
        -
        Location: Luzon, Phillipines.
        +
        Location: Luzon, Philippines.
        Magnitude: 5.4
        Depth: 147 km
        Date: 06/02/2019
        @@ -74710,7 +74710,7 @@
        Date: 12/03/2018
        circle_marker_2c50281790fd62ab71c40faf5c12f941.bindTooltip( `
        -
        Location: 48 km Noth of Swat
        +
        Location: 48 km North of Swat
        Magnitude: 3.7
        Depth: 125 km
        Date: 13/02/2024
        @@ -83621,7 +83621,7 @@
        Date: 23/03/2019
        circle_marker_fe6485d434e1b775ec411a3c4b6a79e7.bindTooltip( `
        -
        Location: New Britian Region, Papua New Guinea
        +
        Location: New Britain Region, Papua New Guinea
        Magnitude: 5.6
        Depth: 117 km
        Date: 11/06/2024
        @@ -84210,7 +84210,7 @@
        Date: 30/06/2022
        circle_marker_28e33b1f892d6725c6c493384aac3d42.bindTooltip( `
        -
        Location: Alaska Penisula
        +
        Location: Alaska Peninsula
        Magnitude: 5.0
        Depth: 116 km
        Date: 12/11/2016
        @@ -86471,7 +86471,7 @@
        Date: 26/09/2021
        circle_marker_134d4d1018d12ab2bcad25b3cd4015d0.bindTooltip( `
        -
        Location: New Britian Region, P.N.G.
        +
        Location: New Britain Region, P.N.G.
        Magnitude: 5.1
        Depth: 114 km
        Date: 28/11/2018
        @@ -88922,7 +88922,7 @@
        Date: 11/08/2021
        circle_marker_56ec6fcbb0250065dd4f08fa075af32f.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.2
        Depth: 112 km
        Date: 01/10/2018
        @@ -93691,7 +93691,7 @@
        Date: 26/12/2017
        circle_marker_e95b38cfb2b1827937b0fe757ec72830.bindTooltip( `
        -
        Location: New Britian Region, Papua New Guinea
        +
        Location: New Britain Region, Papua New Guinea
        Magnitude: 5.6
        Depth: 108 km
        Date: 11/06/2024
        @@ -95724,7 +95724,7 @@
        Date: 09/09/2017
        circle_marker_fcc6003720d824096c14f0f4a5601e08.bindTooltip( `
        -
        Location: Phillipines Islands Region
        +
        Location: Philippines Islands Region
        Magnitude: 5.3
        Depth: 105 km
        Date: 18/08/2016
        @@ -125136,7 +125136,7 @@
        Date: 21/07/2018
        circle_marker_91e237b44772cfccb339eae78cdd7320.bindTooltip( `
        -
        Location: Hokkaido japan Regon
        +
        Location: Hokkaido japan Region
        Magnitude: 4.3
        Depth: 79 km
        Date: 12/06/2024
        @@ -126314,7 +126314,7 @@
        Date: 10/10/2023
        circle_marker_29b489c91f9a2669d7b2c92bcd0dd888.bindTooltip( `
        -
        Location: Luzon, Phillipines.
        +
        Location: Luzon, Philippines.
        Magnitude: 5.0
        Depth: 77 km
        Date: 12/01/2019
        @@ -126865,7 +126865,7 @@
        Date: 05/02/2019
        circle_marker_6114d9187c56ee79b4e24cd7a18c6cf6.bindTooltip( `
        -
        Location: New Britian Region,P.N.G,
        +
        Location: New Britain Region,P.N.G,
        Magnitude: 5.3
        Depth: 76 km
        Date: 12/10/2018
        @@ -131235,7 +131235,7 @@
        Date: 22/10/2023
        circle_marker_7e8e63f70b573929fef6817f0b1e4fec.bindTooltip( `
        -
        Location: Indian Ocean Tripple Junction.
        +
        Location: Indian Ocean Triple Junction.
        Magnitude: 5.4
        Depth: 70 km
        Date: 28/09/2018
        @@ -131938,7 +131938,7 @@
        Date: 13/11/2023
        circle_marker_7e1130bedfbcb1e316e980b5e76a7889.bindTooltip( `
        -
        Location: Kenia Penisula Alaska
        +
        Location: Kenia Peninsula Alaska
        Magnitude: 5.1
        Depth: 70 km
        Date: 03/07/2019
        @@ -131957,7 +131957,7 @@
        Date: 03/07/2019
        circle_marker_49e2bc5a52e36bcf9c43f5979b859003.bindTooltip( `
        -
        Location: Hindu Kush Region Afganistan
        +
        Location: Hindu Kush Region Afghanistan
        Magnitude: 3.3
        Depth: 70 km
        Date: 25/10/2016
        @@ -139633,7 +139633,7 @@
        Date: 10/03/2017
        circle_marker_455a3e60c350e538cfdb81f4054d6fef.bindTooltip( `
        -
        Location: New Britian Region, P.N.G.
        +
        Location: New Britain Region, P.N.G.
        Magnitude: 5.9
        Depth: 59 km
        Date: 19/07/2018
        @@ -146967,7 +146967,7 @@
        Date: 28/02/2018
        circle_marker_35675fbfe671c53006c0f7779ebb8f4e.bindTooltip( `
        -
        Location: Off Coast of Central Amercia
        +
        Location: Off Coast of Central America
        Magnitude: 4.9
        Depth: 49 km
        Date: 07/12/2023
        @@ -182554,7 +182554,7 @@
        Date: 15/12/2021
        circle_marker_7bb17ae13746b0b800510d515b5b4909.bindTooltip( `
        -
        Location: New Britian Region, P.N.G
        +
        Location: New Britain Region, P.N.G
        Magnitude: 5.9
        Depth: 21 km
        Date: 07/07/2017
        @@ -189242,7 +189242,7 @@
        Date: 04/01/2023
        circle_marker_f16640b557f18e2fed024a2b5a3c9b37.bindTooltip( `
        -
        Location: Off Coast of Central Amercia
        +
        Location: Off Coast of Central America
        Magnitude: 4.6
        Depth: 18 km
        Date: 15/10/2023
        @@ -213847,7 +213847,7 @@
        Date: 30/01/2016
        circle_marker_dc2b475b700ea494a40df803129cb958.bindTooltip( `
        -
        Location: Northen Algeria
        +
        Location: Northern Algeria
        Magnitude: 5.0
        Depth: 10 km
        Date: 18/11/2016
        @@ -215918,7 +215918,7 @@
        Date: 01/07/2016
        circle_marker_ba7dac355e28b0b0d1dac8ec668eeaa8.bindTooltip( `
        -
        Location: Mindanao, Phillippines
        +
        Location: Mindanao, Philippines
        Magnitude: 5.3
        Depth: 10 km
        Date: 27/09/2017
        @@ -218331,7 +218331,7 @@
        Date: 30/09/2019
        circle_marker_eb9909c5d8a344920854eadcee551462.bindTooltip( `
        -
        Location: Sourthern East Pacific Rise.
        +
        Location: Southern East Pacific Rise.
        Magnitude: 5.1
        Depth: 10 km
        Date: 01/10/2019
        @@ -221238,7 +221238,7 @@
        Date: 12/11/2019
        circle_marker_295a50c46e7d245915334634df29e243.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.9
        Depth: 10 km
        Date: 15/11/2019
        @@ -221257,7 +221257,7 @@
        Date: 15/11/2019
        circle_marker_6ce94a5b7ecc5f8582c5c406fad0c299.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.5
        Depth: 10 km
        Date: 15/11/2019
        @@ -221276,7 +221276,7 @@
        Date: 15/11/2019
        circle_marker_c954c56add1950149b3f9bf7e5f652c0.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.5
        Depth: 10 km
        Date: 15/11/2019
        @@ -221314,7 +221314,7 @@
        Date: 15/11/2019
        circle_marker_be2d0f2e3107117723adadf2288001fa.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.5
        Depth: 10 km
        Date: 15/11/2019
        @@ -221352,7 +221352,7 @@
        Date: 15/11/2019
        circle_marker_f5d722afb6d16ba9905d236c0ebf3803.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.9
        Depth: 10 km
        Date: 15/11/2019
        @@ -221409,7 +221409,7 @@
        Date: 15/11/2019
        circle_marker_3584c7d308c169fd1461902e15512ccb.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.5
        Depth: 10 km
        Date: 15/11/2019
        @@ -221599,7 +221599,7 @@
        Date: 17/11/2019
        circle_marker_8a6c20ff341ac96f8fe375157cb92e2e.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.6
        Depth: 10 km
        Date: 15/11/2019
        @@ -221618,7 +221618,7 @@
        Date: 15/11/2019
        circle_marker_2c9863e43b1acc79f7e031746da2629d.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.9
        Depth: 10 km
        Date: 15/11/2019
        @@ -221789,7 +221789,7 @@
        Date: 14/11/2019
        circle_marker_6dceb28a2ee2b80abe8f9cb4f4c7fd06.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.7
        Depth: 10 km
        Date: 14/11/2019
        @@ -222036,7 +222036,7 @@
        Date: 31/10/2019
        circle_marker_daa9c98171bfa8e0c6e292b011d344b8.bindTooltip( `
        -
        Location: Mindanoa Philipines
        +
        Location: Mindanoa Philippines
        Magnitude: 5.0
        Depth: 10 km
        Date: 31/10/2019
        @@ -226121,7 +226121,7 @@
        Date: 31/05/2019
        circle_marker_afc3b09d3fe1ae2ad1bc2731b7cdffe3.bindTooltip( `
        -
        Location: Off west Coast of Northen Sumatra
        +
        Location: Off west Coast of Northern Sumatra
        Magnitude: 4.7
        Depth: 10 km
        Date: 31/05/2019
        @@ -226653,7 +226653,7 @@
        Date: 17/06/2019
        circle_marker_092733eed7c2a52a5ce85ab3f21302eb.bindTooltip( `
        -
        Location: Pacific Antartic Ridge.
        +
        Location: Pacific Antarctic Ridge.
        Magnitude: 5.3
        Depth: 10 km
        Date: 17/06/2019
        @@ -229047,7 +229047,7 @@
        Date: 13/07/2019
        circle_marker_0c2b4d88a852b723c144e1a3fec60aab.bindTooltip( `
        -
        Location: Guatamala
        +
        Location: Guatemala
        Magnitude: 5.2
        Depth: 10 km
        Date: 14/07/2019
        @@ -229427,7 +229427,7 @@
        Date: 13/07/2019
        circle_marker_5c1adc4e384e3108cba294a9e102a549.bindTooltip( `
        -
        Location: Pacific Antartic Ridge.
        +
        Location: Pacific Antarctic Ridge.
        Magnitude: 4.9
        Depth: 10 km
        Date: 27/07/2019
        @@ -235849,7 +235849,7 @@
        Date: 19/05/2024
        circle_marker_44cc4560fec9dbfa59dd39abd05e4448.bindTooltip( `
        -
        Location: Norhern Mid-Atlantic Ridge
        +
        Location: Northern Mid-Atlantic Ridge
        Magnitude: 5.0
        Depth: 10 km
        Date: 19/05/2024
        @@ -244665,7 +244665,7 @@
        Date: 30/09/2018
        circle_marker_f4de735aae43c860eda68ef00387dd5a.bindTooltip( `
        -
        Location: Indian Ocean Tripple Junction.
        +
        Location: Indian Ocean Triple Junction.
        Magnitude: 5.0
        Depth: 10 km
        Date: 01/10/2018
        @@ -244684,7 +244684,7 @@
        Date: 01/10/2018
        circle_marker_f3fadb6a8b7b7bcb35ac5bdc3fb1ca4d.bindTooltip( `
        -
        Location: Indian Ocean Tripple Junction.
        +
        Location: Indian Ocean Triple Junction.
        Magnitude: 5.4
        Depth: 10 km
        Date: 01/10/2018
        @@ -245140,7 +245140,7 @@
        Date: 28/09/2018
        circle_marker_96c2a9d46f08aca6f0ee716b073383b7.bindTooltip( `
        -
        Location: Indian Ocean Tripple Junction.
        +
        Location: Indian Ocean Triple Junction.
        Magnitude: 5.6
        Depth: 10 km
        Date: 28/09/2018
        @@ -245216,7 +245216,7 @@
        Date: 28/09/2018
        circle_marker_7a164a1ba71cd7be584c72879de53fcd.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.6
        Depth: 10 km
        Date: 28/09/2018
        @@ -245254,7 +245254,7 @@
        Date: 29/09/2018
        circle_marker_ab6cc4300510f280aa28f6d1a7761f61.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.8
        Depth: 10 km
        Date: 28/09/2018
        @@ -245311,7 +245311,7 @@
        Date: 28/09/2018
        circle_marker_a75b089a522df23b0b7cb6145215d157.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 4.8
        Depth: 10 km
        Date: 28/09/2018
        @@ -245330,7 +245330,7 @@
        Date: 28/09/2018
        circle_marker_ccb3a8d48a7cac634a8a14fbf6877947.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.7
        Depth: 10 km
        Date: 28/09/2018
        @@ -245349,7 +245349,7 @@
        Date: 28/09/2018
        circle_marker_69d89e2fc430bf5d593dd100610a3f10.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.4
        Depth: 10 km
        Date: 28/09/2018
        @@ -245368,7 +245368,7 @@
        Date: 28/09/2018
        circle_marker_7d69acef397282c788bb63cbd328708c.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 4.9
        Depth: 10 km
        Date: 28/09/2018
        @@ -248389,7 +248389,7 @@
        Date: 02/12/2018
        circle_marker_ce74923be01e89bc6c658f180d3e3006.bindTooltip( `
        -
        Location: Carribean Sea
        +
        Location: Caribbean Sea
        Magnitude: 5.4
        Depth: 10 km
        Date: 25/11/2018
        @@ -248788,7 +248788,7 @@
        Date: 25/11/2018
        circle_marker_7035afc1f0a14a98a2bb5b2f21a59fa7.bindTooltip( `
        -
        Location: Carribean Sea.
        +
        Location: Caribbean Sea.
        Magnitude: 5.0
        Depth: 10 km
        Date: 25/11/2018
        @@ -249377,7 +249377,7 @@
        Date: 03/12/2018
        circle_marker_f8546a247d0f7eef3ac806b002fe6cb0.bindTooltip( `
        -
        Location: Norhern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 5.4
        Depth: 10 km
        Date: 04/12/2018
        @@ -250023,7 +250023,7 @@
        Date: 02/11/2018
        circle_marker_635107bbeef8fab73af78a074d94a04c.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 4.9
        Depth: 10 km
        Date: 02/11/2018
        @@ -257338,7 +257338,7 @@
        Date: 06/07/2018
        circle_marker_a7803575da3f3002144699377ed1c744.bindTooltip( `
        -
        Location: Western Indian Antartic Ridge
        +
        Location: Western Indian Antarctic Ridge
        Magnitude: 5.1
        Depth: 10 km
        Date: 30/06/2018
        @@ -264083,7 +264083,7 @@
        Date: 12/04/2019
        circle_marker_b6e9cddbd4880827fbf51eb75b0b7f23.bindTooltip( `
        -
        Location: Nothern Mid Atlantic Ridge
        +
        Location: Northern Mid Atlantic Ridge
        Magnitude: 4.7
        Depth: 10 km
        Date: 12/04/2019
        @@ -264634,7 +264634,7 @@
        Date: 08/04/2019
        circle_marker_03769a079a0eb1c311bcc9b159992ee9.bindTooltip( `
        -
        Location: Off Coast of Central Amercia
        +
        Location: Off Coast of Central America
        Magnitude: 4.8
        Depth: 10 km
        Date: 08/04/2019
        @@ -265451,7 +265451,7 @@
        Date: 15/04/2019
        circle_marker_23583d2429ce845342981e0c34697e22.bindTooltip( `
        -
        Location: Off Coast of Central Amercia
        +
        Location: Off Coast of Central America
        Magnitude: 4.8
        Depth: 10 km
        Date: 16/04/2019
        @@ -266876,7 +266876,7 @@
        Date: 26/01/2019
        circle_marker_ee96e2c1e79360a8d6fcc9cdab5f642a.bindTooltip( `
        -
        Location: Off west Coast of Northen Sumatra
        +
        Location: Off west Coast of Northern Sumatra
        Magnitude: 4.8
        Depth: 10 km
        Date: 27/01/2019
        @@ -268605,7 +268605,7 @@
        Date: 03/01/2019
        circle_marker_5e905ee26138e363b1b8dc3faf4555e2.bindTooltip( `
        -
        Location: Northen Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 5.5
        Depth: 10 km
        Date: 03/01/2019
        @@ -270144,7 +270144,7 @@
        Date: 04/02/2019
        circle_marker_ed0c9aea45159345713dc597ce0fc8d6.bindTooltip( `
        -
        Location: Luzon, Phillipines.
        +
        Location: Luzon, Philippines.
        Magnitude: 5.2
        Depth: 10 km
        Date: 04/02/2019
        diff --git a/static/interactiveCharts/593-customize-bubble-map-with-folium-3.html b/static/interactiveCharts/593-customize-bubble-map-with-folium-3.html index a5c06d89ed..612c86e4bf 100644 --- a/static/interactiveCharts/593-customize-bubble-map-with-folium-3.html +++ b/static/interactiveCharts/593-customize-bubble-map-with-folium-3.html @@ -57466,7 +57466,7 @@
        Date: 10/11/2018
        circle_marker_295a975373598cfa03903aaa2280ae2e.bindTooltip( `
        -
        Location: Nothern Colombia
        +
        Location: Northern Colombia
        Magnitude: 5.5
        Depth: 150 km
        Date: 07/08/2018
        @@ -60335,7 +60335,7 @@
        Date: 17/07/2023
        circle_marker_1dba488d21a924fcf76c90abd45a1ace.bindTooltip( `
        -
        Location: Luzon, Phillipines.
        +
        Location: Luzon, Philippines.
        Magnitude: 5.4
        Depth: 147 km
        Date: 06/02/2019
        @@ -74718,7 +74718,7 @@
        Date: 12/03/2018
        circle_marker_3636ca71cf1f3478fac037263516397d.bindTooltip( `
        -
        Location: 48 km Noth of Swat
        +
        Location: 48 km North of Swat
        Magnitude: 3.7
        Depth: 125 km
        Date: 13/02/2024
        @@ -83629,7 +83629,7 @@
        Date: 23/03/2019
        circle_marker_0dad5d2f44d7d194e084d8f667b710bd.bindTooltip( `
        -
        Location: New Britian Region, Papua New Guinea
        +
        Location: New Britain Region, Papua New Guinea
        Magnitude: 5.6
        Depth: 117 km
        Date: 11/06/2024
        @@ -84218,7 +84218,7 @@
        Date: 30/06/2022
        circle_marker_54a4a8cd7ffffc1ee09a703d6963b465.bindTooltip( `
        -
        Location: Alaska Penisula
        +
        Location: Alaska Peninsula
        Magnitude: 5.0
        Depth: 116 km
        Date: 12/11/2016
        @@ -86479,7 +86479,7 @@
        Date: 26/09/2021
        circle_marker_cf6c9e849ef6ff78d15f68f824cca495.bindTooltip( `
        -
        Location: New Britian Region, P.N.G.
        +
        Location: New Britain Region, P.N.G.
        Magnitude: 5.1
        Depth: 114 km
        Date: 28/11/2018
        @@ -88930,7 +88930,7 @@
        Date: 11/08/2021
        circle_marker_357f68fc8e7b5306f6dc49856bbc00c4.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.2
        Depth: 112 km
        Date: 01/10/2018
        @@ -93699,7 +93699,7 @@
        Date: 26/12/2017
        circle_marker_1bec85c592e2975c496f96d227e44c70.bindTooltip( `
        -
        Location: New Britian Region, Papua New Guinea
        +
        Location: New Britain Region, Papua New Guinea
        Magnitude: 5.6
        Depth: 108 km
        Date: 11/06/2024
        @@ -95732,7 +95732,7 @@
        Date: 09/09/2017
        circle_marker_652e6ff36f2953b59d485baa72368d1c.bindTooltip( `
        -
        Location: Phillipines Islands Region
        +
        Location: Philippines Islands Region
        Magnitude: 5.3
        Depth: 105 km
        Date: 18/08/2016
        @@ -125144,7 +125144,7 @@
        Date: 21/07/2018
        circle_marker_17cd1634b1963b7c6563f838b4801c7a.bindTooltip( `
        -
        Location: Hokkaido japan Regon
        +
        Location: Hokkaido japan Region
        Magnitude: 4.3
        Depth: 79 km
        Date: 12/06/2024
        @@ -126322,7 +126322,7 @@
        Date: 10/10/2023
        circle_marker_d7923b706568b65fb023705043dfd64b.bindTooltip( `
        -
        Location: Luzon, Phillipines.
        +
        Location: Luzon, Philippines.
        Magnitude: 5.0
        Depth: 77 km
        Date: 12/01/2019
        @@ -126873,7 +126873,7 @@
        Date: 05/02/2019
        circle_marker_48c8e04b70f9e0a9f9cc3dcc87e7c002.bindTooltip( `
        -
        Location: New Britian Region,P.N.G,
        +
        Location: New Britain Region,P.N.G,
        Magnitude: 5.3
        Depth: 76 km
        Date: 12/10/2018
        @@ -131243,7 +131243,7 @@
        Date: 22/10/2023
        circle_marker_e5d7f49229562176b1ce05b0ea40daa5.bindTooltip( `
        -
        Location: Indian Ocean Tripple Junction.
        +
        Location: Indian Ocean Triple Junction.
        Magnitude: 5.4
        Depth: 70 km
        Date: 28/09/2018
        @@ -131946,7 +131946,7 @@
        Date: 13/11/2023
        circle_marker_f21c69b2ba93e03f44130720686bd44d.bindTooltip( `
        -
        Location: Kenia Penisula Alaska
        +
        Location: Kenia Peninsula Alaska
        Magnitude: 5.1
        Depth: 70 km
        Date: 03/07/2019
        @@ -131965,7 +131965,7 @@
        Date: 03/07/2019
        circle_marker_34b030ee41384b1563e7893642bd7ce1.bindTooltip( `
        -
        Location: Hindu Kush Region Afganistan
        +
        Location: Hindu Kush Region Afghanistan
        Magnitude: 3.3
        Depth: 70 km
        Date: 25/10/2016
        @@ -139641,7 +139641,7 @@
        Date: 10/03/2017
        circle_marker_6e0f3de42a2abc1e0b78ce697e38c18b.bindTooltip( `
        -
        Location: New Britian Region, P.N.G.
        +
        Location: New Britain Region, P.N.G.
        Magnitude: 5.9
        Depth: 59 km
        Date: 19/07/2018
        @@ -146975,7 +146975,7 @@
        Date: 28/02/2018
        circle_marker_331433839542170fd207234c5e2ddf7a.bindTooltip( `
        -
        Location: Off Coast of Central Amercia
        +
        Location: Off Coast of Central America
        Magnitude: 4.9
        Depth: 49 km
        Date: 07/12/2023
        @@ -182562,7 +182562,7 @@
        Date: 15/12/2021
        circle_marker_3619381f08d0b2e68413206d54544579.bindTooltip( `
        -
        Location: New Britian Region, P.N.G
        +
        Location: New Britain Region, P.N.G
        Magnitude: 5.9
        Depth: 21 km
        Date: 07/07/2017
        @@ -189250,7 +189250,7 @@
        Date: 04/01/2023
        circle_marker_5a75d70d6cc436f2706e036d061f5614.bindTooltip( `
        -
        Location: Off Coast of Central Amercia
        +
        Location: Off Coast of Central America
        Magnitude: 4.6
        Depth: 18 km
        Date: 15/10/2023
        @@ -213855,7 +213855,7 @@
        Date: 30/01/2016
        circle_marker_4ab3997f5ab90ce29b19b1fc695a4683.bindTooltip( `
        -
        Location: Northen Algeria
        +
        Location: Northern Algeria
        Magnitude: 5.0
        Depth: 10 km
        Date: 18/11/2016
        @@ -215926,7 +215926,7 @@
        Date: 01/07/2016
        circle_marker_44d5f15b0b48017549476877176838c8.bindTooltip( `
        -
        Location: Mindanao, Phillippines
        +
        Location: Mindanao, Philippines
        Magnitude: 5.3
        Depth: 10 km
        Date: 27/09/2017
        @@ -218339,7 +218339,7 @@
        Date: 30/09/2019
        circle_marker_9ffbdd22061b514435ba24766b7a48c3.bindTooltip( `
        -
        Location: Sourthern East Pacific Rise.
        +
        Location: Southern East Pacific Rise.
        Magnitude: 5.1
        Depth: 10 km
        Date: 01/10/2019
        @@ -221246,7 +221246,7 @@
        Date: 12/11/2019
        circle_marker_15c945a493580363fb62b47526a4be99.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.9
        Depth: 10 km
        Date: 15/11/2019
        @@ -221265,7 +221265,7 @@
        Date: 15/11/2019
        circle_marker_94124eb5e8560d9997045b767cdf9f7f.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.5
        Depth: 10 km
        Date: 15/11/2019
        @@ -221284,7 +221284,7 @@
        Date: 15/11/2019
        circle_marker_3c376ae07c9174b773f19229f98639c6.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.5
        Depth: 10 km
        Date: 15/11/2019
        @@ -221322,7 +221322,7 @@
        Date: 15/11/2019
        circle_marker_55242cdbaba38a3ea592b70ab83148dc.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.5
        Depth: 10 km
        Date: 15/11/2019
        @@ -221360,7 +221360,7 @@
        Date: 15/11/2019
        circle_marker_6d882db166eb6c78114e4bd887171fca.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.9
        Depth: 10 km
        Date: 15/11/2019
        @@ -221417,7 +221417,7 @@
        Date: 15/11/2019
        circle_marker_642abe848f5ef2a48dc0b3ca0b50c0d4.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.5
        Depth: 10 km
        Date: 15/11/2019
        @@ -221607,7 +221607,7 @@
        Date: 17/11/2019
        circle_marker_15860e29641e4e1a173b411a87a7a12f.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.6
        Depth: 10 km
        Date: 15/11/2019
        @@ -221626,7 +221626,7 @@
        Date: 15/11/2019
        circle_marker_e49972e3a8491b5654aef7f8225a3c3f.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.9
        Depth: 10 km
        Date: 15/11/2019
        @@ -221797,7 +221797,7 @@
        Date: 14/11/2019
        circle_marker_21f36103e92fa3a2832316844f9764a1.bindTooltip( `
        -
        Location: Nothern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 4.7
        Depth: 10 km
        Date: 14/11/2019
        @@ -222044,7 +222044,7 @@
        Date: 31/10/2019
        circle_marker_62e7d3ea3badd31814b87b73207e6177.bindTooltip( `
        -
        Location: Mindanoa Philipines
        +
        Location: Mindanoa Philippines
        Magnitude: 5.0
        Depth: 10 km
        Date: 31/10/2019
        @@ -226129,7 +226129,7 @@
        Date: 31/05/2019
        circle_marker_bd56dfd802c01e970b470831a73d94e5.bindTooltip( `
        -
        Location: Off west Coast of Northen Sumatra
        +
        Location: Off west Coast of Northern Sumatra
        Magnitude: 4.7
        Depth: 10 km
        Date: 31/05/2019
        @@ -226661,7 +226661,7 @@
        Date: 17/06/2019
        circle_marker_c6d009dc78c5277838383cde25c67338.bindTooltip( `
        -
        Location: Pacific Antartic Ridge.
        +
        Location: Pacific Antarctic Ridge.
        Magnitude: 5.3
        Depth: 10 km
        Date: 17/06/2019
        @@ -229055,7 +229055,7 @@
        Date: 13/07/2019
        circle_marker_3dc66a71bd090c6eb9addb6a68a6a3bb.bindTooltip( `
        -
        Location: Guatamala
        +
        Location: Guatemala
        Magnitude: 5.2
        Depth: 10 km
        Date: 14/07/2019
        @@ -229435,7 +229435,7 @@
        Date: 13/07/2019
        circle_marker_4d4c453e8f324a2bdfca2f766d990393.bindTooltip( `
        -
        Location: Pacific Antartic Ridge.
        +
        Location: Pacific Antarctic Ridge.
        Magnitude: 4.9
        Depth: 10 km
        Date: 27/07/2019
        @@ -235857,7 +235857,7 @@
        Date: 19/05/2024
        circle_marker_a60ad587f4389b28c88254c26174afbf.bindTooltip( `
        -
        Location: Norhern Mid-Atlantic Ridge
        +
        Location: Northern Mid-Atlantic Ridge
        Magnitude: 5.0
        Depth: 10 km
        Date: 19/05/2024
        @@ -244673,7 +244673,7 @@
        Date: 30/09/2018
        circle_marker_573a6fc373db770b418c2075fed76eeb.bindTooltip( `
        -
        Location: Indian Ocean Tripple Junction.
        +
        Location: Indian Ocean Triple Junction.
        Magnitude: 5.0
        Depth: 10 km
        Date: 01/10/2018
        @@ -244692,7 +244692,7 @@
        Date: 01/10/2018
        circle_marker_e79020024b986f8433bc8c357beeb13c.bindTooltip( `
        -
        Location: Indian Ocean Tripple Junction.
        +
        Location: Indian Ocean Triple Junction.
        Magnitude: 5.4
        Depth: 10 km
        Date: 01/10/2018
        @@ -245148,7 +245148,7 @@
        Date: 28/09/2018
        circle_marker_bb617e5668fda21c5343c635b45076f8.bindTooltip( `
        -
        Location: Indian Ocean Tripple Junction.
        +
        Location: Indian Ocean Triple Junction.
        Magnitude: 5.6
        Depth: 10 km
        Date: 28/09/2018
        @@ -245224,7 +245224,7 @@
        Date: 28/09/2018
        circle_marker_f19761f58ff5c23ea9320c8d4bd576e6.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.6
        Depth: 10 km
        Date: 28/09/2018
        @@ -245262,7 +245262,7 @@
        Date: 29/09/2018
        circle_marker_85c7c496dea7f1b2d3a4911eb23d4809.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.8
        Depth: 10 km
        Date: 28/09/2018
        @@ -245319,7 +245319,7 @@
        Date: 28/09/2018
        circle_marker_3a09ae4e17d615b79500861fc170c4b8.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 4.8
        Depth: 10 km
        Date: 28/09/2018
        @@ -245338,7 +245338,7 @@
        Date: 28/09/2018
        circle_marker_3d300d27c33b95d7c28753da0a562708.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.7
        Depth: 10 km
        Date: 28/09/2018
        @@ -245357,7 +245357,7 @@
        Date: 28/09/2018
        circle_marker_4e2758998f6a5f5421373d9c47c1f447.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 5.4
        Depth: 10 km
        Date: 28/09/2018
        @@ -245376,7 +245376,7 @@
        Date: 28/09/2018
        circle_marker_8ea0e132e8cb13bd41308a6c99df40b8.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 4.9
        Depth: 10 km
        Date: 28/09/2018
        @@ -248397,7 +248397,7 @@
        Date: 02/12/2018
        circle_marker_5394c7ae7bdea84589aafd1b5b604282.bindTooltip( `
        -
        Location: Carribean Sea
        +
        Location: Caribbean Sea
        Magnitude: 5.4
        Depth: 10 km
        Date: 25/11/2018
        @@ -248796,7 +248796,7 @@
        Date: 25/11/2018
        circle_marker_107c7b4e51d700616b24750c2f23c6b6.bindTooltip( `
        -
        Location: Carribean Sea.
        +
        Location: Caribbean Sea.
        Magnitude: 5.0
        Depth: 10 km
        Date: 25/11/2018
        @@ -249385,7 +249385,7 @@
        Date: 03/12/2018
        circle_marker_7d9608c73dec4adbcb96945c29f60af2.bindTooltip( `
        -
        Location: Norhern Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 5.4
        Depth: 10 km
        Date: 04/12/2018
        @@ -250031,7 +250031,7 @@
        Date: 02/11/2018
        circle_marker_ca07bffe1222ffe91971b8d3ccfc06ae.bindTooltip( `
        -
        Location: Minahassa Penisula Sulawesi
        +
        Location: Minahassa Peninsula Sulawesi
        Magnitude: 4.9
        Depth: 10 km
        Date: 02/11/2018
        @@ -257346,7 +257346,7 @@
        Date: 06/07/2018
        circle_marker_35d94a328574f138bc4e93a9ec65c595.bindTooltip( `
        -
        Location: Western Indian Antartic Ridge
        +
        Location: Western Indian Antarctic Ridge
        Magnitude: 5.1
        Depth: 10 km
        Date: 30/06/2018
        @@ -264091,7 +264091,7 @@
        Date: 12/04/2019
        circle_marker_54516d658c0bb9242bc6b49adbb93891.bindTooltip( `
        -
        Location: Nothern Mid Atlantic Ridge
        +
        Location: Northern Mid Atlantic Ridge
        Magnitude: 4.7
        Depth: 10 km
        Date: 12/04/2019
        @@ -264642,7 +264642,7 @@
        Date: 08/04/2019
        circle_marker_84aa2b6c7bb74127b249b2bb74580fb8.bindTooltip( `
        -
        Location: Off Coast of Central Amercia
        +
        Location: Off Coast of Central America
        Magnitude: 4.8
        Depth: 10 km
        Date: 08/04/2019
        @@ -265459,7 +265459,7 @@
        Date: 15/04/2019
        circle_marker_02b5ff40b383c09552e09e6ae51593b3.bindTooltip( `
        -
        Location: Off Coast of Central Amercia
        +
        Location: Off Coast of Central America
        Magnitude: 4.8
        Depth: 10 km
        Date: 16/04/2019
        @@ -266884,7 +266884,7 @@
        Date: 26/01/2019
        circle_marker_c96bd5e4bb04777c731387732f4166e1.bindTooltip( `
        -
        Location: Off west Coast of Northen Sumatra
        +
        Location: Off west Coast of Northern Sumatra
        Magnitude: 4.8
        Depth: 10 km
        Date: 27/01/2019
        @@ -268613,7 +268613,7 @@
        Date: 03/01/2019
        circle_marker_92753e0eaaa0d4b345e9c74aed3d7f6b.bindTooltip( `
        -
        Location: Northen Molucca Sea
        +
        Location: Northern Molucca Sea
        Magnitude: 5.5
        Depth: 10 km
        Date: 03/01/2019
        @@ -270152,7 +270152,7 @@
        Date: 04/02/2019
        circle_marker_0fb2f23e53b13ef399f8b0d7415a9846.bindTooltip( `
        -
        Location: Luzon, Phillipines.
        +
        Location: Luzon, Philippines.
        Magnitude: 5.2
        Depth: 10 km
        Date: 04/02/2019