text errors in chapter 1 #2
Description
Errors in Chapter 1:
Section: Overview of Jupyter Notebook
programming instead programing:
Jupyter Notebook is becoming increasingly popular as a successful User Interface (UI) for Python programing.
Text below figure 1.5
Wrong library name: np.arange() instead of np.arramge():
Next we will learn four NumPy functions: np.arramge(), np.zeros(), np.ones(), and np.linspace().
Section: The np.linspace() function
Incorrect representation under the first mathematical statement:
Text Formula_B17397_01_001 is useless at this point
Section: Pandas functions for exploring a DataFrame
Subsection: The .info() function
function info() must be lowercase:
If you run adult_df.Info(), ...
Section: Pandas functions for exploring a DataFrame
Subsection: Histograms and boxplots to visualize numerical columns
Wrong function adult_df.age.box() instead of adult_df.age.plot.box():
To create the boxplot for the age column, all you need to change is the last part of the code: adult_df.age.box(). Give it a try.
Text below figure 1.34
Function parameter "Normalize" must be lowercase:
To get the relative frequency table, all you need to do is to specify that you want the table to be normalized: .value_counts(Normalize = True). Give it a try!
Text above figure 1.37
Variable CapitalNet must be begin with lowercase:
As we are only interested in the correlations between education_num, lifeNoEd, and CapitalNet, the last line of the code has removed other columns before running the .corr() function.
some lines later: Text below figure 1.37
Variable CapitalNet must be again begin with lowercase:
... the correlation between education_num and CapitalNet is higher, at 0.117891.
inside figure 1.38:
functions .var() and .describe() must be lowercase
Subsection under figure 1.44 Multi-level access
spelling error "sizable" instead "sizeable":
In this subchapter, we gathered sizable exposure to multi-level indexing and columns.