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Change Log

All notable changes to this project will be documented in this file. This project adheres to Semantic Versioning.

[Unreleased]

[1.9.5] - 2016-01-17

Added

  • Offline matplotlib to Plotly figure conversion. Use offline.plot_mpl to convert and plot a matplotlib figure as a Plotly figure independently of IPython/Jupyter notebooks or use offline.iplot_mpl to convert and plot inside of IPython/Jupyter notebooks. Additionally, use offline.enable_mpl_offline to convert and plot all matplotlib figures as plotly figures inside an IPython/Jupyter notebook. See examples below:

An example independent of IPython/Jupyter notebooks:

from plotly.offline import init_notebook_mode, plot_mpl
import matplotlib.pyplot as plt

init_notebook_mode()

fig = plt.figure()
x = [10, 15, 20]
y = [100, 150, 200]
plt.plot(x, y, "o")

plot_mpl(fig)

An example inside of an IPython/Jupyter notebook:

from plotly.offline import init_notebook_mode, iplot_mpl
import matplotlib.pyplot as plt

init_notebook_mode()

fig = plt.figure()
x = [10, 15, 20]
y = [100, 150, 200]
plt.plot(x, y, "o")

iplot_mpl(fig)

An example of enabling all matplotlib figures to be converted to Plotly figures inside of an IPython/Jupyter notebook:

from plotly.offline import init_notebook_mode, enable_mpl_offline
import matplotlib.pyplot as plt

init_notebook_mode()
enable_mpl_offline()

fig = plt.figure()
x = [10, 15, 20, 25, 30]
y = [100, 250, 200, 150, 300]
plt.plot(x, y, "o")
fig

[1.9.4] - 2016-01-11

Added

  • Offline plotting now works outside of the IPython/Jupyter notebook. Here's an example:
from plotly.offline import plot
from plotly.graph_objs import Scatter

plot([Scatter(x=[1, 2, 3], y=[3, 1, 6])])

This command works entirely locally. It writes to a local HTML file with the necessary plotly.js code to render the graph. Your browser will open the file after you make the call.

The call signature is very similar to plotly.offline.iplot and plotly.plotly.plot and plotly.plotly.iplot, so you can basically use these commands interchangeably.

If you want to publish your graphs to the web, use plotly.plotly.plot, as in:

import plotly.plotly as py
from plotly.graph_objs import Scatter

py.plot([Scatter(x=[1, 2, 3], y=[5, 1, 6])])

This will upload the graph to your online plotly account.

[1.9.3] - 2015-12-08

Added

  • Check for no_proxy when determining if the streaming request should pass through a proxy in the chunked_requests submodule. Example: no_proxy='my_stream_url' and http_proxy=my.proxy.ip:1234, then my_stream_url will not get proxied. Previously it would.

[1.9.2] - 2015-11-30

Bug Fix: Previously, the "Export to plot.ly" link on offline charts would export your figures to the public plotly cloud, even if your config_file (set with plotly.tools.set_config_file to the file ~/.plotly/.config) set plotly_domain to a plotly enterprise URL like https://plotly.acme.com.

This is now fixed. Your graphs will be exported to your plotly_domain if it is set.

[1.9.1] - 2015-11-26

Added

  • The FigureFactory can now create annotated heatmaps with .create_annotated_heatmap. Check it out with:
import plotly.tools as tls
help(tls.FigureFactory.create_annotated_heatmap)
  • The FigureFactory can now create tables with .create_table.
import plotly.tools as tls
help(tls.FigureFactory.create_table)

[1.9.0] - 2015-11-15

  • Previously, using plotly offline required a paid license. No more: plotly.js is now shipped inside this package to allow unlimited free use of plotly inside the ipython notebook environment. The plotly.js library that is included in this package is free, open source, and maintained independently on GitHub at https://github.com/plotly/plotly.js.
  • The plotly.js bundle that is required for offline use is no longer downloaded and installed independently from this package: plotly.offline.download_plotlyjs is deprecated.
  • New versions of plotly.js will be tested and incorporated into this package as new versioned pip releases; plotly.js is not automatically kept in sync with this package.

[1.8.12] - 2015-11-02

  • Big data warning mentions plotly.graph_objs.Scattergl as possible solution.

[1.8.9] - 2015-10-11

[1.8.8] - 2015-10-05

  • Sometimes creating a graph with a private share-key doesn't work - the graph is private, but not accessible with the share key. Now we check to see if it didn't work, and re-try a few times until it does.

[1.8.7] - 2015-10-01

Added

  • The FigureFactory can now create dendrogram plots with .create_dendrogram.

[1.8.6] - 2015-09-28

Fixed

  • Saving "world_readable" to your config file via plotly.tools.set_config actually works.

Added

  • You can also save auto_open and sharing to the config file so that you can forget these keyword argument in py.iplot and py.plot.

[1.8.5] - 2015-09-29

Fixed

  • Fixed validation errors (validate=False workaround no longer required)

Added

  • Auto-sync API request on import to get the latest schema from Plotly
  • .-access for nested attributes in plotly graph objects
  • General .help() method for plotly graph objects
  • Specific attribute .help(<attribute>) also included

Removed

  • No more is streamable, streaming validation.

[1.8.3] - 2015-08-14

Fixed

  • Fixed typos in plot and iplot documentations

[1.8.2] - 2015-08-11

Added

  • CHANGELOG
  • sharing keyword argument for plotly.plotly.plot and plotly.plotly.iplot with options 'public' | 'private' | 'secret' to control the privacy of the charts. Depreciates world_readable

Changed

  • If the response from plot or iplot contains an error message, raise an exception

Removed

  • height and width are no longer accepted in iplot. Just stick them into your figure's layout instead, it'll be more consistent when you view it outside of the IPython notebook environment. So, instead of this:

     py.iplot([{'x': [1, 2, 3], 'y': [3, 1, 5]}], height=800)

    do this:

     py.iplot({
 	'data': [{'x': [1, 2, 3], 'y': [3, 1, 5]}],
 	'layout': {'height': 800}
 })

Fixed

  • The height of the graph in iplot respects the figure's height in layout