Skip to content

Latest commit

 

History

History
1332 lines (1117 loc) · 63 KB

CHANGELOG.md

File metadata and controls

1332 lines (1117 loc) · 63 KB

Change Log

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

[3.7.1] - 2019-03-19

Fixed

  • Fixed .update on numbered axis objects for Python < 3.6 (#1462, #1464)

[3.7.0] - 2019-03-08

Updated

Added

  • Added new auto_play argument to offline plot and iplot to control whether figures with frames are automatically animated when the figure is loaded (#1447)
  • Added support for uploading "offline" animations (those with inline data arrays rather than grid references) to Chart Studio using plotly.plotly.create_animations (#1432)

Updated

  • Updated implementation of the ternary_contour figure factory that was added in 3.6.0. The new implementation uses the native plotly.js ternary axes and provides ILR transform support. (#1418)

Fixed

  • Make sure the trace selectedpoints property of FigureWidget traces is updated on the Python side in response to plotly.js selection events (#1433)
  • Fix validation for 0-dimensional numpy arrays (#1444). Special thanks to @ankokumoyashi for this contribution!

[3.6.1] - 2019-02-08

Updated

Fixed

  • Crash on import when ipywidgets < 7 installed (#1425)
  • Made scipy an optional import for the ternary contour figure factory (#1423)
  • Eliminated use of deprecated numpy.asscalar function (#1428)

Updated

  • Updated Plotly.js to version 1.44.1. Select highlights included below. See the plotly.js CHANGELOG for more information.

[3.6.0] - 2019-02-01

Updated

  • Updated Plotly.js to version 1.44.1. Select highlights included below. See the plotly.js CHANGELOG for more information.

Added

  • Add isosurface gl3d trace type (plotly/plotly.js#3438)
  • Preview of ternary contour figure factory (#1413). Special thanks to @emmanuelle for this contribution!
  • Add support for line.color colorbars for scatter3d traces (#1085, plotly/plotly.js#3384)
  • Add support for hovertemplate on scatterpolar, scatterpolargl, scatterternary, barpolar, choropleth, scattergeo, and scattermapbox trace (plotly/plotly.js#3398, plotly/plotly.js#3436)
  • Add width attribute to box and violin traces (plotly/plotly.js#3234)
  • Add support for <sup>, <sup>, <b>, <i> and <em> pseudo-html tags in extra (aka trace "name") hover labels (plotly/plotly.js#3443)
  • Add 4 additional colors to the colorway cycle of the plotly themes (#1408)
  • Automatically coerce array-like objects (e.g. xarray DataArrays) to numpy arrays (#1393). Special thanks to @malmaud for this contribution!

Fixed

  • Fix annotated heatmap text color when values are specified as a nested list (#1300)
  • Fix update method with legacy title* properties (#1403)
  • Fix deprecation warnings on Python 3.7 and ipywidgets > 7.0 (#1417). Special thanks to @Juanlu001 for this contribution!

[3.5.0] - 2019-01-04

Updated

Changed

  • Plotly.js 1.43 converted title properties (e.g. layout.title) from strings into compound objects that contain the text as the text property along with new title placement attributes x, y, xref, yref, xanchor, yanchor and pad. Plotly.py 3.5.0 follows the new schema, but still supports specifying title as a string, in which case the string is assigned to the title.text property (#1302)
  • Plotly.js 1.43 also moved existing title* properties (e.g. layout.titlefont) under the title object (e.g. layout.title.font). Plotly.py 3.5.0 follows the new schema, but still supports the legacy title* properties by mapping them to the corresponding title.* property (#1302)
  • The update method on graph_objs now returns the updated object in order to support chaining multiple update operations together (#1379)
  • The show_link option has been set to False by default in the offline plot and iplot functions. Now that the "send data to cloud" button has been disabled by default in plotly.js 1.43.0, no buttons/links will be displayed by default that result in data being sent off of the local machine (#1304)
  • config options that are not known by plotly.py result in a warning but are still passed along to plotly.js. Prior to this change these unknown options were dropped silently (#1290)
  • Built-in themes now specify colorscales using the new global layout.colorscale properties. Previously the colorscales were defined for each trace type individually. This reduces the size of the resulting theme files (#1303)
  • Increased the maximum retry time of the orca integration from 8s to 30s (#1297)

Fixed

  • Fixed FigureWidget performance regression that, when working with large datasets, resulted in a slight freeze of the widget after user interactions (pan, zoom, etc) (1305)
  • Fix orca error when the ELECTRON_RUN_AS_NODE environment variable is set (#1293)
  • The 'responsive' config key was being silently blocked (#1290)
  • Fixed error when using unicode characters in string properties on Python 2 (#1289)
  • Removed invalid calls to non-existent validate and strip_style Figure methods in matplotlylib conversion logic (#1128)

[3.4.2] - 2018-11-23

Fixed

  • config options are now supported when using plotly.offline.iplot to display a figure in JupyterLab. Requires version 0.18.1 of the @jupyterlab/plotly-extension extension. (#1281, jupyterlab/jupyter-renderers#168)
  • Custom plotly_domain values are now supported in FigureWidget in both the classic notebook and JupyterLab (#1284)

[3.4.1] - 2018-11-09

Updated

Fixed

  • Fixed histogram binning with pandas Series or numpy array (regression introduced in 3.4.0) (#1257, plotly/plotly.js#3211)
  • Fixed incorrect validation error on the args property of layout.updatemenu.Button() when value is a list that starts with a list (#1265)
  • Fixed deadlock causing plotly.io.write_image to hang on Windows after exporting more than ~25 images (#1255)
  • Fixed plot display error for scattergl trace with mode='lines' and more than 100k points (#1271)
  • Fixed responsive resizing error with iplot in the classic notebook (#1263)

[3.4.0] - 2018-11-02

Updated

  • Updated Plotly.js to version 1.42.2. Select highlights included below, see the plotly.js CHANGELOG for more information.

Added

  • Default figure properties may now be customized using figure templates (themes) and 7 new predefined templates are bundled with plotly.py (#1224)
  • Added Parallel Categories (parcats) trace type for the visualization of multi-dimensional categorical datasets (plotly/plotly.js#2963)
  • Added LaTeX typesetting support for figures displayed in the Jupyter Notebook using plotly.offline.iplot and plotly.graph_objs.FigureWidget. Note: There are still outstanding issues with MathJax rendering in FireFox, but it is now working well in Chrome. (#1243)
  • Added include_mathjax argument to plotly.offline.plot to support the creation of HTML files with LaTeX typesetting (#1243)
  • Added new plotly.offline.get_plotlyjs function that returns the contents of the bundled plotly.js library as a string (#637, #1246)
  • Added new plotly.offline.get_plotlyjs_version function that returns the version of the bundled plotly.js library (#1246)
  • HTML div strings returned by plotly.offline.plot now contain logic to automatically resize the figure responsively. This logic was previously only added for html files. (#1043, #1234)
  • Figures displayed using plotly.offline.iplot in the classic Jupyter Notebook will now resize responsively (#1234)
  • Added 'cdn', 'directory', and path string include_plotlyjs options in plotly.offline.plot (#1234)
    • When 'cdn', the resulting html file/div includes a script tag reference to the plotlyjs cdn.
    • When 'directory', the resulting html file/div includes a script tag reference to a plotly.min.js bundle in the same directory as the html file. If output_type is 'file' then this plotly.min.js bundle is created in the output directory if it doesn't already exist.
    • When a string ending with '.js', the resulting html file/div includes a script tag that references this exact path. This can be used to point to a plotly.js bundle from an alternative CDN.
  • Added a new color_threshold argument to the create_dendrogram figure factory to control the dendrogram clustering cutoff (#995, #1075, #1214)
  • Added support for autorange='reversed' in 3D axes (#803, plotly/plotly.js#3141)
  • Added new gl3d tick and title auto-rotation algorithm that limits text overlaps (plotly/plotly.js#3084, plotly/plotly.js#3131)
  • Added modebar layout style attributes: orientation, bgcolor, color and activecolor (plotly/plotly.js#3068, plotly/plotly.js#3091)
  • Added title, titleposition and titlefont attributes to pie traces (plotly/plotly.js#2987)
  • Added hoverlabel.split attribute to ohlc and candlestick traces to split hover labels into multiple pieces (plotly/plotly.js#2959)
  • Added support for line.shape values 'hv', 'vh', 'hvh' and 'vhv' in scattergl traces (plotly/plotly.js#3087)
  • Added trace, node and link hoverinfo for sankey traces (#3096, #3150)
  • Added per-sector textfont settings in pie traces (#3130)

Changed

Fixed

  • Plotly's use of MathJax for LaTeX typesetting no longer interferes with the Jupyter Notebook's use of MathJax (#445, #360)
  • Fixed several issues with the use of reversescale=True in the create_annotated_heatmap figure factory (#1251)
  • Fixed case where plotly.offline.iplot would fail to render in the classic Jupyter Notebook if the notebook contained a Markdown headline with the text "Plotly" (#816)
  • None values in a scatter.hovertext list are now omitted from the hover label rather than being displayed as the string "None" (#1244)
  • Subplot titles created by plotly.tools.make_subplots are now positioned properly when custom row_width/column_width arguments are specified (#1229)
  • The bar.width property may now be specified as a numpy array or a pandas series (#1231, plotly/plotly.js#3169)
  • Error bars are now scaled correctly for logarithmic scatter3d traces (#1139)
  • Use uuid.uuid4 rather than uuid.uuid1 to work around an upstream Python bug (#1235, #1236)
  • The layout.grid.subplots property may now be specified as a 2D list of subplot identifiers (#1220, #1240)
  • Fixed scatter3d text alignment (#1055, plotly/plotly.js#3180)

JupyterLab Versions

For use with JupyterLab, the following versions of the following packages must be installed:

  • Python Packages

    • plotly==3.4.0
    • ipywidgets>=7.2
    • notebook>=5.3
    • jupyterlab==0.35
  • JupyterLab Extensions

    • plotlywidget@0.5.0
    • @jupyter-widgets/jupyterlab-manager@0.38
    • @jupyterlab/plotly-extension@0.18

[3.3.0] - 2018-09-28

Updated

  • Updated Plotly.js to version 1.41.3. Select highlights included below, see the plotly.js CHANGELOG for more information.
  • Do not create or check permissions on the ~/.plotly configuration directory until a configuration write operation is performed (#1195). This change avoids some concurrency problems associated with running many instances of plotly.py simultaneously (#1068).

Added

  • Enable selection by clicking on points via new layout attribute clickmode and flag 'select' (#2944)
  • Added stacked area charts via new attributes stackgroup and stackgaps in scatter traces (#2960)
  • Added barpolar trace type - which replace and augment area traces (#2954)
  • Added polar.hole layout parameter to punch hole at the middle of polar subplot offsetting the start of the radial range (#2977, #2996)
  • Figures may now be easily converted to and from JSON using the new to_json, from_json, read_json, and write_json functions in the plotly.io package (#1188)
  • Figures and graph objects now support deepcopy and pickle operations (#1191)
  • The location of the "~/.plotly" settings directory may now be customized using the PLOTLY_DIR environment variable (#1195)
  • Added optional scaleratio argument to the create_quiver figure factory. When specified, the axes are restricted to this ratio and the quiver arrows are computed to have consistent lengths across angles. (#1197)

Fixed

  • Replace use of pkg_resources.resource_string with pkgutil.get_data to improve compatibility with cx_Freeze (#1201)
  • An exception is no longer raised when an optional dependency raises an exception on import. The exception is logged and plotly.py continues as if the dependency were not installed (#1192)
  • Fixed invalid dendrogram axis labels when the points being clustered contain duplicate values (#1186)
  • Added missing LICENSE.txt file to PyPI source distribution (#765)

JupyterLab Versions

For use with JupyterLab, the following versions of the following packages must be installed:

  • Python Packages

    • plotly==3.3.0
    • ipywidgets>=7.2
    • notebook>=5.3
    • jupyterlab==0.34
  • JupyterLab Extensions

    • plotlywidget@0.4.0
    • @jupyter-widgets/jupyterlab-manager@0.37
    • @jupyterlab/plotly-extension@0.17

[3.2.1] - 2018-09-14

This is a patch release that fixes a few bugs and reintroduces a few version 2 features that were not supported in version 3.

The bundled version of plotly.js remains at 1.40.1

JupyterLab Versions

For use with JupyterLab, the following versions of the following packages must be installed:

  • Python Packages

    • plotly==3.2.1
    • ipywidgets>=7.2
    • notebook>=5.3
    • jupyterlab==0.34
  • JupyterLab Extensions

    • plotlywidget@0.3.0
    • @jupyter-widgets/jupyterlab-manager@0.37
    • @jupyterlab/plotly-extension@0.17

Added

  • An optional skip_invalid argument has been added to the Figure and FigureWidget constructors. By default, skip_invalid is False and invalid figure properties will result in an exception (this is identical to the previous behavior). When skip_invalid is set to True, invalid properties will instead be silently ignored. This argument replaces the _raise argument that was available in version 2, and makes it possible to import figure definitions from different plotly versions, where incompatible properties are ignored rather than causing an exception.
  • A to_ordered_dict method has been added to the Figure and FigureWidget classes. This method returns a representation of the figure as a nested structure of OrdererdDict and list instances where the keys in each OrderedDict are sorted alphabetically. This method replaces the get_ordered method that was available in version 2, and makes it possible to traverse the nested structure of a figure in a deterministic order.

Fixed

[3.2.0] - 2018-09-05

This release introduces the long-anticipated ability to programmatically export figures as high quality static images in both raster and vector formats.

JupyterLab Versions (Python 3.5+)

For use with JupyterLab, the following versions of the following packages must be installed:

  • Python Packages

    • plotly==3.2.0
    • ipywidgets>=7.2
    • notebook>=5.3
    • jupyterlab==0.34
  • JupyterLab Extensions

    • plotlywidget@0.3.0
    • @jupyter-widgets/jupyterlab-manager@0.37
    • @jupyterlab/plotly-extension@0.17

Added

  • plotly.js version 1.40.1, which introduces the following features:
  • Support for offline static image export with the to_image and write_image functions in the new plotly.io package (#1120).
    • Note: Image export requires the plotly orca command line utility and the psutil Python package.
  • New documentation sections covering Static Image Export and Orca Management
  • Support for displaying FigureWidget instances in static contexts (e.g. nbviewer) just like the built-in ipywidgets (#1117)
  • Full integration of the Cividis colorscale (#883)
  • conda packaging
    • From here forward, new versions of plotly.py will be published to the plotly anaconda channel on the same day they are published to PyPI. (72ad0e4)
    • The README now includes conda installation instructions alongside the pip instructions.
    • In addition to the existing installation approaches, orca is now also available as a conda package from the plotly anaconda channel.

Updated

  • Show traces at the top of the Gantt chart's colorbar (#1110)
  • Significantly improved validation performance for numeric pandas Series objects (#1149)
  • Specialize auto-generated docstrings for Python syntax
  • More robust and specific logic for retrying requests to the plot.ly cloud service (#1146)
  • Support basic authentication when using the streaming API behind a proxy server (#1133)

Fixed

  • Validators for dash properties (e.g. scatter.line.dash) incorrectly rejected dash length lists (#1136)
  • Annotated heatmap error when custom colorscale was specified (#1151)
  • Incorrect deprecation warning for deprecated plotly.graph_objs.Annotations class (#1138)
  • Harmless JavaScript console error when opening an html file produced by plotly.offline.plot (#1152)
  • Incorrect validation errors when writing data to the streaming API (#1145)

[3.1.1] - 2018-08-10

This release is a minor bug-fix update to version 3.1.0

JupyterLab Versions

For use with JupyterLab, the following versions of the following packages must be installed:

  • Python Packages

    • plotly==3.1.1
    • ipywidgets>=7.2
    • notebook>=5.3
    • jupyterlab==0.33
  • JupyterLab Extensions

    • plotlywidget@0.2.1
    • @jupyter-widgets/jupyterlab-manager@0.36
    • @jupyterlab/plotly-extension@0.16

Updated

  • Updated plotly.js to version 1.39.4.

Fixed

[3.1.0] - 2018-07-20

JupyterLab Versions

For use with JupyterLab, the following versions of the following packages must be installed. See README.md for instructions.

  • Python Packages

    • plotly==3.1.0
    • ipywidgets>=7.2
    • notebook>=5.3
    • jupyterlab==0.32.1
  • JupyterLab Extensions

    • plotlywidget@0.2.0
    • @jupyter-widgets/jupyterlab-manager@0.35
    • @jupyterlab/plotly-extension@0.16

Updated

Added

  • Added 3D streamtube traces plotly/plotly.js#2658
  • Added support for on-graph text in scattergl traces
  • Added gridshape attribute to polar subplots with values 'circular' (the default) and 'linear' (to draw polygon grids) plotly/plotly.js#2739

[3.0.2] - 2018-07-17

This is a minor bug-fix release to 3.0.0

JupyterLab plotlywidget version: 0.1.1

Plotly.js version: 1.38.3

Fixed

  • Several errors related to numbered subplot labels (e.g. xaxis2, polar3, etc.) GH1057
  • Error where the v property was ignored in cone traces GH1060
  • Assorted performance improvements when constructing graph objects GH1061

[3.0.1] - 2018-07-17 [YANKED]

Note: This release's installation was broken. It has been removed from PyPI

[3.0.0] - 2018-07-05

This is a major version with many exciting updates. See the Introducing plotly.py 3.0.0 post for more information.

JupyterLab plotlywidget version: 0.1.1

Plotly.js version: 1.38.3

Added

  • Full Jupyter ipywidgets integration with the new graph_objs.FigureWidget class
  • FigureWidget figures can be updated interactively using property assignment syntax
  • The full trace and layout API is generated from the plotly schema to provide a great experience for interactive use in the notebook
  • Support for setting array properties as numpy arrays. When numpy arrays are used, ipywidgets binary serialization protocol is used to avoid converting these to JSON strings.
  • Context manager API for animation. Run help(go.Figure().batch_animate) for the full doc string.
  • Perform automatic retries when communicating with plot.ly services. This introduces a new required dependency on the retrying library.
  • Improved data validation covering the full API with clear, informative error messages. This means that incorrect properties and/or values now always raise a ValueError with a description of the error, the invalid property, and the available properties on the level that it was placed in the graph object. Eg. go.Scatter(foo=123) raises a validation error. See https://plot.ly/python/reference/ for a reference to all valid properties and values in the Python API.
  • Error message for plotly.figure_factory.create_choropleth is now helpful to Anaconda users who do not have the correct modules installed for the County Choropleth figure factory.

Changed / Deprecated

Please see the migration guid for a full list of the changes and deprecations in version 3.0.0

[2.7.0] - 2018-05-23

Updated

  • Updated plotly.min.js to version 1.38.0.
    • New features include a 3D cone trace to visualize vector fields.
    • See the plotly.js CHANGELOG for additional information regarding the updates.

[2.6.0] - 2018-05-09

Updated

  • Updated plotly.min.js to version 1.37.1.
    • New features include a splom (scatter plot matrix) trace type.
    • See the plotly.js CHANGELOG for additional information regarding the updates.
  • Error message for plotly.figure_factory.create_choropleth is more helpful for Windows users on installing geopandas and dependencies including shapely.

[2.5.1] - 2018-03-26

Fixed

  • plotly.figure_factory.create_choropleth now works in Windows without raising an OSError. The module now uses cross-platform path tools from os to manipulate and manage the shapefiles contained in this package.

[2.5.0] - 2018-03-12

Fixed

  • import plotly.figure_factory does not fail if pandas is not installed. See plotly#958

Added

  • New parameter fill_percent to the .insert method for the dashboards API. You can now insert a box into the dashboard layout and specify what proportion of the original container box it will occupy. Run help(plotly.dashboard_objs.Dashboard.insert) for more information on fill_percent.

Updated

  • Updated plotly.min.js to version 1.35.2.
    • New features include adding an automargin attribute to cartesian axes and a layout grids attribute for easy subplot generation.
    • See the plotly.js CHANGELOG for additional information regarding the updates.
  • plotly.figure_factory.create_choropleth has changed some of the default plotting options:

[2.4.1] - 2018-02-21

Fixed

  • The required shapefiles to generate the choropleths via plotly.figure_factory.create_choropleth are now shipped in the package data.

[2.4.0] - 2018-02-16

Added

  • County Choropleth figure factory. Call help(plotly.figure_factory.create_choropleth) for examples and how to get started making choropleths of US counties with the Python API.

Note: Calling plotly.figure_factory.create_choropleth will fail with an IOError due to missing shapefiles see: https://github.com/plotly/plotly.py/blob/master/CHANGELOG.md#241---2018-02-21

[2.3.0] - 2018-01-25

Fixed

  • Merged pull request that fixes GraphWidget for IPython > v6

Updated

  • Updated plotly.min.js to version 1.33.1.
    • New plot types include a violin trace type.
    • New features include completely rewritten scattergl using regl and a completely rewritten polar chart renderer.
    • See the plotly.js CHANGELOG for additional information regarding the updates.

[2.2.3] - 2017-12-04

Added

-column_width and row_width parameters for plotly.tools.make_subplots. Call help(plotly.tools.make_subplots) for documentation.

Updated

  • Updated plotly.min.js to version 1.31.2.
    • Fixes include adjustments to table trace for offline plotting.
    • See the plotly.js CHANGELOG for additional information regarding the updates.

[2.2.2] - 2017-11-23

Added

  • Bullet chart figure factory. Call help(plotly.figure_factory.create_bullet) for examples and how to get started making bullet charts with the API.

[2.2.1] - 2017-10-26

Fixed

  • Presentation objects now added to setup.py

[2.2.0] - 2017-10-26

Added

  • NEW Presentations API for Python! Run help(plotly.presentation_objs.Presentations) for help or check out the new documentation

[2.1.0] - 2017-10-10

Updated

  • Updated plotly.min.js to version 1.31.0.
    • New features include a table trace type.
    • See the plotly.js CHANGELOG for additional information regarding the updates.

[2.0.16] - 2017-10-06

Updated

  • Updated plotly.min.js to version 1.31.0 for plotly.offline.

[2.0.15] - 2017-08-22

Updated

  • Updated plotly.min.js to version 1.30.0 for plotly.offline.

[2.0.14] - 2017-08-09

Fixed

  • Sharekey enabling issue where plots were made private instead of secret.
  • Issue removing rug plots from violin plots with multiple traces.

[2.0.13] - 2017-08-04

Updated

  • Updated plotly.min.js to version 1.29.1 for plotly.offline.
  • figure_factory.create_gantt and figure_factory.create_dendrogram now return a Plotly figure (consistent with other figure factory chart types).
  • offline.init_notebook_mode() is now optional when using offline.iplot().

[2.0.12] - 2017-06-30

Updated

  • Updated plotly.min.js to version 1.28.3 for plotly.offline.

Added

  • figure_factory.create_facet_grid now supports histogram, bar, and box traces.

[2.0.11] - 2017-06-20

Updated

  • Updated plotly.min.js to version 1.28.1 for plotly.offline.

[2.0.10] - 2017-06-12

Added

  • The figure_factory can now create facet grids with .create_facet_grid. Check it out with:
import plotly.figure_factory as ff
help(ff.create_facet_grid)

[2.0.9] - 2017-05-30

Fixed

Added

  • 'sort' parameter to FF.create_violin to control whether violin plots are sorted alphabetically.

[2.0.8] - 2017-04-21

Added

  • Beta: Added API methods that wrap the API endpoint for managing Dash objects on plot.ly. The API interface is under plotly.api.v2.dash_apps
  • offline embedded plots are now responsive to window resizing when output_type == "div" is set in plotly.offline.iplot().
  • Offline embedded plots are now responsive to window resizing when output_type == "div" is set in plotly.offline.iplot().
  • Offline animations are now supported on Plotly Cloud.

Updated

  • Updated plotly.min.js to version 1.26.0 for plotly.offline.

Updated

  • plotly.offline.plot and plotly.offline.iplot now accept various configuration options for their arguments.

[2.0.7] - 2017-04-07

Updated

  • Updated plotly.min.js to version 1.25.0 for plotly.offline.

Added

  • Added check to verify the share key is enabled when secret charts are created.

[2.0.6] - 2017-03-20

Added

  • Added a new mimetype 'text/vnd.plotly.v1+html' for iplot outputs.

[2.0.5] - 2017-03-07

Fixed

  • import plotly was broken in 2.0.3 and 2.0.2 because the new dashboard_objs wasn't included in our setup.py's "packages". Now it is and import plotly and the other features introduced in 2.0.3 and 2.0.2 should work.

[2.0.4] - 2017-03-07 [YANKED]

Note: This release's installation was broken. It has been removed from PyPI

Added

  • Added dashboard_objs to top level import.

[2.0.3] - 2017-03-06 [YANKED]

Note: This release's installation was broken. It has been removed from PyPI

Added

  • Dashboards can now be created using the API and uploaded to Plotly. Use import plotly.dashboard_objs to create a Dashboard object. You can learn more about Dashboard objects by running help(plotly.dashboard_objs) and help(plotly.plotly.plotly.dashboard_ops) for uploading and retrieving dashboards from the cloud.

[2.0.2] - 2017-02-20

Fixed

  • Offline plots created with plotly.offline.plot now resize as expected when the window is resized.
  • plotly.figure_factory.create_distplot now can support more than 10 traces without raising an error. Updated so that if the list of colors (default colors too) is less than your number of traces, the color for your traces will loop around to start when it hits the end.

[2.0.1] - 2017-02-07

Added

  • Support for rendering plots in nteract! See nteract/nteract#662 for the associated PR in nteract.
  • As part of the above, plotly output now prints with a custom mimetype - application/vnd.plotly.v1+json
  • memoize decorator added to plotly.utils

Changed

  • a Grid from plotly.grid_objs now accepts a pandas.Dataframe as its argument.
  • computationally-intensive graph_reference functions are memoized.

[2.0.0] - 2017-01-25

Changed

  • plotly.exceptions.PlotlyRequestException is always raised for network failures. Previously either a PlotlyError, PlotlyRequestException, or a requests.exceptions.ReqestException could be raised. In particular, scripts which depend on try-except blocks containing network requests should be revisited.
  • plotly.py:sign_in now validates to the plotly server specified in your config. If it cannot make a successful request, it raises a PlotlyError.
  • plotly.figure_factory will raise an ImportError if numpy is not installed.
  • plotly.figure_factory.create_violin() now has a rugplot parameter which determines whether or not a rugplot is draw beside each violin plot.

Deprecated

  • plotly.tools.FigureFactory. Use plotly.figure_factory.*.
  • (optional imports) plotly.tools._*_imported It was private anyhow, but now it's gone. (e.g., _numpy_imported)
  • (plotly v2 helper) plotly.py._api_v2 It was private anyhow, but now it's gone.

[1.13.0] - 2016-12-17

Added

  • Python 3.5 has been added as a tested environment for this package.

Updated

  • plotly.plotly.create_animations and plotly.plotly.icreate_animations now return appropriate error messages if the response is not successful.
  • frames are now integrated into GRAPH_REFERENCE and figure validation.

Changed

  • The plot-schema from https://api.plot.ly/plot-schema is no longer updated on import.

[1.12.12] - 2016-12-06

Updated

  • Updated plotly.min.js to version 1.20.5 for plotly.offline.
  • FF.create_scatterplotmatrix now by default does not show the trace labels for the box plots, only if diag=box is selected for the diagonal subplot type.

[1.12.11] - 2016-12-01

Fixed

  • The link text in the bottom right corner of the offline plots now properly displays Export to [Domain Name] for the given domain name set in the users' .config file.

[1.12.10] - 2016-11-28

Updated

  • FF.create_violin and FF.create_scatterplotmatrix now by default do not print subplot grid information in output
  • Removed alert that occured when downloading plot images offline. Please note: for higher resolution images and more export options, consider making requests to our image servers. See: help(py.image) for more details.

Added

  • Plot configuration options for offline plots. See the list of configuration options and examples for more information.
    • Please note that these configuration options are for offline plots ONLY. For configuration options when embedding online plots please see our embed tutorial.
  • colors.py file which contains functions for manipulating and validating colors and arrays of colors
  • 'scale' param in FF.create_trisurf which now can set the interpolation on the colorscales
  • animations now work in offline mode. By running plotly.offline.plot() and plotly.offline.iplot() with a fig with frames, the resulting plot will cycle through the figures defined in frames either in the browser or in an ipython notebook respectively. Here's an example:
import IPython.display
from IPython.display import display, HTML
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)

figure_or_data = {'data': [{'x': [1, 2], 'y': [0, 1]}],
                  'layout': {'xaxis': {'range': [0, 3], 'autorange': False},
                             'yaxis': {'range': [0, 20], 'autorange': False},
                  'title': 'First Title'},
                  'frames': [{'data': [{'x': [1, 2], 'y': [5, 7]}]},
                             {'data': [{'x': [-1, 3], 'y': [3, 9]}]},
                             {'data': [{'x': [2, 2.6], 'y': [7, 5]}]},
                             {'data': [{'x': [1.5, 3], 'y': [7.5, 4]}]},
                             {'data': [{'x': [1, 2], 'y': [0, 1]}],
                              'layout': {'title': 'End Title'}}]}
iplot(figure_or_data)

More examples can be found at https://plot.ly/python/animations/.

  • animations now work in online mode: use plotly.plotly.create_animations and plotly.plotly.icreate_animations which animate a figure with the frames argument. Here is a simple example:
import plotly.plotly as py
from plotly.grid_objs import Grid, Column

column_1 = Column([0.5], 'x')
column_2 = Column([0.5], 'y')
column_3 = Column([1.5], 'x2')
column_4 = Column([1.5], 'y2')

grid = Grid([column_1, column_2, column_3, column_4])
py.grid_ops.upload(grid, 'ping_pong_grid', auto_open=False)

# create figure
figure = {
    'data': [
        {
            'xsrc': grid.get_column_reference('x'),
            'ysrc': grid.get_column_reference('y'),
            'mode': 'markers',
        }
    ],
    'layout': {'title': 'Ping Pong Animation',
               'xaxis': {'range': [0, 2], 'autorange': False},
               'yaxis': {'range': [0, 2], 'autorange': False},
               'updatemenus': [{
                   'buttons': [
                       {'args': [None],
                        'label': u'Play',
                        'method': u'animate'}
               ],
               'pad': {'r': 10, 't': 87},
               'showactive': False,
               'type': 'buttons'
                }]},
    'frames': [
        {
            'data': [
                {
                    'xsrc': grid.get_column_reference('x2'),
                    'ysrc': grid.get_column_reference('y2'),
                    'mode': 'markers',
                }
            ]
        },
        {
            'data': [
                {
                    'xsrc': grid.get_column_reference('x'),
                    'ysrc': grid.get_column_reference('y'),
                    'mode': 'markers',
                }
            ]
        }
    ]
}

py.create_animations(figure, 'ping_pong')

Fixed

  • Trisurf now uses correct Plotly Colorscales when called
  • Fixed a bug in the format of unique-identifiers in columns of grids that are uploaded to plotly via plotly.plotly.upload. See plotly#599 for details. In particular, creating plots that are based off of plotly grids is no longer broken. Here is an example:
import plotly.plotly as py
from plotly.grid_objs import Grid, Column

c1 = Column([6, 6, 6, 5], 'column 1')
c2 = Column(['a', 'b', 'c', 'd'], 'column 2')
g = Grid([c1, c2])

# Upload the grid
py.grid_ops.upload(g, 'my-grid', auto_open=False)

# Make a graph that with data that is referenced from that grid
trace = Scatter(xsrc=g[0], ysrc=g[1])
url = py.plot([trace], filename='my-plot')

Then, whenever you update the data in 'my-grid', the associated plot will update too. See https://plot.ly/python/data-api for more details on usage and examples.

[1.12.9] - 2016-08-22

Fixed

  • the colorbar in .create_trisurf now displays properly in offline mode.

Updated

  • the colorbar in .create_trisurf now displays the appropriate max and min values on the ends of the bar which corresponding to the coloring metric of the figure
  • edges_color is now a param in .create_trisurf which only takes rgb values at the moment

[1.12.8] - 2016-08-18

Fixed

  • Fixed color bug with trisurf plots where certain triangles were colored strangely. The coordinates of rgb(...) are now rounded to their nearest integer (using Python3 method of rounding), then placed in the color string to fix the issue.

[1.12.7] - 2016-08-17

Fixed

  • Edited plotly.min.js due to issue using iplot to plot offline in Jupyter Notebooks
    • Please note that plotly.min.js may be cached in your Jupyter Notebook. Therefore, if you continue to experience this issue after upgrading the Plotly package please open a new notebook or clear the cache to ensure the correct plotly.min.js is referenced.

[1.12.6] - 2016-08-09

Updated

  • Updated plotly.min.js from 1.14.1 to 1.16.2
    • Trace type scattermapbox is now part of the main bundle
    • Add updatemenus (aka dropdowns) layout components
    • See the plotly.js CHANGELOG for additional information regarding the updates

[1.12.5] - 2016-08-03

Updated

  • .create_trisurf now supports a visible colorbar for the trisurf plots. Check out the docs for help:
import plotly.tools as tls
help(tls.FigureFactory.create_trisurf)

[1.12.4] - 2016-07-14

Added

  • The FigureFactory can now create 2D-density charts with .create_2D_density. Check it out with:
import plotly.tools as tls
help(tls.FigureFactory.create_2D_density)

[1.12.3] - 2016-06-30

Updated

  • Updated plotly.min.js from 1.13.0 to 1.14.1
    • Numerous additions and changes where made to the mapbox layout layers attributes
    • Attribute line.color in scatter3d traces now support color scales
    • Layout shapes can now be moved and resized (except for 'path' shapes) in editable contexts
    • See the plotly.js CHANGELOG for additional information regarding the updates
  • Updated default-schema

Added

  • Added update_plotlyjs_for_offline in makefile in order to automate updating plotly.min.js for offline mode

[1.12.2] - 2016-06-20

Updated

  • Updated plotly.min.js so the offline mode is using plotly.js v1.13.0
    • Fix Plotly.toImage and Plotly.downloadImage bug specific to Chrome 51 on OSX
    • Beta version of the scattermapbox trace type - which allows users to create mapbox-gl maps using the plotly.js API. Note that scattermapbox is only available through custom bundling in this release.
    • See the plotly.js CHANGELOG for additional additions and updates.

Added

  • The FigureFactory can now create gantt charts with .create_gantt. Check it out with:
import plotly.tools as tls
help(tls.FigureFactory.create_gantt)
  • Ability to download images in offline mode. By providing an extra keyword image to the existing plot calls, you can now download the images of the plots you make in offline mode.

Fixed

  • Fixed check for the height parameter passed to _plot_html, and now sets the correct link text for plots generated in offline mode.

[1.12.1] - 2016-06-19

Added

  • The FigureFactory can now create violin plots with .create_violin. Check it out with:
import plotly.tools as tls
help(tls.FigureFactory.create_violin)

[1.12.0] - 2016-06-06

Added

  • Added ability to enable/disable SSL certificate verification for streaming. Disabling SSL certification verification requires Python v2.7.9 / v3.4.3 (or above). This feature can be toggled via the plotly_ssl_verification configuration setting.

[1.11.0] - 2016-05-27

Updated

  • Changed the default option for create_distplot in the figure factory from probability to probability density and also added the histnorm parameter to allow the user to choose between the two options. Note: This is a backwards incompatible change.

  • Updated plotly.min.js so the offline mode is using plotly.js v1.12.0

    • Light position is now configurable in surface traces
    • surface and mesh3d lighting attributes are now accompanied with comprehensive descriptions
  • Allowed create_scatterplotmatrix and create_trisurf to use divergent and categorical colormaps. The parameter palette has been replaced by colormap and use_palette has been removed. In create_scatterplotmatrix, users can now:

    • Input a list of different color types (hex, tuple, rgb) to colormap to map colors divergently
    • Use the same list to categorically group the items in the index column
    • Pass a singlton color type to colormap to color all the data with one color
    • Input a dictionary to colormap to map index values to a specific color
    • 'cat' and 'seq' are valid options for colormap_type, which specify the type of colormap being used
  • In create_trisurf, the parameter dist_func has been replaced by color_func. Users can now:

    • Input a list of different color types (hex, tuple, rgb) to colormap to map colors divergently
    • Input a list|array of hex and rgb colors to color_func to assign each simplex to a color

Added

  • Added the option to load plotly.js from a CDN by setting the parameter connected=True in the init_notebook_mode() function call
  • The FigureFactory can now create trisurf plots with .create_trisurf. Check it out with:
import plotly.tools as tls
help(tls.FigureFactory.create_trisurf)

[1.10.0] - 2016-05-19

Fixed

  • Version 1.9.13 fixed an issue in offline mode where if you ran init_notebook_mode more than once the function would skip importing (because it saw that it had already imported the library) but then accidentally clear plotly.js from the DOM. This meant that if you ran init_notebook_mode more than once, your graphs would not appear when you refreshed the page. Version 1.9.13 solved this issue by injecting plotly.js with every iplot call. While this works, it also injects the library excessively, causing notebooks to have multiple versions of plotly.js inline in the DOM, potentially making notebooks with many iplot calls very large. Version 1.10.0 brings back the requirement to call init_notebook_mode before making an iplot call. It makes init_notebook_mode idempotent: you can call it multiple times without worrying about losing your plots on refresh.

[1.9.13] - 2016-05-19

Fixed

  • Fixed issue in offline mode related to the inability to reload plotly.js on page refresh and extra init_notebook_mode calls.

[1.9.12] - 2016-05-16

Added

  • SSL support for streaming.

[1.9.11] - 2016-05-02

Added

  • The FigureFactory can now create scatter plot matrices with .create_scatterplotmatrix. Check it out with:
import plotly.tools as tls
help(tls.FigureFactory.create_scatterplotmatrix)

[1.9.10] - 2016-04-27

Updated

  • Updated plotly.min.js so the offline mode is using plotly.js v1.10.0
    • Added beta versions of two new 2D WebGL trace types: heatmapgl, contourgl
    • Added fills for scatterternary traces
    • Added configurable shapes layer positioning with the shape attribute: layer

[1.9.9] - 2016-04-15

Fixed

  • Fixed require is not defined issue when plotting offline outside of Ipython Notebooks.

[1.9.8] - 2016-04-14

Fixed

  • Error no longer results from a "Run All" cells when working in a Jupyter Notebook.

Updated

  • Updated plotly.min.js so offline is using plotly.js v1.9.0
    • Added Ternary plots with support for scatter traces (trace type scatterternary, currently only available in offline mode)
    • For comprehensive update list see the plotly.js CHANGELOG

[1.9.7] - 2016-04-04

Fixed

  • Offline mode will no longer delete the Jupyter Notebook's require, requirejs, and define variables.

Updated

  • Updated plotly.min.js so offline is using plotly.js v1.8.0
    • Added range selector functionality for cartesian plots
    • Added range slider functionality for scatter traces
    • Added custom surface color functionality
    • Added ability to subplot multiple graph types (SVG cartesian, 3D, maps, pie charts)
    • For comprehensive update list see the plotly.js CHANGELOG

[1.9.6] - 2016-02-18

Updated

  • Updated plotly.min.js so offline is using plotly.js v1.5.2

[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