The interactive graphing library for Python (includes Plotly Express) :sparkles:

Plotly

Last update: Jan 5, 2023

Related tags

Data Visualization visualization d3 python webgl dashboard interactive sparkles plotly declarative jupyter-notebook regl plotlyjs graph-library plotly-dash

Overview

plotly.py

Latest Release
User forum
PyPI Downloads
License

Data Science Workspaces

Our recommended IDE for Plotly’s Python graphing library is Dash Enterprise’s Data Science Workspaces, which has both Jupyter notebook and Python code file support.

Quickstart

pip install plotly==4.14.3

Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.5"):

import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(y=[2, 1, 4, 3]))
fig.add_trace(go.Bar(y=[1, 4, 3, 2]))
fig.update_layout(title = 'Hello Figure')
fig.show()

See the Python documentation for more examples.

Read about what's new in plotly.py v4

Overview

plotly.py is an interactive, open-source, and browser-based graphing library for Python ✨

Built on top of plotly.js, plotly.py is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more.

plotly.py is MIT Licensed. Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud.

Installation

plotly.py may be installed using pip...

pip install plotly==4.14.3

or conda.

conda install -c plotly plotly=4.14.3

Jupyter Notebook Support

For use in the Jupyter Notebook, install the notebook and ipywidgets packages using pip:

pip install "notebook>=5.3" "ipywidgets>=7.5"

or conda:

conda install "notebook>=5.3" "ipywidgets>=7.5"

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install jupyterlab "ipywidgets>=7.5"

or conda:

conda install jupyterlab "ipywidgets>=7.5"

Then run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# Basic JupyterLab renderer support
jupyter labextension install [email protected]

# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager [email protected]

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.

Static Image Export

plotly.py supports static image export, using either the kaleido package (recommended, supported as of plotly version 4.9) or the orca command line utility (legacy as of plotly version 4.9).

Kaleido

The kaleido package has no dependencies and can be installed using pip...

$ pip install -U kaleido

or conda.

$ conda install -c conda-forge python-kaleido

Orca

While Kaleido is now the recommended image export approach because it is easier to install and more widely compatible, static image export can also be supported by the legacy orca command line utility and the psutil Python package.

These dependencies can both be installed using conda:

conda install -c plotly plotly-orca==1.3.1 psutil

Or, psutil can be installed using pip...

pip install psutil

and orca can be installed according to the instructions in the orca README.

Extended Geo Support

Some plotly.py features rely on fairly large geographic shape files. The county choropleth figure factory is one such example. These shape files are distributed as a separate plotly-geo package. This package can be installed using pip...

pip install plotly-geo==1.0.0

or conda

conda install -c plotly plotly-geo=1.0.0

Chart Studio support

The chart-studio package can be used to upload plotly figures to Plotly's Chart Studio Cloud or On-Prem service. This package can be installed using pip...

pip install chart-studio==1.1.0

or conda

conda install -c plotly chart-studio=1.1.0

Migration

If you're migrating from plotly.py v3 to v4, please check out the Version 4 migration guide

If you're migrating from plotly.py v2 to v3, please check out the Version 3 migration guide

Copyright and Licenses

Code released under the MIT license.

Docs released under the Creative Commons license.

Comments

[WIP] Plotly 3.0.0 - Deep Jupyter Integration, Validation, Performance, and More
Update: June 27, 2018

This branch will mark a major release of the plotly.py branch, Version 3.0.0 There are many new and great features in this branch including deeper Jupyter integration, deeper figure validation, improved performance, and more. You can try this out with a prerelease version, see https://pypi.org/project/plotly/#history for the latest. To install and enable with Jupyter, run:

pip install plotly==3.0.0rc11 pip install "notebook>=5.3" "ipywidgets>=7.2" # only necessary for Jupyter Notebook environments

If you're using older versions of notebook or ipywidgets you may need to manually activate the widget extensions (this should not be needed for notebook>=5.3 and ipywidgets>=7.2)

jupyter nbextension enable --py widgetsnbextension --sys-prefix jupyter nbextension enable --py plotlywidget --sys-prefix

In addition, to add JupyterLab support run the following commands:

pip install jupyterlab jupyter labextension install @jupyter-widgets/jupyterlab-manager # install the Jupyter widgets extension jupyter labextension install [email protected]

The original message from February 19, 2018 is below:

Alright, here we go! @chriddyp @jackparmer

Overview This is a first cut at integrating the work I started in the ipyplotly project into plotly.py.

Integration Approach I moved the new object hierarchy to plotly/datatypes. I modified the graph_objs.py code generation logic to remap Figure, Layout, and all of the trace objects (Bar, Scatter, etc.) to the corresponding objects in the new datatypes hierarchy. All of the other classes in graph_objs were converted into list or dict subclasses. This is simply for backwards compatibility for the time being, I'm not sure what we want to do with these in the long run.

Widget notes The backend ipywidget logic is implemented in the new datatypes.Figure and datatypes.FigureWidget classes. The front-end logic is implemented in the js/ directory.

Examples See the notebooks in specs/ipyplotly_integration for an overview of the new functionality.

TODO

[x] Support dict-style .update method on all datatypes

[x] Assess existing tests and catalog breakage

[x] Python 2.7 support

[x] JupyterLab support

[x] Update README with some examples from Overview.ipynb

[x] Reformat for 79 character width (plus PEP8 in general)

Failing test modes Summary of reasons for current test failures

unexpected keyword argument '_raise' (test_get_figure). Looks like old graph objects had a _raise constructor parameter to control whether validation was performed. I'm not sure why this was needed, but validation isn't optional for the new objects.

Validation exceptions not raised on compatibility classes. Some of the current graph_objs.py classes don't directly map to objects in the new hierarchy, and they are currently included as dict/list subclasses for source compatibility. e.g.

Sequence types like Annotations don't have an equivalent because sequences are now represented as tuples of compound types. For instance, the annotations property of Layout accepts tuples of datatypes.layout.Annotation objects and there is no Annotations type.

Types like Marker, ColorBar, ErrorX, Font, Line, Frames, etc. are replaced by more precise types. For example, there is now a trace.scatter.Marker class and a trace.bar.Marker class and they each contain only the properties that are valid for their trace type.

New datatype objects don't have a validate() method

Subplot properties may only be suffixed by an integer > 1. See https://github.com/plotly/plotly.py/pull/956#issuecomment-371340640 for some comments. The documentation and schema of Plotly.js seem to disallow subplotid properties ending in 1. (x, x2, x3, but not x1).

There is no get_data method on datatype objects. This had a flatten option to return a dict with keys like foo.bar.baz. I think this could be implemented on the new objects if there's a need for.

Errors in test_graph_objs.py because the collection of classes in graph_objs.py has changed.

Datatypes are no longer dict subclasses so tests like assert Scatter() == dict(type='scatter') fail.

Exception types don't always match: The current datatype/validator logic mostly raises ValueError and KeyError exceptions. Many of the tests expect a PlotlyError.

There is no strip_style method on datatypes. The new logic doesn't maintain the style meta-data after code generation, but it would be possible to add this if this method needs to be preserved.

Datatypes have no to_string method, but again this could be added.

Invalid value of type 'plotly.grid_objs.grid_objs.Column' received for the 'xsrc' property of trace.scatter: grid_objs aren't accepted as *src properties

Scalar values aren't currently accepted as data_array types (e.g. scatter.x). This breaks some of the streaming tests which have things like my_stream.write(Scatter(x=1, y=10), ...)

It's not valid to pass a dictionary of object properties to the constructor of a data type without kwarg expansion. Scatter({'x': ..., 'y': ...}) is invalid, need to do Scatter(**{'x': ..., 'y': ...}). This breaks the tools.py/validate function.

The layout.width/height properties are numbers (according to the schema), but the dendrogram figure_factory sets height to the string '100%'.

All data_array typed properties are converted to read-only numpy arrays internally. So comparisons that expect lists fail (see TestStreamline/test_simple_streamline)

flaglist/enumeration types are case sensitive. Causes failure in TestTrisurf/test_trisurf_all_args because hoverinfo is set to 'None' rather than 'none'

'Figure' object has no attribute 'to_dataframe': I'm not really clear on what this method is supposed to do in general.

'dot' is in invalid marker type (according to the schema). Used in test_optional/test_matplotlylib/data/scatter.py/SIMPLE_SCATTER

AttributeError: module 'plotly.graph_objs.graph_objs' has no attribute 'Histogram2dcontour': It's Histogram2dContour. We could support both versions if we need to.

There are a buch of JSON encoding failure that seem to relate to date encoding.

Summary Missing methods on datatypes

to_string [removing]

strip_style [removing]

get_data [removing]

validate [removing]

to_dataframe [removing]

Next steps

[x] Support strict flag in string validator (see plotly/plotly.js#2523).

[x] Remove hard numpy dependency. Support storing data_arrays as lists internally, but convert to tuples on property access.

[x] Investigate improving import performance and reenabling recursive submodule imports.

[x] add optional row/col support to add_traces. Deprecate append_traces and remap to add_traces with row/col args.

[x] Make ipywidgets an optional dependency, only loaded when FigureWidget constructor is called.

[x] Remove all use of deprecated classes in figure_factory, matplotlylib, etc.

[x] tests

[x] the actual modules users call

enhancement breaking change jupyter
opened by jonmmease 153
Revamp tls.get_subplots
@theengineear @chriddyp

tls.get_subplots is in need of some revamping.

More info in this Asana task.

This NB shows off the new features.

Features wishlist:

[x] Generate more complicated subplot arrangements e.g https://plot.ly/~etpinard/245

[x] Assign shared axes

[x] Set irregular horizontal and vertical spacing in-between subplots

[x] Generate subscenes - subaxes subplot grid.

[x] Generate insets with ease

API issue to resolve:

[x] rowspan > 1 and is_empty https://github.com/plotly/python-api/pull/170#discussion_r22334996

Solution: Enforce specs to have dimensions (rows, columns). Use None to fill in cells over row / column spans.

[x] Ordering of the specs keyword argument https://github.com/plotly/python-api/pull/170#issuecomment-68561185
opened by etpinard 66
Refactor JupyterLab JS extensions and package as federated extension
This PR:

[x] merges the widget and the jupyterlab render extensions into one unique package (an example out there is https://github.com/deathbeds/ipydrawio/blob/master/packages/ipydrawio).

[x] packages the jupyterlab extension as federated module (fixes #3036)

[x] import asynchronously plotly.js

[x] I have read through the contributing notes and understand the structure of the package. In particular, if my PR modifies code of plotly.graph_objects, my modifications concern the codegen files and not generated files.

[x] I have added tests (if submitting a new feature or correcting a bug) or modified existing tests.

[x] For a new feature, I have added documentation examples in an existing or new tutorial notebook (please see the doc checklist as well).

[ ] I have added a CHANGELOG entry if fixing/changing/adding anything substantial.

[x] For a new feature or a change in behaviour, I have updated the relevant docstrings in the code to describe the feature or behaviour (please see the doc checklist as well).
opened by fcollonval 55
Updated method for ternary contour figure factory

Following the suggestions in #1413, and help from @empet, here is an alternative version for implementing contour plots in ternary diagrams.

Pros: this method uses a ScatterTernary trace, meaning that it is natively an object of a ternary plot, hence it uses the ternary pan/zoom. Cons: the trace is not a Contour trace, hence quite a lot of boilerplate code will be needed for handling colorscale, colorbar, etc.

I post here a first proof of concept, the PR is far from being finished (TODO: fix tests, fix documentation, implement annotations better etc.).

@empet: I haven't had the time yet to compare this method with yours using ILR transform, but I'll surely do!

opened by emmanuelle 49
Adding Scatterplot Matrix to FigureFactory
@cldougl

This is the first PR for the Scatterplot Matrix in the FigureFactory class in tools.py. The function currently takes in only pandas dataframes, does sanity checks on the dataframe (more than one column, either strings or numbers within a column, etc.) and then builds a scatterplot matrix based on this input. There is an option for indexing by one of the columns which must be inputted by the user (parameter: index) and for either a scatterplot or histogram along the main diagonal (parameter: diagonal).

Things I am working on implementing:

I want to integrate a jitter parameter that adds random noise to the scatterplot so that densities can be easily seen in a plot. I already have a jitter parameter, but it only works in certain places.

I also am working to add to more options for diagonal plots, such as a 2d density and box plot.

Adding more parameters and options to the scatterplot (eg. showgrid) is also another thing I am working on expanding.
opened by Kully 44
Update graph reference
Alright, the real deal!

TODO:

[x] add back deprecation warnings with _deprecated

[x] ~~use hrName~~

[x] wait, don't use hrname :) (it adds unnecessary maintenance overhead)

[x] use _isSubplotObj

[x] stop hard coding meta keys

[x] skipped tests need attached GH issues

[x] :tiger2: for graph_objs_tools.py

[x] discuss #291 (copy stuff), #290 (key ordering), #289 (pretty help), #293 (schema as singleton)

[x] :dolls: need a final revisit

[x] fix up some test code that uses deprecated keys

[x] incorporate new deprecated role definitions

[x] ~~use descriptions from deprecated fields in warnings~~ i'm now pointing users to call help appropriately. i think this is good enough.

[ ] gotta make sure this doesn't break anything in cufflinks

[x] don't add new class definitions (only for traces)
opened by theengineear 44
Sparklines Figure Factory
@jackparmer progress so far

you can set column_widths (like in go.Table) with a list [1, 4, 2, ...] you set the chart types with a list: i.e. the one above is produced with chart_types=['name', 'bullet', 'line', 'avg', 'bar']

# TODO: # add more color variety # add tests

any suggestions?
opened by Kully 42
Jupyterlab 3.x.x support
With a fresh install of Jupyterlab version 3.0.0, installing plotly with the command jupyter labextension install [email protected] yields an error:

An error occured. ValueError: "[email protected]" is not compatible with the current JupyterLab Conflicting Dependencies: JupyterLab Extension Package >=3.0.0 <3.1.0 >=1.3.0 <2.0.0||>=2.0.0 <3.0.0@jupyterlab/rendermime-interfaces

Obviously this is a bleeding edge issue and very much a feature request, not a bug, I just wanted to make sure it was documented. Thank you!
opened by bdecato 41
Offline mode not displaying inline in Jupyter notebook master?
I hadn't tested recently, but today, using master of the Jupyter notebook, I can't get offline plots to display inline, instead I get the external temporary file. Consider this simple test:

from plotly import __version__ from plotly.offline import init_notebook_mode, plot from plotly.graph_objs import Scatter init_notebook_mode() print("plotly version:", __version__) plot([Scatter(x=[1, 2, 3], y=[3, 1, 6])])

I get for output:

plotly version: 1.9.10 Out[1]: 'file:///Users/fperez/tmp/temp-plot.html'

and the plot correctly opening in a new tab by itself, but no inline notebook output. Here's a screenshot for reference:

In the JS console, I don't see anything that immediately points to the problem. Here's a screenshot, b/c copy-pasting text from the JS console makes a mish-mash of the formatting:

The above were from current Chrome on OSX, but I replicated the problem on Safari.

Any thoughts on how to proceed much appreciated. Thanks!
opened by fperez 41
Import and initialization optimizations
Overview

This PR contains a variety of optimizations targeted and improving plotly.py's import and Figure creation/serialization speed.

Lazy submodule imports in Python 3.7+

PEP-562 in Python 3.7 introduced a nice approach for implementing lazy loading of submodules. The top-level plotly/__init__.py, plotly/io/__init__.py and the full graph_objs hierarchy have been updated to use lazy submodule importing for Python 3.7+. For older Python versions, all submodule imports are still performed immediately.

Part of this process involved codegen updates to split graph object and validator classes into their own files.

Lazy creation of validators

Previously, each graph object would instantiate a set of validators (one per property) in the constructor. Now, validators are constructed when first used, and they are stored in a global cache (plotly/validator_cache.py)

Lazy creation of child graph objects

Previously, child graph objects were created in the constructor, and they were initialized for every possible property. Now, graph objects initialized either on property access or when the property is set to a non-None value (if validation is enabled, see below).

Avoid loading numpy and pandas when not in use

In several places in the codebase, we attempt to import numpy/pandas using our get_module function, and then use the pandas/numpy module handle to check whether an argument is a data structure from that library. The get_module function now has a should_load option. When set to False, get_module will only return the module if it is already loaded. This is useful because if pandas isn't loaded, then we don't need to check whether a value is a DataFrame. This keeps us from having to pay the pandas/numpy import cost when these libraries are installed but not in use. This saves ~200ms when pandas/numpy are installed but not in use.

Avoid dynamic docstring generation

This PR removes the dynamic docstring generation that was used to populate the docstrings for the Figure methods corresponding to plotly.io functions (e.g. Figure.show with created by transforming plotly.io.show). These docstrings were added statically. This saves ~200ms on import time.

Support optional validation

This PR adds support for disabling property validation using the go.validation object. This can be used as a callable to enable/disable validation for the session (e.g. go.validation(False)), or it can be used as a context manager to enable/disable validation within block of code (e.g. with go.validation(False):).

API inspired by Bokeh's implementation in https://github.com/bokeh/bokeh/issues/6042.

Results

Here are some before/after performance results on Python 3.7 with this PR:

top-level import

%%time import plotly

Version 4.6: 239 ms PR: 2.5ms 95x speedup

Import, create empty figure, and serialize to JSON

%%time import plotly.graph_objects as go go.Figure().to_json()

Version 4.6: 696 ms PR: 27ms 25x speedup

Repeatedly create empty figure and serialize to json (after import)

%%timeit go.Figure().to_json()

Version 4.6: 68 ms PR: 1.5ms 45x speedup

Import, load data, create animated plotly express figure, serialize to json

%%time import plotly.express as px df = px.data.gapminder() fig = px.scatter(df, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country", size="pop", color="continent", hover_name="country", facet_col="continent", log_x=True, size_max=45, range_x=[100,100000], range_y=[25,90]) fig.to_json()

Version 4.6: 1530 ms PR: 550 ms 2.7x speedup

Repeatedly create px plot after import and data are loaded

%%timeit fig = px.scatter(df, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country", size="pop", color="continent", hover_name="country", facet_col="continent", log_x=True, size_max=45, range_x=[100,100000], range_y=[25,90]) fig.to_json()

Version 4.6: 663 ms PR: 167 ms 4x speedup

Import, load data, create animated plotly express figure, serialize to json, skip validation

%%time import plotly.express as px import plotly.graph_objects as go df = px.data.gapminder() with go.validate(False): fig = px.scatter(df, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country", size="pop", color="continent", hover_name="country", facet_col="continent", log_x=True, size_max=45, range_x=[100,100000], range_y=[25,90]) fig.to_json()

PR (no validation): 449 ms PR (with validation): 550 ms Version 4.6: 1530 ms

Repeatedly import, load data, create animated plotly express figure, serialize to json, skip validation

%%timeit with go.validate(False): fig = px.scatter(df, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country", size="pop", color="continent", hover_name="country", facet_col="continent", log_x=True, size_max=45, range_x=[100,100000], range_y=[25,90])

PR (no validation): 127ms PR (with validation): 167ms Version 4.6: 663 ms

cc @nicolaskruchten @emmanuelle
opened by jonmmease 39
add_shape, add_layout_image, add_annotation for multiple facets at once, add_hline and add_vline (+add_vrect/add_hrect)
Closes #2141 and closes #2140

Making it possible to specify multiple rows and columns when using add_shape, add_layout_image or add_annotation. This pull request is to share the work, so a lot is missing still.

Code PR

[x] I have read through the contributing notes and understand the structure of the package. In particular, if my PR modifies code of plotly.graph_objects, my modifications concern the codegen files and not generated files.

[ ] I have added tests (if submitting a new feature or correcting a bug) or modified existing tests.

[ ] For a new feature, I have added documentation examples in an existing or new tutorial notebook (please see the doc checklist as well).

[ ] I have added a CHANGELOG entry if fixing/changing/adding anything substantial.
opened by nicholas-esterer 38
Bump json5 from 1.0.1 to 1.0.2 in /packages/javascript/jupyterlab-plotly
Bumps json5 from 1.0.1 to 1.0.2.

Release notes

Sourced from json5's releases.

v1.0.2

Fix: Properties with the name __proto__ are added to objects and arrays. (#199) This also fixes a prototype pollution vulnerability reported by Jonathan Gregson! (#295). This has been backported to v1. (#298)

Changelog

Sourced from json5's changelog.

Unreleased [code, diff]

v2.2.3 [code, diff]

Fix: [email protected] is now the 'latest' release according to npm instead of v1.0.2. (#299)

v2.2.2 [code, diff]

Fix: Properties with the name __proto__ are added to objects and arrays. (#199) This also fixes a prototype pollution vulnerability reported by Jonathan Gregson! (#295).

v2.2.1 [code, diff]

Fix: Removed dependence on minimist to patch CVE-2021-44906. (#266)

v2.2.0 [code, diff]

New: Accurate and documented TypeScript declarations are now included. There is no need to install @types/json5. (#236, #244)

v2.1.3 [code, diff]

Fix: An out of memory bug when parsing numbers has been fixed. (#228, #229)

v2.1.2 [code, diff]

... (truncated)

Commits

a62db1e 1.0.2

e0c23fe docs: update CHANGELOG for v1.0.2

62a6540 fix: add proto to objects and arrays

See full diff in compare view

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dependencies javascript
opened by dependabot[bot] 0
Can the points be shown inside of the violin area?
One of my favorite types of plots to show distributions is to use Sina plots where the points are spread out within the area of the violin representing the density of the distribution. I then additionally overlay this with a boxplot as is already possible in plotly. So my questions/feature requests are then:

Can the points of a violin plot be shown inside of the violin rather than next to it?

Is it possible to have the points be spread out to the width of the violin as in the Sina plots?

Thank you for your consideration.
opened by Midnighter 0

Bug using the underscore notation for annotation attributes, coupled with buttons

Hi, I just had trouble with the following example:

fig.update_layout(
            updatemenus=[
                dict(
                    type="buttons",
                    buttons=[
                        dict(
                            label="All",
                            method="update",
                            args=[
                                {"visible": [True] * 9},  # show all traces
                                {
                                    "annotations": [inner_annotation]
                                },
                            ],
                        ),
                    ],
                )
            ]
        )

Everything works fine on the figure load, however, clicking on the button would change the font_size of my annotation back to default, whereas I set it on 16.

inner_annotation = dict(
            ...
           font_size=16,
        )

After some tests I figured out changing the syntax to

inner_annotation = dict(
            ...
           font={"size": 16},
        )

resolved the issue.

opened by sde-cdsp 0

Allow setting the camera "field of view"

It doesn't seem possible to set the 3D camera field of view (fov).

(Re: my post to Stackoverflow.)

Looking at the source code, I see that:

In https://github.com/plotly/plotly.js/blob/master/src/plots/gl3d/scene.js, it uses glPlot3d.createScene and sets the options in proto.prepareOptions.

In https://github.com/gl-vis/gl-plot3d/blob/master/scene.js#L179, the allowed options include the field-of-view parameter fovy (field-of-view in the vertical direction), which defaults to Math.PI/4 (45 degrees).

For 3D graphics, a 45-degree vertical field-of-view typically gives an exaggerated perspective. It corresponds to about a 28mm camera lens.

It would be nice for plotly.graph_objects.layout.scene.Camera to include a fovy parameter (in radians).

opened by hhoppe 0
languages RTL direction issue fig.write_image "jpeg"

The issue with export chart to jpeg in languages right to left direction (arbic -hebrew -urdu) ,when using command "fig.write_image".

to export to .html no issue and all brackets are ok but to export to image jpg the brackets are missed up.

opened by iMuaad 0

Releases(v5.11.0)

v5.11.0(Oct 27, 2022)
Updated

Updated Plotly.js to from version 2.14.0 to version 2.16.1. See the plotly.js CHANGELOG for more information. Notable changes include:

Add clustering options to scattermapbox [#5827], with thanks to @elben10 for the contribution!

Add bounds to mapbox suplots [6339]

Add angle, angleref and standoff to marker and add backoff to line; also introduce new arrow symbols to facilitate drawing networks [#6297]

Add minreducedwidth and minreducedheight to layout for increasing control over automargin [#6307]

Add entrywidth and entrywidthmode to legend [#6202, #6324]

Source code(tar.gz)
Source code(zip)
v5.10.0(Aug 11, 2022)
Updated

Updated Plotly.js to from version 2.12.1 to version 2.14.0. See the plotly.js CHANGELOG for more information. Notable changes include:

Add support for sankey links with arrows

Add selections, newselection and activeselection layout attributes to have persistent and editable selections over cartesian subplots

Add unselected.line.color and unselected.line.opacity options to parcoords trace

Display Plotly's new logo in the modebar

Source code(tar.gz)
Source code(zip)
v5.9.0(Jun 24, 2022)
Added

pattern_shape options now available in px.timeline() #3774

facet_* and category_orders now available in px.pie() #3775

Performance

px methods no longer call groupby on the input dataframe when the result would be a single group, and no longer groups by a lambda, for significant speedups #3765 with thanks to @jvdd

Updated

Allow non-string extras in flaglist attributes, to support upcoming changes to ax.automargin in plotly.js plotly.js#6193, #3749

Source code(tar.gz)
Source code(zip)
v5.8.2(Jun 10, 2022)
Fixed

Fixed a syntax error that caused rendering issues in Databricks notebooks and likely elsewhere. #3763 with thanks to @fwetdb

Source code(tar.gz)
Source code(zip)
v5.8.1(Jun 8, 2022)

(no changes in this release due a build-process error, please see https://github.com/plotly/plotly.py/releases/tag/v5.8.2 for the changes that were initially reported to be in this build)
Source code(tar.gz)
Source code(zip)
v5.8.0(May 11, 2022)
See the full release announcement on the forum at https://community.plotly.com/t/announcing-plotly-py-5-8-0-better-autocompletions-with-type-hints-minor-ticks/64002 !

Fixed

Improve support for type checking and IDE auto-completion by bypassing lazy-loading when type checking. #3425 with thanks to @JP-Ellis

line dash-style validators are now correctly used everywhere so that values like 10px 2px are accepted #3722

Resolved various deprecation warning messages and compatibility issues with upstream dependencies and Python 3.11, plus removed dependency on six, with thanks to @maresb, @hugovk, @tirkarthi, @martinRenou, and @BjoernLudwigPTB

Better support for MathJax 3 #3706

Added

Type annotations for Plotly Express functions and chainable go.Figure methods, for better IDE auto-completion #3708

Updated

Updated Plotly.js to from version 2.11.1 to version 2.12.1. See the plotly.js CHANGELOG for more information. Notable changes include:

Add minor ticks to cartesian axes

Add griddash option to most axes

Source code(tar.gz)
Source code(zip)
v5.7.0(Apr 5, 2022)
See the full release announcement here: https://community.plotly.com/t/announcing-plotly-py-5-7-0-text-on-histograms-and-heatmaps-patterns-on-areas-plotly-js-version-number-access-smith-charts/62735

Added

added pattern_shape options to px.area() #3668

Updated

Updated Plotly.js to from version 2.9.0 to version 2.11.1. See the plotly.js CHANGELOG for more information. Notable changes include:

Add fillpattern options to scatter trace

Various JS-specific improvements such as MathJax 3.0 support

Source code(tar.gz)
Source code(zip)
v5.6.0(Feb 9, 2022)
Updated

Updated Plotly.js to from version 2.8.3 to version 2.9.0. See the plotly.js CHANGELOG for more information. Notable changes include:

Implement ticklabelstep to reduce labels on cartesian axes and colorbars

Display the version of plotly.js when hovering over the modebar

Source code(tar.gz)
Source code(zip)
v5.5.0(Dec 21, 2021)
Added

text_auto argument to px.bar, px.histogram, px.density_heatmap, px.imshow #3518

Deprecated ff.create_annotated_heatmap, ff.create_county_choropleth, ff.create_gantt #3518

div_id argument to pio.to_html, pio.write_html, fig.to_html and fig.write_html to optionally make its IDs deterministic #3487 with thanks to @Skn0tt

Fixed

Fixed ValueError when ff.create_annotated_heatmap passes rgba() colors into to_rgb_color_list #3478 with thanks to @janosh

Updated

Updated Plotly.js to from version 2.6.3 to version 2.8.3. See the plotly.js CHANGELOG for more information. Notable changes include:

Horizontal color bars

texttemplate for histogram-like and heatmap-like traces

Source code(tar.gz)
Source code(zip)
v5.4.0(Nov 15, 2021)
Fixed

Fixed error when serializing dict with mix of string and non-string keys #3380

Updated

The JSON serialization engines no longer sort their keys #3380

Updated Plotly.js to from version 2.4.2 to version 2.6.3. See the plotly.js CHANGELOG for more information. Notable changes include:

New subplot type smith that supports scattersmith trace types for visualizing data in the complex domain

Changes to Plotly.js packaging

Source code(tar.gz)
Source code(zip)
v5.3.1(Sep 1, 2021)
Updated

Updated Plotly.js to from version 2.4.1 to version 2.4.2. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

Bug fix for rendering unified hover labels in classic Jupyter Notebooks

Source code(tar.gz)
Source code(zip)
v5.3.0(Aug 30, 2021)
Updated Plotly.js to from version 2.3.1 to version 2.4.1. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

Added legend.groupclick options

Provide bbox of hover items in event data

Source code(tar.gz)
Source code(zip)
v5.2.2(Aug 23, 2021)
Fixed

Fixed error when using the orjson engine with non-string keys #3351

Source code(tar.gz)
Source code(zip)
v5.2.1(Aug 14, 2021)
See the full release announcement here: https://community.plotly.com/t/announcing-plotly-py-5-2-1-trendlines-ecdf-plots-markers-on-lines-sharper-webgl-legend-group-titles/55681

Updated

Updated Plotly.js to from version 2.2.0 to version 2.3.1. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

new projections in geo subplots from a more recent version of d3-geo

new number-formatting directives from a more recent version of d3-format

Improve rendering of scattergl, splom and parcoords by implementing plotGlPixelRatio for those traces

performance improvements and bug fixes

Added

Extra flags were added to the gapminder and stocks dataset to facilitate testing, documentation and demos #3305

All line-like Plotly Express functions now accept markers argument to display markers, and all but line_mapbox accept symbol to map a field to the symbol attribute, similar to scatter-like functions #3326

px.scatter and px.density_contours now support new trendline types 'rolling', 'expanding' and 'ewm' #2997

px.scatter and px.density_contours now support new trendline_options argument to parameterize trendlines, with support for constant control and log-scaling in 'ols' and specification of the fraction used for 'lowess', as well as pass-through to Pandas for 'rolling', 'expanding' and 'ewm' #2997

px.scatter and px.density_contours now support new trendline_scope argument that accepts the value 'overall' to request a single trendline for all traces, including across facets and animation frames #2997

A new px.ecdf() function for Empirical Cumulative Distribution Functions #3330

Fixed

Fixed regression introduced in version 5.0.0 where pandas/numpy arrays with dtype of Object were being converted to list values when added to a Figure (#3292, #3293)

Better detection of Chrome and Chromium browsers in the Renderers framework, especially on Linux (#3278) with thanks to @c-chaitanya for the contribution

Source code(tar.gz)
Source code(zip)
v5.1.0(Jun 28, 2021)
Updated Plotly.js from version 2.1.0 to version 2.2.0. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

new <trace>.legendgrouptitle attribute for legend group titles

new %h text formatting directive for half-years

performance improvements and bug fixes

Source code(tar.gz)
Source code(zip)
v5.0.0(Jun 21, 2021)
See the full release announcement here: https://community.plotly.com/t/introducing-plotly-py-5-0-0-a-new-federated-jupyter-extension-icicle-charts-and-bar-chart-patterns/54039

Updated/Changed

Items in this section may be considered backwards-incompatible changes for the purposes of Semantic Versioning but we expect the vast majority of users to be able to upgrade to version 5.0 without encountering any issues.

Dropped support for Python older than 3.6 #3160

Updated Plotly.js to from version 1.58.4 to version 2.1.0. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

dropped support for IE9 and IE10

dropped support for long-deprecated graph_objects like area traces and scatter.(t|r) and layout.(radial|angular)axis attributes

modebar no longer has hovermode or spikeline buttons by default (can be added back with fig.update_layout(modebar_add=["v1hovermode", "toggleSpikeLines"]))

"Aa" text no longer appears on legend items unless mode="text"

In bar traces, textposition now defaults to "auto"

Font size for legend and colorbar titles now matches axis title font size (slightly bigger)

deprecated heatmapgl, pointcloud traces as well as all transform attributes

Combined plotlywidget into jupyterlab-plotly and packaged them as a federated extension #3142 with massive thanks to @fcollonval for the contribution

In addition to this change, large Plotly.js bundles are now lazily loaded on-demand by JupyterLab

Plotly.js CDN url will now be versioned by default for HTML exports using include_plotlyjs='cdn' and for "connected" renderers. #2961 with thanks to @adehad for the contribution

Recommending Kaleido by default over Orca #3094

Replaced retrying dependency with tenacity #2911 with thanks to @jmsmdy for the contribution

Plotly Express now always takes into account every value in category_orders when computing discrete mappings (color, symbol, line-dash, pattern-shapes) as well as facets, even those values which are absent in the data #3247

Added

Additions due to bumping Plotly.js from 1.58.4 to 2.1.0 (see changelog):

New icicle trace type, with thanks to @Kully and @mtwichan of Zyphr for their contribution!

New marker.pattern options for bar-like trace types with thanks to @s417-lama for the contribution!

New legendrank attribute to control rank of traces within legends

Plotly Express' px.bar(), px.histogram() and px.bar_polar() now support the pattern_shape argument #3252

New Plotly Express px.icicle() function, with thanks to @Kully and @mtwichan of Zyphr for their contribution! #3256

New functions in plotly.colors: get_colorscale() and sample_colorscale() #3136 and #3186 with thanks to @CarlAndersson for the contributions

Faster JSON encoding when orjson is present #2955

Fixed

Pandas and Numpy datetime serialization fixes #3022

Fixed selected points of histograms in FigureWidget #2771 with thanks to @meffmadd for the contribution

Static image export now honors layout.(width|height)#3240

Improvements to "matplotlylib" conversion utility in plotly.tools.mpl_to_plotly() with thanks to @fdion #3143

Source code(tar.gz)
Source code(zip)
v5.0.0rc2(Jun 7, 2021)
Find out more about the RC process on our Forum: https://community.plotly.com/t/plotly-py-5-0-is-coming-soon-try-the-release-candidate-today/53470

Updated

Updated Plotly.js to version 2.0.0. See the plotly.js 2.0.0 CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

new marker.pattern options for bar-like trace types

dropped support for IE9 and IE10

dropped support for long-deprecated graph_objects like area traces and scatter.(t|r) and layout.(radial|angular)axis attributes

deprecated heatmapgl, pointcloud traces as well as all transform attributes

Combined plotlywidget into jupyterlab-plotly and packaged them as a federated extension #3142 with massive thanks to @fcollonval for the contribution

Plotly.js CDN url will now be versioned by default for HTML exports using include_plotlyjs='cdn' and for "connected" renderers. #2961 with thanks to @adehad for the contribution

Dropped support for Python older than 3.6 #3160

Recommending Kaleido by default over Orca #3094

Replaced retrying dependency with tenacity #2911 with thanks to @jmsmdy for the contribution

Added

New functions in plotly.colors: get_colorscale() and sample_colorscale() #3136 and #3186 with thanks to @CarlAndersson for the contributions

Faster JSON encoding when orjson is present #2955

Fixed

Pandas and Numpy datetime serialization fixes #3022

Fixed selected points of histograms in FigureWidget #2771 with thanks to @meffmadd for the contribution

Source code(tar.gz)
Source code(zip)
v5.0.0rc1(Jun 7, 2021)
Find out more about the RC process on our Forum: https://community.plotly.com/t/plotly-py-5-0-is-coming-soon-try-the-release-candidate-today/53470

Updated

Updated Plotly.js to version 2.0.0-rc.2. See the plotly.js 2.0.0 CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

new marker.pattern options for bar-like trace types

dropped support for IE9 and IE10

dropped support for long-deprecated graph_objects like area traces and scatter.(t|r) and layout.(radial|angular)axis attributes

deprecated heatmapgl, pointcloud traces as well as all transform attributes

Combined plotlywidget into jupyterlab-plotly and packaged them as a federated extension #3142 with massive thanks to @fcollonval for the contribution

Plotly.js CDN url will now be versioned by default for HTML exports using include_plotlyjs='cdn' and for "connected" renderers. #2961 with thanks to @adehad for the contribution

Dropped support for Python older than 3.6 #3160

Recommending Kaleido by default over Orca #3094

Replaced retrying dependency with tenacity #2911 with thanks to @jmsmdy for the contribution

Added

New functions in plotly.colors: get_colorscale() and sample_colorscale() #3136 and #3186 with thanks to @CarlAndersson for the contributions

Faster JSON encoding when orjson is present #2955

Fixed

Pandas and Numpy datetime serialization fixes #3022

Fixed selected points of histograms in FigureWidget #2771 with thanks to @meffmadd for the contribution

Source code(tar.gz)
Source code(zip)
v4.14.3(Jan 12, 2021)
px.timeline() now allows hover_data formatting of start and end times 3018

Small change to packaging of plotlywidget extension for JupyterLab 3 3021

Source code(tar.gz)
Source code(zip)
v4.14.2(Jan 11, 2021)
Updated

JupyterLab extensions now compatible with JupyterLab 3.x 3016

Updated Plotly.js to version 1.58.4. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

fixes for rendering 3d plots on recent Safari versions

fixes to inside ticklabels

regression fixes

Fixed

px.histogram() Y-axis labels now take into account histnorm and barnorm 2989

px.histogram() marginal and facet_* now work correctly together 3014

Source code(tar.gz)
Source code(zip)
v4.14.1(Dec 9, 2020)
See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-14-faceted-and-animated-images-and-heatmaps-inside-tick-labels-better-axis-type-detection/48079

Updated

Updated Plotly.js to version 1.58.2. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

fixes for new ticklabelposition attribute

fixes for a regression related to treemaps in the previous version

Source code(tar.gz)
Source code(zip)
v4.14.0(Dec 7, 2020)
See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-14-faceted-and-animated-images-and-heatmaps-inside-tick-labels-better-axis-type-detection/48079

Added

px.imshow now supports facet_col and animation_frame arguments for visualizing 3-d and 4-d images 2746

px.defaults now supports color_discrete_map, symbol_map, line_dash_map, labels and category_orders as well as a .reset() method 2957

Fixed

axes will now auto-type numeric strings as categorical data rather than linear in the default templates 2951

Updated

Updated Plotly.js to version 1.58.1. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:

a new ticklabelposition attribute to enable positioning tick labels inside the plotting area

better support for scaleanchor and matches on cartesian axes for matched square subplots

a new autotypenumbers attribute which is now set to strict in the default templates

various fixes relating to automargins for small figures

Source code(tar.gz)
Source code(zip)
v4.13.0(Nov 23, 2020)
See the fully release announcement at https://community.plotly.com/t/announcing-plotly-py-4-13-magical-error-messages-and-documentation-plus-speedups-and-faceted-maps/47497

Added

px.choropleth, px.scatter_geo and px.line_geo now support faceting as well as fitbounds and basemap_visible 2923

px.scatter_geo and px.line_geo now support geojson/featureidkey input 2923

px.scatter_geo now supports symbol 2923

go.Figure now has a set_subplots method to set subplots on an already existing figure. 2866

Added Turbo colorscale and fancier swatch display functions 2882

A utility function image_array_to_data_uri has been added in plotly.utils, in order to transform NumPy arrays to data b64 URIs (which can be passed to the source parameter of go.Image, or to layout images). 2879

the selector argument to updater/selector functions now accepts ints and strs 2894

Updated

the JSON serialization of plotly figures has been accelerated thanks to a different handling of Infinity and NaN values. For example, a figure with a 1000x1000 Heatmap should now serialize 2x faster. 2880

Coding mistakes with "magic underscores" now return significantly more ergonomic error messages 2843

Error messages related to impossible subplot geometries are now much more helpful 2897

Fixed

px.scatter_geo support for text is fixed 2923

the x and y parameters of px.imshow are now used also in the case where an Image trace is used (for RGB data or with binary_string=True). However, only numerical values are accepted (while the Heatmap trace allows date or string values for x and y). 2761

Source code(tar.gz)
Source code(zip)
v4.12.0(Oct 23, 2020)
See the full release announcement at https://community.plotly.com/t/announcing-plotly-py-4-12-horizontal-and-vertical-lines-and-rectangles/46783

Added

For add_trace, add_shape, add_annotation and add_layout_image, the row and/or col argument now also accept the string "all". row="all" adds the object to all the subplot rows and col="all" adds the object to all the subplot columns. (#2840)

Shapes that reference the plot axes in one dimension and the data in another dimension can be added with the new add_hline, add_vline, add_hrect, add_vrect functions, which also support the row="all" and col="all" arguments. (#2840)

The add_trace, add_shape, add_annotation, add_layout_image, add_hline, add_vline, add_hrect, add_vrect functions accept an argument exclude_empty_subplots which if True, only adds the object to subplots already containing traces or layout objects. This is useful in conjunction with the row="all" and col="all" arguments. (#2840)

For all go.Figure functions accepting a selector argument (e.g., select_traces), this argument can now also be a function which is passed each relevant graph object (in the case of select_traces, it is passed every trace in the figure). For graph objects where this function returns true, the graph object is included in the selection. (#2844)

Updated

Updated Plotly.js to version 1.57.1. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module.

Source code(tar.gz)
Source code(zip)
v4.11.0(Oct 1, 2020)
See the full release announcement at https://community.plotly.com/t/announcing-plotly-py-4-12-horizontal-and-vertical-lines-and-rectangles/46783

Updated

Updated Plotly.js to version 1.56.0. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module.

Source code(tar.gz)
Source code(zip)
v4.10.0(Sep 10, 2020)
See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-10-date-axis-improvements-a-faster-px-imshow-and-full-figures-for-development/44685

Added

Added plotly.io.full_figure_for_development() and plotly.graph_objects.Figure.full_figure_for_development() (#2737)

Updated

Updated Plotly.js to version 1.55.2. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module.

px.imshow has a new binary_string boolean argument, which passes the image data as a b64 binary string when True. Using binary strings allow for faster image rendering and smaller figure size. Additional optional arguments binary_backend, binary_format and binary_compression_level control how to generate the b64 string (#2691

px.imshow has a new constrast_rescaling argument in order to choose how to set data values corresponding to the bounds of the color range (#2691

Fixed

Plotly Express no longer converts datetime columns of input dataframes to UTC (#2749)

Plotly Express has more complete support for datetimes as additional hover_data (#2749)

Histogram selection behaviour with FigureWidget (#2711) with thanks to @meffmadd

Behaviour of full_html() with html=False (#2469) with thanks to @tallamjr

ff.distplot() now only computes traces that will be shown (#2730) with thanks to @akbo

Pandas backend .hist() works with latest version of Pandas (#2713) with thanks to @Kerybas

Source code(tar.gz)
Source code(zip)
v4.9.0(Jul 16, 2020)
See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-9-kaleido-for-static-image-export-hexbin-tile-maps-and-timelines/42524

Added

Added image export support using Kaleido. The image export backend can be configured using the new engine argument to plotly.io.to_image and plotly.io.write_image. The engine argument may be set to "kaleido", "orca", or "auto". The default is engine="auto", in which case the Kaleido backend is enabled if the kaleido package from PyPI is installed, otherwise Orca is used. (#2613).

plotly.express.timeline() added as an official alternative to plotly.figure_factories.create_gantt() (#2626)

create_hexbin_mapbox() added to Figure Factories, with thanks to @RenaudLN for the impressive contribution!

facet_row_spacing and facet_col_spacing added to Plotly Express cartesian 2d functions (#2614)

base added to Plotly Express bar and bar_polar functions (#2626)

px.NO_COLOR constant to override wide-form color assignment in Plotly Express (#2614)

Fixed

trendline traces are now of type scattergl when render_mode="webgl" in Plotly Express (#2614)

regression from 4.8.1 whereby "parent" was not accepted as part of path for px.sunburst() and px.treemap() (#2640)

create_dendrogram() figure factory now works correctly with scipy 1.5.1 (#2627)

Updated

Updated Plotly.js to version 1.54.6. See the plotly.js CHANGELOG for more information.

Added all cartesian-2d Plotly Express functions, plus imshow, to Pandas backend with kind option (#2541)

plotly.express.imshow now uses data frame index and columns names and values to populate axis parameters by default (#2539)

Javascript extensions are now build using Node 12, and have an updated package-lock.json with many fewer security warnings (#2636)

Source code(tar.gz)
Source code(zip)
v4.8.2(Jun 26, 2020)
See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-8-plotly-express-support-for-wide-and-mixed-form-data-plus-a-pandas-backend/40048

Updated

Updated Plotly.js to version 1.54.5. See the plotly.js CHANGELOG for more information. This version includes various bug and security fixes.

add_traces() now accepts bare int-like values for rows/cols as well as lists thereof (#2546), with thanks to @MCBoarder289 for the contribution!

Fixed

row/col now accept int-like values, not strictly int values (#2451), with thanks to @MCBoarder289 for the contribution!

Fixed special cases with px.sunburst and px.treemap with path input (#2524)

Fixed bug in hover_data argument of px functions, when the column name is changed with labels and hover_data is a dictionary setting up a specific format for the hover data (#2544).

Made the Plotly Express trendline argument more robust and made it work with datetime x values (#2554)

Fixed bug in px.sunburst and px.treemap: when the color and values arguments correspond to the same column, a different aggregation function has to be used for the two arguments (#2591)

Plotly Express wide mode now accepts mixed integer and float columns (#2598)

Plotly Express range_(x|y) should not impact the unlinked range of marginal subplots (#2600)

px.line now sets line_group=<variable> in wide mode by default (#2599)

Corrected some regex warnings (#2577), with thanks to @georgevdd for the contribution!

Source code(tar.gz)
Source code(zip)
v4.8.1(May 29, 2020)
See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-8-plotly-express-support-for-wide-and-mixed-form-data-plus-a-pandas-backend/40048

Fixed

Fixed the accidental removal of some functions and submodules from plotly.colors and plotly.express.colors

Source code(tar.gz)
Source code(zip)
v4.8.0(May 26, 2020)
See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-8-plotly-express-support-for-wide-and-mixed-form-data-plus-a-pandas-backend/40048

Key new documentation pages:

Wide-form and mixed-form data support in Plotly Express

Pandas plotting backend

Added

plotly now provides a Plotly Express-backed Pandas-compatible plotting backend, which can be activated via pandas.options.plotting.backend = "plotly". Note that it is not intended to implement every Pandas plotting function, nor is it intended to replicate the behaviour of every argument, although per the changes below, x and y should behave similarly. (#2336)

New datasets have been added to plotly.express.data: stocks, experiment, medals_wide and medals_long. (#2336)

plotly go.Figure and go.FigureWidget now have a _repr_html_ and a _repr_mimebundle_ method, which are standard hooks for integration in systems based on IPython. In particular, with _repr_html_ plotly figures can now be used within sphinx-gallery without any scraper. These additions should not change anything to the way plotly figures are displayed in notebook environments, since the _ipython_display_ method (already present in earlier versions) takes precedence over the new methods.

Updated

The behaviour of the x, y, orientation, histfunc, violinmode, boxmode and stripmode arguments for 2d-cartesian functions in Plotly Express (i.e. scatter, line, area, bar, histogram, violin, box, strip, funnel, density_heatmap and density_contour) has been refined (#2336):

wide-form data support: if either x or y (but not both) may now be provided as a list of column references into data_frame or columns of data, in which case the imputed data frame will be treated as "wide" data and melt()ed internally before applying the usual mapping rules, with function-specific defaults.

if neither x nor y is provided but data_frame is, the data frame will be treated as "wide" with defaults depending on the value of orientation (and orientation has accordingly been added to scatter, line, density_heatmap, and density_contour for this purpose). Previously this would have resulted in an empty figure.

if x or y is missing, it is inferred to be the index of data_frame if data_frame provided, otherwise a stable index of integers starting at 0. In the case of px.bar, if the provided value is not continuous, the missing value is treated as a column of 1s named "count", so as to behave more like px.histogram and to avoid sizing the resulting bars differently based on their position in the column. Previously, missing values defaulted to integers starting at 0 per trace which made it potentially inconsistent or misleading.

if x (y) is missing, orientation now defaults to v (h). Previously it always defaulted to v but this is not considered a breaking change, as the cases in which it now defaults to h caused unreadable output if set to v.

if both x and y are provided and one of them does not contain continuous values, orientation defaults to the value perpendicular to that axis. Previously it always defaulted to v but this is not considered a breaking change, as the cases in which it now defaults to h caused unreadable output if set to v.

if both x and y are provided to histogram, and if x, y and z are provided to density_heatmap or density_contour, then histfunc now defaults to sum so as to avoid ignoring the provided data, and to cause histogram and bar to behave more similarly.

violinmode, boxmode and stripmode now default to overlay if x (y) in in v (h) orientation is also mapped to color, to avoid strange spacing issues with the previous default of group in all cases.

The Plotly Express arguments color_discrete_map, symbol_map and line_dash_map now accept the string "identity" which causes the corresponding input data to be used as-is rather than mapped into color_discrete_sequence, symbol_sequence or line_dash_sequence, respectively. (#2336)

Plotly Express now accepts px.Constant or px.Range objects in the place of column references so as to express constant or increasing integer values. (#2336)

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Update: June 27, 2018

Overview

Lazy submodule imports in Python 3.7+

Lazy creation of validators

Lazy creation of child graph objects

Avoid loading numpy and pandas when not in use

Avoid dynamic docstring generation

Support optional validation

Results

top-level import

Import, create empty figure, and serialize to JSON

Repeatedly create empty figure and serialize to json (after import)

Import, load data, create animated plotly express figure, serialize to json

Repeatedly create px plot after import and data are loaded

Import, load data, create animated plotly express figure, serialize to json, skip validation

Repeatedly import, load data, create animated plotly express figure, serialize to json, skip validation

Code PR

v1.0.2

Unreleased [code, diff]

v2.2.3 [code, diff]

v2.2.2 [code, diff]

v2.2.1 [code, diff]

v2.2.0 [code, diff]

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v2.1.2 [code, diff]

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v5.9.0(Jun 24, 2022)

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