Metadata-Version: 2.1
Name: plotly
Version: 4.14.3
Summary: An open-source, interactive data visualization library for Python
Home-page: https://plotly.com/python/
Author: Chris P
Author-email: chris@plot.ly
Maintainer: Nicolas Kruchten
Maintainer-email: nicolas@plot.ly
License: MIT
Project-URL: Github, https://github.com/plotly/plotly.py
Description: # plotly.py
        
        <table>
            <tr>
                <td>Latest Release</td>
                <td>
                    <a href="https://pypi.org/project/plotly/"/>
                    <img src="https://badge.fury.io/py/plotly.svg"/>
                </td>
            </tr>
            <tr>
                <td>User forum</td>
                <td>
                    <a href="https://community.plot.ly"/>
                    <img src="https://img.shields.io/badge/help_forum-discourse-blue.svg"/>
                </td>
            </tr>
            <tr>
                <td>PyPI Downloads</td>
                <td>
                    <a href="https://pepy.tech/project/plotly"/>
                    <img src="https://pepy.tech/badge/plotly/month"/>
                </td>
            </tr>
            <tr>
                <td>License</td>
                <td>
                    <a href="https://opensource.org/licenses/MIT"/>
                    <img src="https://img.shields.io/badge/License-MIT-yellow.svg"/>
                </td>
            </tr>
        </table>
        
        ## Data Science Workspaces
        
        Our recommended IDE for Plotly’s Python graphing library is Dash Enterprise’s [Data Science Workspaces](https://plotly.com/dash/workspaces/), which has both Jupyter notebook and Python code file support.
        
        ## Quickstart
        
        `pip install plotly==4.14.3`
        
        Inside [Jupyter notebook](https://jupyter.org/install) (installable with `pip install "notebook>=5.3" "ipywidgets>=7.5"`):
        
        ```python
        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](https://plot.ly/python/) for more examples.
        
        Read about what's new in [plotly.py v4](https://medium.com/plotly/plotly-py-4-0-is-here-offline-only-express-first-displayable-anywhere-fc444e5659ee)
        
        ## Overview
        
        [plotly.py](https://plot.ly/python) is an interactive, open-source, and browser-based graphing library for Python :sparkles:
        
        Built on top of [plotly.js](https://github.com/plotly/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](packages/python/chart-studio/LICENSE.txt). Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using [Chart Studio Cloud](https://chart-studio.plot.ly/feed/).
        
        [Contact us](https://plot.ly/products/consulting-and-oem/) for consulting, dashboard development, application integration, and feature additions.
        
        <p align="center">
            <a href="https://plot.ly/python" target="_blank">
            <img src="https://raw.githubusercontent.com/cldougl/plot_images/add_r_img/plotly_2017.png">
        </a></p>
        
        ---
        
        - [Online Documentation](https://plot.ly/python)
        - [Contributing to plotly](contributing.md)
        - [Changelog](CHANGELOG.md)
        - [Code of Conduct](CODE_OF_CONDUCT.md)
        - [Version 4 Migration Guide](https://plot.ly/python/next/v4-migration/)
        - [New! Announcing Dash 1.0](https://medium.com/plotly/welcoming-dash-1-0-0-f3af4b84bae)
        - [Community forum](https://community.plot.ly/c/api/python)
        
        ---
        
        ## 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`](https://nodejs.org/) to be installed):
        
        ```
        # Basic JupyterLab renderer support
        jupyter labextension install jupyterlab-plotly@4.14.3
        
        # OPTIONAL: Jupyter widgets extension for FigureWidget support
        jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.14.3
        ```
        
        Please check out our [Troubleshooting guide](https://plotly.com/python/troubleshooting/) if you run into any problems with JupyterLab.
        
        ### Static Image Export
        
        plotly.py supports [static image export](https://plotly.com/python/static-image-export/),
        using either the [`kaleido`](https://github.com/plotly/Kaleido)
        package (recommended, supported as of `plotly` version 4.9) or the [orca](https://github.com/plotly/orca)
        command line utility (legacy as of `plotly` version 4.9).
        
        #### Kaleido
        
        The [`kaleido`](https://github.com/plotly/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](https://plotly.com/python/static-image-export/)
        can also be supported
        by the legacy [orca](https://github.com/plotly/orca) command line utility and the
         [`psutil`](https://github.com/giampaolo/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](https://github.com/plotly/orca).
        
        
        ### 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](https://plot.ly/python/next/v4-migration/)
        
        If you're migrating from plotly.py v2 to v3, please check out the [Version 3 migration guide](migration-guide.md)
        
        ## Copyright and Licenses
        
        Code and documentation copyright 2019 Plotly, Inc.
        
        Code released under the [MIT license](packages/python/chart-studio/LICENSE.txt).
        
        Docs released under the [Creative Commons license](https://github.com/plotly/documentation/blob/source/LICENSE).
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/markdown
