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# 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>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>
## Quickstart
`pip install plotly "notebook>=5.3" "ipywidgets>=7.2"`
Inside [Jupyter notebook](https://jupyter.org/install):
```python
import plotly.graph_objs as go
fig = go.FigureWidget()
# Display an empty figure
fig
```
```python
# Add a scatter chart
fig.add_scatter(y=[2, 1, 4, 3])
# Add a bar chart
fig.add_bar(y=[1, 4, 3, 2])
# Add a title
fig.layout.title = 'Hello FigureWidget'
```
See the [Python documentation](https://plot.ly/python/) for more examples.
Read about what's new in [plotly.py v3](https://medium.com/@plotlygraphs/introducing-plotly-py-3-0-0-7bb1333f69c6)
## Overview
[plotly.py](https://plot.ly/d3-js-for-python-and-pandas-charts/) 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](LICENSE.txt). Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online on [plot.ly](https://plot.ly).
[Contact us](https://plot.ly/products/consulting-and-oem/) for Plotly.js consulting, dashboard development, application integration, and feature additions. Sharing your graphs online or in dashboards? Consider a [plot.ly subscription](https://plot.ly/products/cloud).
<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](contributing.md)
- [Changelog](CHANGELOG.md)
- [Code of Conduct](CODE_OF_CONDUCT.md)
- [Version 3 Migration Guide](migration-guide.md)
- [New! Announcing Dash](https://medium.com/@plotlygraphs/introducing-dash-5ecf7191b503)
- [Community](https://community.plot.ly/c/api/python)
***
## Installation
plotly.py may be installed using pip...
```
pip install plotly==3.6.1
```
or conda.
```
conda install -c plotly plotly=3.6.1
```
### Jupyter Notebook Support
For use in the Jupyter Notebook, install the `notebook` and `ipywidgets`
packages using pip...
```
pip install "notebook>=5.3" "ipywidgets>=7.2"
```
or conda.
```
conda install "notebook>=5.3" "ipywidgets>=7.2"
```
### JupyterLab Support (Python 3.5+)
For use in JupyterLab, install the `jupyterlab` and `ipywidgets`
packages using pip...
```
pip install jupyterlab==0.35 "ipywidgets>=7.2"
```
or conda.
```
conda install jupyterlab=0.35 "ipywidgets>=7.2"
```
Then run the following commands to install the required JupyterLab extensions:
```
# Avoid "JavaScript heap out of memory" errors during extension installation
# (OS X/Linux)
export NODE_OPTIONS=--max-old-space-size=4096
# (Windows)
set NODE_OPTIONS=--max-old-space-size=4096
# Jupyter widgets extension
jupyter labextension install @jupyter-widgets/jupyterlab-manager@0.38 --no-build
# FigureWidget support
jupyter labextension install plotlywidget@0.7.1 --no-build
# offline iplot support
jupyter labextension install @jupyterlab/plotly-extension@0.18.1 --no-build
# JupyterLab chart editor support (optional)
jupyter labextension install jupyterlab-chart-editor@1.0 --no-build
# Build extensions (must be done to activate extensions since --no-build is used above)
jupyter lab build
# Unset NODE_OPTIONS environment variable
# (OS X/Linux)
unset NODE_OPTIONS
# (Windows)
set NODE_OPTIONS=
```
### Static Image Export
plotly.py supports static image export using the `to_image` and `write_image`
functions in the `plotly.io` package. This functionality requires the
installation of the plotly [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 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).
## Migration
If you're migrating from plotly.py version 2, please check out the [migration guide](migration-guide.md)
## Copyright and Licenses
Code and documentation copyright 2018 Plotly, Inc.
Code released under the [MIT license](LICENSE.txt).
Docs released under the [Creative Commons license](https://github.com/plotly/documentation/blob/source/LICENSE).
|
