| Name | hvplot JSON |
| Version |
0.9.2
JSON |
| download |
| home_page | https://hvplot.holoviz.org |
| Summary | A high-level plotting API for the PyData ecosystem built on HoloViews. |
| upload_time | 2024-01-29 16:26:00 |
| maintainer | HoloViz developers |
| docs_url | None |
| author | Philipp Rudiger |
| requires_python | >=3.8 |
| license | BSD |
| keywords |
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| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# hvPlot makes data analysis and visualization simple <img src="https://github.com/holoviz/hvplot/blob/main/doc/_static/logo.png?raw=true" style="width:2em;margin-bottom:-15px">
| | |
| --- | --- |
| Build Status | [](https://github.com/holoviz/hvplot/actions?query=workflow%3Atests+branch%3Amain) |
| Coverage | [](https://codecov.io/gh/holoviz/hvplot) |
| Latest dev release | [](https://github.com/holoviz/hvplot/tags) [](https://holoviz-dev.github.io/hvplot/) |
| Latest release | [](https://github.com/holoviz/hvplot/releases) [](https://pypi.python.org/pypi/hvplot) [](https://anaconda.org/pyviz/hvplot) [](https://anaconda.org/conda-forge/hvplot) [](https://anaconda.org/anaconda/hvplot) |
| Python | [](https://pypi.org/project/hvplot/) |
| Docs | [](https://github.com/holoviz/hvplot/tree/gh-pages) [](https://hvplot.holoviz.org) |
| Binder | [](https://mybinder.org/v2/gh/holoviz/hvplot/v0.8.1?urlpath=lab/tree/examples) |
| Support | [](https://discourse.holoviz.org/c/hvplot/8) |
[Home](https://hvplot.holoviz.org/) | [Installation instructions](#installation-instructions) | [Getting Started Guide](https://hvplot.holoviz.org/getting_started/index.html) | [Reference Guides](https://hvplot.holoviz.org/reference/index.html) | [Examples](#examples) | [License](#license) | [Support](#support--feedback)
## hvPlot provides a familiar, high-level API for visualization
The API is based on the familiar Pandas `.plot` API and the innovative `.interactive` API.
<img src="https://github.com/MarcSkovMadsen/awesome-panel-assets/blob/master/images/hvPlot/hvplot-total-intro.gif?raw=true" style="max-height:600px;border-radius:2%;">
## hvPlot works with the tools you know and love
hvPlot
- supports a wide range of data sources including [Pandas](http://pandas.pydata.org), [Polars](https://docs.pola.rs/), [XArray](http://xarray.pydata.org), [Dask](http://dask.pydata.org), [Streamz](http://streamz.readthedocs.io), [Intake](http://github.com/ContinuumIO/intake), [GeoPandas](http://geopandas.org) and [NetworkX](https://networkx.github.io/documentation/stable/).
- supports the plotting backends [Bokeh](https://docs.bokeh.org/en/latest/), [Matplotlib](https://matplotlib.org/) and [Plotly](https://plotly.com/python/).
- exposes the powerful tools from the [HoloViz](https://holoviz.org/) ecosystem in a familiar and convenient API.
[<img src="https://hvplot.holoviz.org/assets/diagram.svg" style="max-height:400px;border-radius:2%;"/>](https://holoviz.org/)
hvPlot is **the simplest way to benefit from the [HoloViz](https://holoviz.org/) ecosystem for data exploration**.
## hvPlot can be used for exploration, reporting and data apps
Check out [this blog post](https://towardsdatascience.com/the-easiest-way-to-create-an-interactive-dashboard-in-python-77440f2511d1) to see how easy it is to create an interactive dashboard with hvPlot and Panel.
<a href="https://towardsdatascience.com/the-easiest-way-to-create-an-interactive-dashboard-in-python-77440f2511d1"><img src="https://miro.medium.com/max/700/1*bZjPtucT8O1esjQaGQenHw.gif" style="max-height:600px;border-radius:2%;"></a>
## Mini getting-started
Head over to the [getting started guide](https://hvplot.holoviz.org/getting_started/index.html) for more!
### Install
hvPlot can be installed on Linux, Windows, or Mac with ``conda``:
```bash
conda install hvplot
```
or with ``pip``:
```bash
pip install hvplot
```
Please note that for versions of `jupyterlab<3.0`, you must install the JupyterLab extension manually with:
```bash
jupyter labextension install @pyviz/jupyterlab_pyviz
```
### Plotting data
Work with your data source:
```python
import numpy as np
import pandas as pd
idx = pd.date_range('1/1/2000', periods=1000)
df = pd.DataFrame(np.random.randn(1000, 4), index=idx, columns=list('ABCD')).cumsum()
```
Import the hvPlot extension for your data source and optionally set the plotting backend:
```python
import hvplot.pandas
# Optional: hvplot.extension('matplotlib') or hvplot.extension('plotly')
```
Use the `.hvplot` API as you would use the Pandas or Xarray `.plot` API:
```python
df.hvplot()
```
[<img src="https://github.com/MarcSkovMadsen/awesome-panel-assets/blob/master/images/hvPlot/hvplot-intro-plot.gif?raw=true" style="max-height:300px;border-radius:2%;">](https://hvplot.holoviz.org/user_guide/index.html)
### Interactive data apps
Just add `.interactive` and replace your normal arguments with [Panel widgets](https://panel.holoviz.org/reference/index.html#widgets) or [Ipywidgets](https://ipywidgets.readthedocs.io/en/stable/examples/Widget%20List.html).
```python
import panel as pn
pn.extension()
df.interactive(width=600).head(n=pn.widgets.IntSlider(start=1, end=5, value=3))
```
[<img src="https://github.com/MarcSkovMadsen/awesome-panel-assets/blob/master/images/hvPlot/hvplot-intro-interactive.gif?raw=true" style="max-height:300px;border-radius:2%;">](https://hvplot.holoviz.org/user_guide/Interactive.html)
### How to find documentation from your notebook or editor
To see the available arguments for a specific `kind` of plot run
```python
hvplot.help(kind='scatter')
```
In a notebook or ipython environment the usual
- `help` and `?` will provide you with documentation.
- `TAB` and `SHIFT+TAB` completion will help you navigate.
## License
hvPlot is completely free and open-source. It is licensed under the [BSD 3-Clause License](https://opensource.org/licenses/BSD-3-Clause).
## Support & Feedback
- Usage questions and showcases -> [HoloViz Community](https://holoviz.org/community.html)
- Bug reports and feature requests -> [Github](https://github.com/holoviz/hvplot)
- Developer discussions -> [Discord](https://discord.gg/rb6gPXbdAr)
For more detail check out the [HoloViz Community Guide](https://holoviz.org/community.html).
## Contributions
We would love to work with you no matter whether you want to contribute to issue management, PRs, documentation, blog posts, community support or social media communication.
To get started with the code or docs check out the [Developer Guide](https://hvplot.holoviz.org/developer_guide/index.html).
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"description": "# hvPlot makes data analysis and visualization simple <img src=\"https://github.com/holoviz/hvplot/blob/main/doc/_static/logo.png?raw=true\" style=\"width:2em;margin-bottom:-15px\">\n\n| | |\n| --- | --- |\n| Build Status | [](https://github.com/holoviz/hvplot/actions?query=workflow%3Atests+branch%3Amain) |\n| Coverage | [](https://codecov.io/gh/holoviz/hvplot) |\n| Latest dev release | [](https://github.com/holoviz/hvplot/tags) [](https://holoviz-dev.github.io/hvplot/) |\n| Latest release | [](https://github.com/holoviz/hvplot/releases) [](https://pypi.python.org/pypi/hvplot) [](https://anaconda.org/pyviz/hvplot) [](https://anaconda.org/conda-forge/hvplot) [](https://anaconda.org/anaconda/hvplot) |\n| Python | [](https://pypi.org/project/hvplot/) |\n| Docs | [](https://github.com/holoviz/hvplot/tree/gh-pages) [](https://hvplot.holoviz.org) |\n| Binder | [](https://mybinder.org/v2/gh/holoviz/hvplot/v0.8.1?urlpath=lab/tree/examples) |\n| Support | [](https://discourse.holoviz.org/c/hvplot/8) |\n\n[Home](https://hvplot.holoviz.org/) | [Installation instructions](#installation-instructions) | [Getting Started Guide](https://hvplot.holoviz.org/getting_started/index.html) | [Reference Guides](https://hvplot.holoviz.org/reference/index.html) | [Examples](#examples) | [License](#license) | [Support](#support--feedback)\n\n## hvPlot provides a familiar, high-level API for visualization\n\nThe API is based on the familiar Pandas `.plot` API and the innovative `.interactive` API.\n\n<img src=\"https://github.com/MarcSkovMadsen/awesome-panel-assets/blob/master/images/hvPlot/hvplot-total-intro.gif?raw=true\" style=\"max-height:600px;border-radius:2%;\">\n\n## hvPlot works with the tools you know and love\n\nhvPlot\n\n- supports a wide range of data sources including [Pandas](http://pandas.pydata.org), [Polars](https://docs.pola.rs/), [XArray](http://xarray.pydata.org), [Dask](http://dask.pydata.org), [Streamz](http://streamz.readthedocs.io), [Intake](http://github.com/ContinuumIO/intake), [GeoPandas](http://geopandas.org) and [NetworkX](https://networkx.github.io/documentation/stable/).\n- supports the plotting backends [Bokeh](https://docs.bokeh.org/en/latest/), [Matplotlib](https://matplotlib.org/) and [Plotly](https://plotly.com/python/).\n- exposes the powerful tools from the [HoloViz](https://holoviz.org/) ecosystem in a familiar and convenient API.\n\n[<img src=\"https://hvplot.holoviz.org/assets/diagram.svg\" style=\"max-height:400px;border-radius:2%;\"/>](https://holoviz.org/)\n\nhvPlot is **the simplest way to benefit from the [HoloViz](https://holoviz.org/) ecosystem for data exploration**.\n\n## hvPlot can be used for exploration, reporting and data apps\n\nCheck out [this blog post](https://towardsdatascience.com/the-easiest-way-to-create-an-interactive-dashboard-in-python-77440f2511d1) to see how easy it is to create an interactive dashboard with hvPlot and Panel.\n\n<a href=\"https://towardsdatascience.com/the-easiest-way-to-create-an-interactive-dashboard-in-python-77440f2511d1\"><img src=\"https://miro.medium.com/max/700/1*bZjPtucT8O1esjQaGQenHw.gif\" style=\"max-height:600px;border-radius:2%;\"></a>\n\n## Mini getting-started\n\nHead over to the [getting started guide](https://hvplot.holoviz.org/getting_started/index.html) for more!\n\n### Install\n\nhvPlot can be installed on Linux, Windows, or Mac with ``conda``:\n\n```bash\nconda install hvplot\n```\n\nor with ``pip``:\n\n```bash\npip install hvplot\n```\n\nPlease note that for versions of `jupyterlab<3.0`, you must install the JupyterLab extension manually with:\n\n```bash\njupyter labextension install @pyviz/jupyterlab_pyviz\n```\n\n### Plotting data\n\nWork with your data source:\n\n```python\nimport numpy as np\nimport pandas as pd\n\nidx = pd.date_range('1/1/2000', periods=1000)\ndf = pd.DataFrame(np.random.randn(1000, 4), index=idx, columns=list('ABCD')).cumsum()\n```\n\nImport the hvPlot extension for your data source and optionally set the plotting backend:\n\n```python\nimport hvplot.pandas\n# Optional: hvplot.extension('matplotlib') or hvplot.extension('plotly')\n```\n\nUse the `.hvplot` API as you would use the Pandas or Xarray `.plot` API:\n\n```python\ndf.hvplot()\n```\n\n[<img src=\"https://github.com/MarcSkovMadsen/awesome-panel-assets/blob/master/images/hvPlot/hvplot-intro-plot.gif?raw=true\" style=\"max-height:300px;border-radius:2%;\">](https://hvplot.holoviz.org/user_guide/index.html)\n\n\n### Interactive data apps\n\nJust add `.interactive` and replace your normal arguments with [Panel widgets](https://panel.holoviz.org/reference/index.html#widgets) or [Ipywidgets](https://ipywidgets.readthedocs.io/en/stable/examples/Widget%20List.html).\n\n```python\nimport panel as pn\npn.extension()\n\ndf.interactive(width=600).head(n=pn.widgets.IntSlider(start=1, end=5, value=3))\n```\n\n[<img 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