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ggplot alternatives and similar packages
Based on the "Data Visualization" category.
Alternatively, view ggplot alternatives based on common mentions on social networks and blogs.
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Apache Superset
DISCONTINUED. Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset] -
redash
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data. -
#<Sawyer::Resource:0x00007fbd82367850>
Panel: The powerful data exploration & web app framework for Python -
Flask JSONDash
:snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go. -
ipyvizzu
Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax.
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README
ggplot
What is it?
ggplot
is a Python implementation of the grammar of graphics. It is not intended
to be a feature-for-feature port of ggplot2 for R
--though
there is much greatness in ggplot2
, the Python world could stand to benefit
from it. So there will be feature overlap, but not neccessarily mimicry
(after all, R is a little weird).
You can do cool things like this:
ggplot(diamonds, aes(x='price', color='clarity')) + \
geom_density() + \
scale_color_brewer(type='div', palette=7) + \
facet_wrap('cut')
[](./docs/example.png)
Installation
$ pip install -U ggplot
# or
$ conda install -c conda-forge ggplot
# or
pip install git+https://github.com/yhat/ggplot.git
Examples
Examples are the best way to learn. There is a Jupyter Notebook full of them. There are also notebooks that show how to do particular things with ggplot (i.e. [make a scatter plot](./docs/how-to/Making%20a%20Scatter%20Plot.ipynb) or [make a histogram](./docs/how-to/Making%20a%20Scatter%20Plot.ipynb)).
- [docs](./docs)
- [gallery](./docs/Gallery.ipynb)
- [various examples](./examples.md)
What happened to the old version that didn't work?
It's gone--the windows, the doors, everything. Just kidding, you can find it here, though I'm not sure why you'd want to look at it. The data grouping and manipulation bits were re-written (so they actually worked) with things like facets in mind.
Contributing
Thanks to all of the ggplot [contributors](./contributors.md#contributors)! See [contributing.md](./contributing.md).