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A Pythonic wrapper around R's ggplot

Project description

pyggplot is a Pythonic wrapper around the [R ggplot2 library](

It is based on a a straightforward take [Pandas]( data frames and shove them into [R]( via [rpy2]( approach.

## Examples Please visit

## Installation

The easiest installation is via [PyPI](

$ pip install pyggplot

You may be required to update pandas, rpy2, so you may be required to run

$ pip install –upgrade pyggplot

## Usage

import pandas as pd import numpy as np import ggplot

df = pd.DataFrame({‘x’: np.random.rand(100),

‘y’: np.random.randn(100), ‘group’: [‘A’,’B’] * 50})

p = pyggplot.Plot(df) p.add_scatter(‘x’,’y’, color=’group’) p.render(‘output.png’) ## or if you want to use it in IPython Notebook # p.render_notebook()

## Further usage

Takes a pandas.DataFrame object, then add layers with the various add_xyz functions (e.g. add_scatter).

Refer to the ggplot documentation about the layers (geoms), and simply replace geom_* with add_*. See:

You do not need to separate aesthetics from values - the wrapper will treat a parameter as value if and only if it is not a column name. (so y = 0 is a value, color = ‘blue’ is a value - except if you have a column ‘blue’, then it is a column!. And y = ‘value’ does not work, but that seems to be a ggplot issue).

When the DataFrame is passed to R:

  • row indices are turned into columns with ‘reset_index’,

  • multi level column indices are flattened by concatenating them with ‘ ‘, that is (X, ‘mean’) becomes ‘x mean’.

Error messages are not great - most of them translate to ‘one or more columns were not found’, but they can appear as a lot of different actual messages such as

  • argument “env” is missing, with no default

  • object ‘y’ not found

  • object ‘dat_0’ not found

  • requires the following missing aesthetics: x

  • non numeric argument to binary operator

without actually quite pointing at what is strictly the offending value. Also, the error appears when rendering (or printing in the [IPython Notebook](, not when adding the layer.

## Open questions

  • the stat support is not great - it doesn’t easily map into pythonic objects. For now, do your stats in pandas - more powerful anyhow!

  • how could error messages be improved?

## Other ggplots’ for python

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