Metadata-Version: 1.0
Name: pyggplot
Version: 11
Summary: A pythonic wrapper around R's ggplot
Home-page: UNKNOWN
Author: Florian Finkernagel
Author-email: finkernagel@coonabibba.de
License: BSD
Description: pyggplot
        ========
        
        pyggplot is a Pythonic wrapper around the [R ggplot2 library](http://had.co.nz/ggplot2/).
        
        Unlike the [Python ggplot](https://github.com/yhat/ggplot) this is not a reimplementation based on [Matplotlib](http://matplotlib.org/), but a straightforward *take [Pandas](http://pandas.pydata.org/) data frames and shove them into [R](http://www.r-project.org/) via [rpy2](https://pypi.python.org/pypi/rpy2)* approach.
        
        ## Installation
        
        The easiest installation is via [PyPI](https://pypi.python.org/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()
        
        
        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: http://docs.ggplot2.org/0.9.3.1/index.html
        
        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](http://ipython.org/notebook.html)),
        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?
        
        
        
        
        
Platform: UNKNOWN
