Bin a pandas dataframe on its columns

binify.py

def binify(df, bins):
    """Makes a histogram of each row the provided binsize

    Parameters
    ----------
    data : pandas.DataFrame
        A samples x features dataframe. Each feature will be binned into the
        provided bins
    bins : iterable
        Bins you would like to use for this data. Must include the final bin
        value, e.g. (0, 0.5, 1) for the two bins (0, 0.5) and (0.5, 1)

    Returns
    -------
    binned : pandas.DataFrame
        A len(bins)-1 x features DataFrame of each feature binned across
        samples
    """
    nrow = len(bins) - 1
    ncol = df.shape[1]
    binned = np.zeros((nrow, ncol))

    # TODO.md: make sure this works for numpy matrices
    for i, (name, row) in enumerate(df.iteritems()):
        binned[:, i] = np.histogram(row, bins=bins, normed=True)[0]

    index = ['{}-{}'.format(i, j) for i, j in zip(bins, bins[1:])]
    binned = pd.DataFrame(binned, columns=df.columns, index=index)
    return binned