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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def behaviors_distribution(df, filepath=None):
 """ Plots the distribution of logical networks across input-output behaviors. Optionally, input-output behaviors can be grouped by MSE. Parameters df: `pandas.DataFrame`_ DataFrame with columns `networks` and optionally `mse` filepath: str Absolute path to a folder where to write the plot Returns ------- plot Generated plot .. _pandas.DataFrame: http://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe """


    cols = ["networks", "index"]
    rcols = ["Logical networks", "Input-Output behaviors"]
    sort_cols = ["networks"]

    if "mse" in df.columns:
        cols.append("mse")
        rcols.append("MSE")
        sort_cols = ["mse"] + sort_cols

        df.mse = df.mse.map(lambda f: "%.4f" % f)

    df = df.sort_values(sort_cols).reset_index(drop=True).reset_index(level=0)[cols]
    df.columns = rcols

    if "MSE" in df.columns:
        g = sns.factorplot(x='Input-Output behaviors', y='Logical networks', hue='MSE', data=df, aspect=3, kind='bar', legend_out=False)
    else:
        g = sns.factorplot(x='Input-Output behaviors', y='Logical networks', data=df, aspect=3, kind='bar', legend_out=False)

    g.ax.set_xticks([])
    if filepath:
        g.savefig(os.path.join(filepath, 'behaviors-distribution.pdf'))

    return g