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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 example_stats(filename):
 """ Obtain statistics from create grid topology Prints some statistical numbers and produces exemplary figures """


    nd = results.load_nd_from_pickle(filename=filename)

    nodes_df, edges_df = nd.to_dataframe()

    # get statistical numbers about grid
    stats = results.calculate_mvgd_stats(nd)

    # plot distribution of load/generation of subjacent LV grids
    stations = nodes_df[nodes_df['type'] == 'LV Station']
    f, axarr = plt.subplots(2, sharex=True)
    f.suptitle("Peak load (top) / peak generation capacity (bottom) at LV "
               "substations in kW")
    stations['peak_load'].hist(bins=20, alpha=0.5, ax=axarr[0])
    axarr[0].set_title("Peak load in kW")
    stations['generation_capacity'].hist(bins=20, alpha=0.5, ax=axarr[1])
    axarr[1].set_title("Peak generation capacity in kW")
    plt.show()

    # Introduction of report
    print("You are analyzing MV grid district {mvgd}\n".format(
        mvgd=int(stats.index.values)))

    # print all the calculated stats
    # this isn't a particularly beautiful format but it is
    # information rich
    with option_context('display.max_rows', None,
                        'display.max_columns', None,
                        'display.max_colwidth', -1):
        print(stats.T)