data_view.py 文件源码

def user_info_m_p(df):
    date2 = df[record_date].map(lambda x: str2time(x)).max()
    date1 = datetime.datetime(date2.year, date2.month, 1).date()
    grouped = DataView(df).filter_by_record_date2(date1, date2)[[user_id, 'month', power_consumption]].groupby([user_id, 'month'], as_index=False)
    user_power_mean_m = grouped.mean()
    user_power_median_m = grouped.median()
    user_power_var_m = grouped.var()
    user_power_max_m = grouped.max()
    user_power_min_m = grouped.min()
    user_power_mean_m = user_power_mean_m.rename(columns={power_consumption: 'user_power_mean_m_p'})
    user_power_median_m = user_power_median_m.rename(columns={power_consumption: 'user_power_median_m_p'})
    user_power_var_m = user_power_var_m.rename(columns={power_consumption: 'user_power_var_m_p'})
    user_power_max_m = user_power_max_m.rename(columns={power_consumption: 'user_power_max_m_p'})
    user_power_min_m = user_power_min_m.rename(columns={power_consumption: 'user_power_min_m_p'})
    return pd.merge(user_power_mean_m, user_power_median_m).merge(user_power_var_m).\
        merge(user_power_max_m).merge(user_power_min_m).drop('month', axis=1)


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