Стабильность кумулятивных метрик задача 4

import pandas as pd
import datetime as dt
import numpy as np
import matplotlib.pyplot as plt
from pandas.plotting import register_matplotlib_converters
import warnings
# конвертеры, которые позволяют использовать типы pandas в matplotlib
register_matplotlib_converters()

orders = pd.read_csv('/datasets/data_for_tasks_3.csv', sep=',')
orders['date'] = orders['date'].map(
    lambda x: dt.datetime.strptime(x, '%d/%m/%Y')
)

visitors = pd.read_csv('/datasets/data_for_tasks_3_visitors.csv', sep=',')
visitors['date'] = visitors['date'].map(
    lambda x: dt.datetime.strptime(x, '%d/%m/%Y')
)

datesGroups = orders[['date', 'group']].drop_duplicates()

ordersAggregated = datesGroups.apply(
    lambda x: orders[
        np.logical_and(
            orders['date'] <= x['date'], orders['group'] == x['group']
        )
    ].agg(
        {
            'date': 'max',
            'group': 'max',
            'orderId': 'nunique',
            'userId': 'nunique',
            'revenue': 'sum',
        }
    ),
    axis=1,
).sort_values(by=['date', 'group'])

visitorsAggregated = datesGroups.apply(
    lambda x: visitors[
        np.logical_and(
            visitors['date'] <= x['date'], visitors['group'] == x['group']
        )
    ].agg({'date': 'max', 'group': 'max', 'visitors': 'sum'}),
    axis=1,
).sort_values(by=['date', 'group'])

cumulativeData = ordersAggregated.merge(
    visitorsAggregated, left_on=['date', 'group'], right_on=['date', 'group']
)
cumulativeData.columns = [
    'date',
    'group',
    'orders',
    'buyers',
    'revenue',
    'visitors',
]

cumulativeRevenueA = cumulativeData[cumulativeData['group'] == 'A'][
    ['date', 'revenue', 'orders']
]
cumulativeRevenueB = cumulativeData[cumulativeData['group'] == 'B'][
    ['date', 'revenue', 'orders']
]
mergedCumulativeRevenue = cumulativeRevenueA.merge(cumulativeRevenueB, left_on = 'date',
                                                   right_on='date',  how='left',
                                                  suffixes = ['A', 'B'])

plt.figure(figsize=(12,4))
plt.plot(mergedCumulativeRevenue['date'],
         (mergedCumulativeRevenue['revenueB']/mergedCumulativeRevenue['ordersB'] -
             mergedCumulativeRevenue['revenueA']/mergedCumulativeRevenue['ordersA'])/(
         mergedCumulativeRevenue['revenueA']/mergedCumulativeRevenue['ordersA']))
plt.axhline(y = 0, color ="black", linestyle ="--")
plt.show()