cohorts_touch = orders.query('device == "touch"').groupby(['first_order_month','cohort_lifetime']).agg({'buy_ts':'count','uid':'nunique'}).reset_index()
cohort_touch_users_count = cohorts_touch[['first_order_month','uid']]
cohort_touch_users_count = cohort_touch_users_count.rename(columns={'uid':'cohort_users'})
cohorts_touch = cohorts_touch.merge(cohort_touch_users_count,on='first_order_month')
cohorts_touch['rate'] = cohorts_touch['buy_ts'] / cohorts_touch['cohort_users']
cohorts_pivot_touch = cohorts_touch.pivot_table(index='first_order_month',
                                columns='cohort_lifetime',
                                values='rate',
                                aggfunc='mean').cumsum(axis=1)
cohorts_pivot_touch.index = cohorts_pivot_touch.index.strftime("%m/%Y")
plt.figure(figsize=(13, 9))
plt.title('Среднее количество покупок в когорте на уникального мобильного пользователя')
sns.heatmap(cohorts_pivot_touch, annot=True, fmt='.2f', linewidths=1, linecolor='gray')