我有以下country wise orders data過去兩周的數(shù)據(jù)框。我想計(jì)算與上周相比按國(guó)家/地區(qū)、開始日期和結(jié)束日期分組的食品訂單的百分比變化（增加或減少） 。Formula = (this_week_orders*100)/(last_week_orders) - 100對(duì)于上面的 df，我想得到最終的數(shù)據(jù)框如下正如我們所看到的，Russia had a decrease in order count of 33%與India had an increase of 50%上周相比請(qǐng)建議如何編寫自定義聚合函數(shù)，因?yàn)槲抑皇煜?biāo)準(zhǔn)函數(shù)，如 sum() 、 count() 等......
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梵蒂岡之花
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df = pd.DataFrame({'start_date':['2020-09-21','2020-09-21','2020-09-28', '2020-09-28'],
'end_date':['2020-09-27', '2020-09-27', '2020-10-04', '2020-10-04'],
'Country':['Russia', 'India','Russia','India'],
'orders':[150,80,100,120]})
df['start_date'] = pd.to_datetime(df['start_date'])
df.sort_values(by='start_date', inplace=True)
df['% Change'] = df.groupby('Country')['orders'].pct_change()
輸出
start_date end_date Country orders % Change
0 2020-09-21 2020-09-27 Russia 150 NaN
1 2020-09-21 2020-09-27 India 80 NaN
2 2020-09-28 2020-10-04 Russia 100 -0.333333
3 2020-09-28 2020-10-04 India 120 0.500000
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