我正在尝试进行日期计算,以计算熊猫中非日期列中事件之间经过的天数。
我有一个熊猫数据框,看起来像这样:
df = pd.DataFrame({'date':[
'01.01.2020','02.01.2020','03.01.2020','10.01.2020',
'01.01.2020','04.02.2020','20.02.2020','21.02.2020',
'01.02.2020','10.02.2020','20.02.2020','20.03.2020'],
'user_id':[1,1,1,1,2,2,2,2,3,3,3,3],
'other_val':[0,0,0,100,0,100,0,10,10,0,0,10],
'booly':[True, False, False, True,
True, False, False, True,
True, True, True, True]})
现在,我一直无法弄清楚如何为每个用户创建一个新列,以说明在“ booly”列中每个True值之间经过的天数。因此,对于在“ booly”列中具有True的每一行,要等到下一行在“ booly”列中具有True的行发生多少天,就像这样:
date user_id booly days_until_next_booly
01.01.2020 1 True 9
02.01.2020 1 False None
03.01.2020 1 False None
10.01.2020 1 True None
01.01.2020 2 True 51
04.02.2020 2 False None
20.02.2020 2 False None
21.01.2020 2 True None
01.02.2020 3 True 9
10.02.2020 3 True 10
20.02.2020 3 True 29
20.03.2020 3 True None
# sample data
df = pd.DataFrame({'date':[
'01.01.2020','02.01.2020','03.01.2020','10.01.2020',
'01.01.2020','04.02.2020','20.02.2020','21.02.2020',
'01.02.2020','10.02.2020','20.02.2020','20.03.2020'],
'user_id':[1,1,1,1,2,2,2,2,3,3,3,3],
'other_val':[0,0,0,100,0,100,0,10,10,0,0,10],
'booly':[True, False, False, True,
True, False, False, True,
True, True, True, True]})
# convert data to date time format
df['date'] = pd.to_datetime(df['date'], dayfirst=True)
# use loc with groupby to calculate the difference between True values
df.loc[df['booly'] == True, 'days_until_next_booly'] = df.loc[df['booly'] == True].groupby('user_id')['date'].diff().shift(-1)
date user_id other_val booly days_until_next_booly
0 2020-01-01 1 0 True 9 days
1 2020-01-02 1 0 False NaT
2 2020-01-03 1 0 False NaT
3 2020-01-10 1 100 True NaT
4 2020-01-01 2 0 True 51 days
5 2020-02-04 2 100 False NaT
6 2020-02-20 2 0 False NaT
7 2020-02-21 2 10 True NaT
8 2020-02-01 3 10 True 9 days
9 2020-02-10 3 0 True 10 days
10 2020-02-20 3 0 True 29 days
11 2020-03-20 3 10 True NaT
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