计算特定行之间的时间

Question

我的数据框“d”是：

import pandas as pd
d=pd.DataFrame(columns=['Status','t'])

d['Status']=['A','T', 'A','C','C','A','T','A','C','A']
d['t']= pd.to_datetime(['2021-06-12 08:39:24.813000',
'2021-06-12 08:39:24.820000',
'2021-06-12 08:39:25.210000',
'2021-06-12 08:39:25.217000',
'2021-06-12 08:44:28.830000',
'2021-06-12 10:48:10.293000',
'2021-06-12 10:48:10.300000',
'2021-06-12 10:48:10.680000',
'2021-06-12 10:48:10.693000',
'2021-06-12 10:48:11.223000'])

如何获得“Delta”列来计算值对“T”（触发）和“C”（结束）之间的时间差？它应该是这样的：

Answer 1

您可以使用面具：

m1 = d['Status'].eq('T')  # Ts
m2 = d['Status'].eq('C')  # Cs
m3 = d[m1|m2].groupby(m1.cumsum()).cumcount().eq(1) # first C after a T

d.loc[m2&m3, 'Delta'] = d.loc[m1|(m2&m3), 't'].diff()

# if needed
d['Delta'] = d['Delta'].fillna('0')

输出：

  Status                       t                  Delta
0      A 2021-06-12 08:39:24.813                    NaT
1      T 2021-06-12 08:39:24.820                    NaT
2      A 2021-06-12 08:39:25.210                    NaT
3      C 2021-06-12 08:39:25.217 0 days 00:00:00.397000
4      C 2021-06-12 08:44:28.830                    NaT
5      A 2021-06-12 10:48:10.293                    NaT
6      T 2021-06-12 10:48:10.300                    NaT
7      A 2021-06-12 10:48:10.680                    NaT
8      C 2021-06-12 10:48:10.693 0 days 00:00:00.393000
9      A 2021-06-12 10:48:11.223                    NaT

中间体：

  Status                       t     m1     m2  m1_cumsum  cumcount     m3  m2&m3
0      A 2021-06-12 08:39:24.813  False  False          0       NaN    NaN  False
1      T 2021-06-12 08:39:24.820   True  False          1       0.0  False  False
2      A 2021-06-12 08:39:25.210  False  False          1       NaN    NaN  False
3      C 2021-06-12 08:39:25.217  False   True          1       1.0   True   True
4      C 2021-06-12 08:44:28.830  False   True          1       2.0  False  False
5      A 2021-06-12 10:48:10.293  False  False          1       NaN    NaN  False
6      T 2021-06-12 10:48:10.300   True  False          2       0.0  False  False
7      A 2021-06-12 10:48:10.680  False  False          2       NaN    NaN  False
8      C 2021-06-12 10:48:10.693  False   True          2       1.0   True   True
9      A 2021-06-12 10:48:11.223  False  False          2       NaN    NaN  False

Answer 2

日期集：

import pandas as pd

df=pd.DataFrame(columns=['Status','t'])

df['Status']=['A','T', 'A','C','C','A','T','A','C','A']
df['t']= pd.to_datetime(['2021-06-12 08:39:24.813000',
'2021-06-12 08:39:24.820000',
'2021-06-12 08:39:25.210000',
'2021-06-12 08:39:25.217000',
'2021-06-12 08:44:28.830000',
'2021-06-12 10:48:10.293000',
'2021-06-12 10:48:10.300000',
'2021-06-12 10:48:10.680000',
'2021-06-12 10:48:10.693000',
'2021-06-12 10:48:11.223000'])

df
'''
  Status                       t
0      A 2021-06-12 08:39:24.813
1      T 2021-06-12 08:39:24.820
2      A 2021-06-12 08:39:25.210
3      C 2021-06-12 08:39:25.217
4      C 2021-06-12 08:44:28.830
5      A 2021-06-12 10:48:10.293
6      T 2021-06-12 10:48:10.300
7      A 2021-06-12 10:48:10.680
8      C 2021-06-12 10:48:10.693
9      A 2021-06-12 10:48:11.223
'''

代码：

temp = (
    df.loc[df.Status.isin(['T', 'C'])]
    .assign(nxt=lambda x: x.Status != x.Status.shift())
    .query('nxt==True')
    .assign(Delta=lambda x: x.t - x.t.shift())
)
temp
'''
  Status                       t   nxt                  Delta
1      T 2021-06-12 08:39:24.820  True                    NaT
3      C 2021-06-12 08:39:25.217  True 0 days 00:00:00.397000
6      T 2021-06-12 10:48:10.300  True 0 days 02:08:45.083000
8      C 2021-06-12 10:48:10.693  True 0 days 00:00:00.393000
'''

代码：

for index, row in temp.query('Status=="C"').iterrows():
    df.loc[index, 'Delta'] = row.Delta

df
'''
  Status                       t                  Delta
0      A 2021-06-12 08:39:24.813                    NaT
1      T 2021-06-12 08:39:24.820                    NaT
2      A 2021-06-12 08:39:25.210                    NaT
3      C 2021-06-12 08:39:25.217 0 days 00:00:00.397000
4      C 2021-06-12 08:44:28.830                    NaT
5      A 2021-06-12 10:48:10.293                    NaT
6      T 2021-06-12 10:48:10.300                    NaT
7      A 2021-06-12 10:48:10.680                    NaT
8      C 2021-06-12 10:48:10.693 0 days 00:00:00.393000
9      A 2021-06-12 10:48:11.223                    NaT
'''

计算特定行之间的时间

Compute time between specific rows

python

pandas

dataframe