Question

例如，我有一个包含两列的datadframe

A                B 
00:01:05         2018-10-10 23:58:10

我想得到第三列C，它是A + B的总和

A                B                             C
00:01:05         2018-10-10 23:58:10           2018-10-10 23:59:15

如果我这样做：

df['C']= df['A'] + df['B']

我明白了

cannot add DatetimeArray and DatetimeArray

Answer 1

这是您的示例数据框，

import numpy as np
import pandas as pd

## Generate Random Data
raw_data=np.random.choice([None,1], (50,8))
raw_data= np.r_[raw_data, np.random.choice([None, 1,2,3], (50,8))]

## Create dataframe from random data
df = pd.DataFrame(raw_data, columns="A, B, D, E, F, G, I, L".split(","))
notnull_counts = (~df.isnull()).sum(axis=1)

## filter rows with your condition
legit_rows = df[((notnull_counts==1) | (notnull_counts==2) | (notnull_counts==8))]
non_legit_rows = df[~((notnull_counts==1) | (notnull_counts==2) | (notnull_counts==8))]

display(legit_rows)

将列sample = pd.DataFrame() sample['A'] = ['00:01:05'] sample['B'] = ['2018-10-10 23:58:10']转换为pd.Timstamp，将B转换为pd.Timedelta，

然后正常添加列

sample['B'] = pd.to_datetime(sample['B'])
sample['A'] = pd.to_timedelta(sample['A'], unit='m')

Answer 2

将列A转换为时间增量to_timedelta，必要时将列B转换为to_datetime：

df = pd.DataFrame({'A':['00:01:05'],
                   'B':['2018-10-10 23:58:10']})

df['C'] = pd.to_timedelta(df['A']) + pd.to_datetime(df['B'])
print (df)
          A                    B                   C
0  00:01:05  2018-10-10 23:58:10 2018-10-10 23:59:15

如果列A中包含python时间：

df['C'] = pd.to_timedelta(df['A'].astype(str)) + pd.to_datetime(df['B'])

对两个日期时间列求和

2 个答案: