Question

我有一个包含4列的数据框：天，时间， tmin 和 tmax 。 tmin显示当天的 temperature_min ，tmax显示当天的 temperature_max 。我想要的是能够用当天的tmin和tmax填充一天的所有NaN值。例如，我要转换此数据框：

   day time     tmin tmax 
0   01 00:00:00 NaN NaN
1   01 03:00:00 -6.8 NaN
2   01 06:00:00 NaN NaN
3   01 09:00:00 NaN NaN
4   01 12:00:00 NaN NaN
5   01 15:00:00 NaN 1.2
6   01 18:00:00 NaN NaN
7   01 21:00:00 NaN NaN
8   02 00:00:00 NaN NaN
9   02 03:00:00 -7.2 NaN
10  02 06:00:00 NaN NaN
11  02 09:00:00 NaN NaN
12  02 12:00:00 NaN NaN
13  02 15:00:00 NaN 1.8
14  02 18:00:00 NaN NaN
15  02 21:00:00 NaN NaN

此数据框：

       day time     tmin tmax
    0   01 00:00:00 -6.8 1.2
    1   01 03:00:00 -6.8 1.2
    2   01 06:00:00 -6.8 1.2
    3   01 09:00:00 -6.8 1.2
    4   01 12:00:00 -6.8 1.2
    5   01 15:00:00 -6.8 1.2
    6   01 18:00:00 -6.8 1.2
    7   01 21:00:00 -6.8 1.2
    8   02 00:00:00 -7.2 1.8
    9   02 03:00:00 -7.2 1.8
    10  02 06:00:00 -7.2 1.8
    11  02 09:00:00 -7.2 1.8
    12  02 12:00:00 -7.2 1.8
    13  02 15:00:00 -7.2 1.8
    14  02 18:00:00 -7.2 1.8
    15  02 21:00:00 -7.2 1.8

Answer 1

使用groupby和transform：

df.assign(**df.groupby('day')[['tmin', 'tmax']].transform('first'))

    day      time  tmin  tmax
0     1  00:00:00  -6.8   1.2
1     1  03:00:00  -6.8   1.2
2     1  06:00:00  -6.8   1.2
3     1  09:00:00  -6.8   1.2
4     1  12:00:00  -6.8   1.2
5     1  15:00:00  -6.8   1.2
6     1  18:00:00  -6.8   1.2
7     1  21:00:00  -6.8   1.2
8     2  00:00:00  -7.2   1.8
9     2  03:00:00  -7.2   1.8
10    2  06:00:00  -7.2   1.8
11    2  09:00:00  -7.2   1.8
12    2  12:00:00  -7.2   1.8
13    2  15:00:00  -7.2   1.8
14    2  18:00:00  -7.2   1.8
15    2  21:00:00  -7.2   1.8

或者，如果您想修改原始DataFrame而不是返回副本：

df[['tmin', 'tmax']] = df.groupby('day')[['tmin', 'tmax']].transform('first')

Answer 2

只需将https://angular.io/guide/component-interaction与前向填充和后向填充参数一起使用：

df.tmin = df.groupby('day')['tmin'].fillna(method='ffill').fillna(method='bfill')
df.tmax = df.groupby('day')['tmax'].fillna(method='ffill').fillna(method='bfill')

Answer 3

如果您不希望这样做像@ user3483203那样整洁！

import pandas as pd
myfile = pd.read_csv('temperature.txt', sep=' ')
mydata = pd.DataFrame(data = myfile)

for i in mydata['day']:
    row_start = (i-1) * 8 # assuming 8 data points per day
    row_end = (i) * 8
    mydata['tmin'][row_start:row_end] = pd.DataFrame.min(tempdata['tmin'][row_start:row_end], skipna=True)
    mydata['tmax'][row_start:row_end] = pd.DataFrame.max(tempdata['tmax'][row_start:row_end], skipna=True)

Answer 4

由于您未发布任何代码，因此，这是一个常规解决方案：

    Step 1: Create variables that will keep track of the min and max temps
    Step 2: Loop through each row in the frame
    Step 3: For each row, check if the min or max == "NaN"
    Step 4: If it is, replace with the value of the min or max variable we created earlier

如何使用熊猫用当天的温度_最小值和温度_最大值填充一天的其余时间？

4 个答案: