我想使用我的引用日历作为支架来填充我的主要数据中缺失的数据。为此，我想加入这两个数据框。
import pandas as pd
import numpy as np
d1 = { 'Year': [2019,2019,2019,2019,2019,2019],
'Week': [1,2,3,5,5,6],
'Part': ['A','A','A','A','B','B'],
'Static': [20,20,20,20,40,40],
'Value': [np.nan,10,np.nan,50,30,np.nan] }
d2 = { 'Year':[2019,2019,2019,2019,2019,2019,2019,2019,2019,2019],
'Week':[1,2,3,4,5,6,7,8,9,10] }
df1 = pd.DataFrame(d1)
df2 = pd.DataFrame(d2)
预期输出如下
Year Week Part Static Value
0 2019 1 A 20 NaN
1 2019 2 A 20 10.0
2 2019 3 A 20 NaN
3 2019 4 A 20 NaN
4 2019 5 A 20 50.0
5 2019 6 A 20 NaN
6 2019 7 A 20 NaN
7 2019 8 A 20 NaN
8 2019 9 A 20 NaN
9 2019 10 A 20 NaN
10 2019 1 B 40 NaN
11 2019 2 B 40 NaN
12 2019 3 B 40 NaN
13 2019 4 B 40 NaN
14 2019 5 B 40 30.0
15 2019 6 B 40 NaN
16 2019 7 B 40 NaN
17 2019 8 B 40 NaN
18 2019 9 B 40 NaN
19 2019 10 B 40 NaN
最佳答案
内嵌评论。
# First, replicate `df2` for each unique Part.
df3 = (df2.assign(Key=1)
.merge(pd.DataFrame({'Part': df1.Part.unique(), 'Key': 1}), on='Key')
.drop('Key', 1))
df3
Year Week Part
0 2019 1 A
1 2019 1 B
2 2019 2 A
3 2019 2 B
4 2019 3 A
5 2019 3 B
6 2019 4 A
7 2019 4 B
8 2019 5 A
9 2019 5 B
10 2019 6 A
11 2019 6 B
12 2019 7 A
13 2019 7 B
14 2019 8 A
15 2019 8 B
16 2019 9 A
17 2019 9 B
18 2019 10 A
19 2019 10 B
# Next, perform left outer merge with `df1`.
df3.merge(df1, on=['Year', 'Week', 'Part'], how='left')
Year Week Part Static Value
0 2019 1 A 20.0 NaN
1 2019 1 B NaN NaN
2 2019 2 A 20.0 10.0
3 2019 2 B NaN NaN
4 2019 3 A 20.0 NaN
5 2019 3 B NaN NaN
6 2019 4 A NaN NaN
7 2019 4 B NaN NaN
8 2019 5 A 20.0 50.0
9 2019 5 B 40.0 30.0
10 2019 6 A NaN NaN
11 2019 6 B 40.0 NaN
12 2019 7 A NaN NaN
13 2019 7 B NaN NaN
14 2019 8 A NaN NaN
15 2019 8 B NaN NaN
16 2019 9 A NaN NaN
17 2019 9 B NaN NaN
18 2019 10 A NaN NaN
19 2019 10 B NaN NaN
关于python - 将 pandas DataFrame 与 NaN 合并以查找缺失行，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/54544460/