熊猫数据框 groupby 并填充第一行值

Question

我有一个这样的df，

df = pd.DataFrame({
    "Name" : ["A","B","C","D","E","F","G"],
    "part number" : ["1","3","2","1","5","1","2"],
    "detail1" : ["A","C","B","B","E","E","E"],
    "detail2" : ["one","three","two","two","five","five","five"]
})


df
Name    part number detail1 detail2
A           1           A   one
B           3           C   three
C           2           B   two
D           1           B   two
E           5           E   five
F           1           E   five
G           2           E   five

我想按零件编号分组，并用第一行值填充 detail1 和 detail2。

我的预期输出，

Name    part number detail1 detail2
A       1           A       one
B       3           C       three
C       2           B       two
D       1           A       one
E       5           E       five
F       1           A       one
G       2           B       two

我试过了，df.groupby("part number")[["detail1","detail2"]].first() 但没有给出预期的输出，请帮忙。

Answer 1

在part number 上使用groupby 并使用first 转换列detail1、detail2 并将转换后的列分配回df：

cols = ['detail1', 'detail2']
df[cols] = df.groupby('part number')[cols].transform('first')

结果：

print(df)
  Name part number detail1 detail2
0    A           1       A     one
1    B           3       C   three
2    C           2       B     two
3    D           1       A     one
4    E           5       E    five
5    F           1       A     one
6    G           2       B     two