Python 和 Pandas：如果键值匹配，则将值从非 NaN 单元格复制到 Nan 单元格

Question

I'm new to python and Pandas and I encountered this issue.

so, if I have 4 columns and some rows

A.	B.	C.	D.
Q50.	12.	34	xy
Q50.	23.	NaN.	NaN
Q52.	01.	50.	CAT

I want if A is matching (Q50 in row 1 and row 2) to copy all values from row 1 to row 2 (in this example) values to the NaN.

so I will have:

A.	B.	C.	D.
Q50.	12.	34	xy
Q50.	23.	34	xy
Q52.	01.	50.	CAT

I'm wondering if there is a way to use np.where() where I can say if column A's value exists in my dataframe (row 2 where I have NaNs and row 1 where all cells are filled) then set all NaN in row 2 to equal row 1.

EDIT ----- based on a request:

when I run df.head().to_dict()

{'A': {0: Q50', 1: 'Q52' 2: 'Q50'}, 'B': {0: '12', 1: '01', 2: '23'}, 'C': {0:'34', 1: '50', 2: 'NaN'} 'D': {0: 'xy', 1: 'CAT', 2: 'NaN'}}

Answer 1

Use:

df.groupby('A.').apply(lambda x: x.ffill())

or

df.groupby(df['A.'].values).ffill()

output:

     A.    B.    C.   D.
0  Q50.  12.0  34.0   xy
1  Q50.  23.0  34.0   xy
2  Q52.   1.0  50.0  CAT

NB. you can't do df.groupby('A.').ffill() directly as this loses the column 'A.'