如何根据条件为具有缺失值的 pandas dataframe 单元格分配另一个单元格的值？

Question

I have a dataframe that has some missing values. I want to replace those missing values with a value from another cell in the dataframe based on a condition. So the dataframe looks like this:

x	a
xyz	A
lmn	B
None	A
xyz	A
qrs	C
None	B

What I want to do is set the value of the "None" cell to the value in column x when the values in column a match. So that it looks like this:

x	a
xyz	A
lmn	B
xyz	A
xyz	A
qrs	C
lmn	B

The index is just sequential numbers from 0 up and may change depending on the dataset so the index for the cells with the missing information will change.

Answer 1

You can use ffill() to fill forward missing values:

df['x'] = df.replace('None', np.nan).groupby('a')['x'].ffill()
print(df)

# Output:
     x  a
0  xyz  A
1  lmn  B
2  xyz  A
3  xyz  A
4  qrs  C
5  lmn  B

Answer 2

for i in range(len(df)):
    if df['a'][i] == 'A':
        df['x'][i] = 'xyz'

This worked for me, if you want to do all the other letters, just add an elif .