如何使用 function 中的行索引和单元格值应用于 dataframe？

Question

I have a table similar to this, with the blank spaces being empty strings and the numbers being floats:

   1   2   3   4   5   6
A  
B                  8   5
C      5       7
D  2   3   5
E  0

I want to replace the value of each cell with the output of a function which takes two arguments: the index of the row and the value of the cell.

For example, the values in the first column should be replaced with the output of func(D, 2) and func(E, 0) and the empty cells should stay empty. The function output is a string.

Expected output table:

if func(D, 2) returns X and func(E, 0) returns Y, then column 1 should look like:

   1   2   3   4   5   6
A  
B                  8   5
C      5       7
D  X   3   5
E  Y

How do I do this?

Answer 1

First of all I would fill the dataframe:

df.fillna(0, inplace=True) 

then let's assume that your function is called func and it's first argument is row index, you can apply it using the map method while iterating over rows:

for idx in df.index:
   df.loc[idx] = df.loc[idx].map(lambda x: func(idx, x))