I am new to pandas and I am trying to replace some values on specific columns of a dataframe. My dataframe looks like this:
c1 c2 st mt ast sr c7 c8
0 a a 2 1 4 2 a a
1 b b 3 3 3 3 b b
2 c c 1 1 2 4 c c
3 d d 3 3 1 2 d d
4 e e 2 3 2 1 e e
5 f f 5 5 5 5 f f
in row 1, from columns 2 to 5 (st, mt, ast, sr) I have the number 3 in all columns and row 5 I have the number 5 in all columns. When I subset using the code below and try to replace 3 by 0 and 5 by 0 in these columns, the code return all the values in the row replaced by 0, not only the values in those specific columns. I tried:
df[(df.st == 5) & (df.mt == 5) & (df.ast == 5) & (df.sr == 5)]=0
but I got:
c1 c2 st mt ast sr c7 c8
0 a a 2 1 4 2 a a
1 0 0 0 0 0 0 0 0
2 c c 1 1 2 4 c c
3 d d 3 3 1 2 d d
4 e e 2 3 2 1 e e
5 0 0 0 0 0 0 0 0
I also tried:
df[(df.st == 5) & (df.mt == 5) & (df.ast == 5) & (df.sr == 5)].replace(5,0)
My desired output is:
c1 c2 st mt ast sr c7 c8
0 a a 2 1 4 2 a a
1 b b 0 0 0 0 b b
2 c c 1 1 2 4 c c
3 d d 3 3 1 2 d d
4 e e 2 3 2 1 e e
5 f f 0 0 0 0 f f
How can I achieve this goal?
>Solution :
Use DataFrame.loc with columnsnames in list:
df.loc[(df.st == 5) & (df.mt == 5) & (df.ast == 5) & (df.sr == 5), ['st','mt','ast','sr']]=0
Another idea is working with only selected lists with comapare by 5 by DataFrame.eq and test if all values Trues by DataFrame.all:
cols = ['st','mt','ast','sr']
df.loc[df[cols].eq(5).all(axis=1) | df[cols].eq(3).all(axis=1), cols]=0
print (df)
c1 c2 st mt ast sr c7 c8
0 a a 2 1 4 2 a a
1 b b 0 0 0 0 b b
2 c c 1 1 2 4 c c
3 d d 3 3 1 2 d d
4 e e 2 3 2 1 e e
5 f f 0 0 0 0 f f