Python pandas change dataframe value

Question

I am querying a dataframe like below:

>>> df
    A,B,C
    1,1,200
    1,1,433
    1,1,67
    1,1,23
    1,2,330
    1,2,356
    1,2,56
    1,3,30

if I do part_df = df[df['A'] == 1 & df['B'] == 2], I am able to get a sub-dataframe as

 >>> part_df
    A, B, C
    1, 2, 330
    1, 2, 356
    1, 2, 56

Now i wanna make some changes to part_df like:

part_df['C'] = 0

The changes are not reflected in the original df at all. I guess it is because of numpy's array mechanism that everytime a new copy of dataframe is produced. I am wondering how do I query a dataframe with some conditions and makes changes to the selected part as the example I provided and reflect value back to original dataframe in place?

Did you ask me a question, I had something pop up in my inbox but this post doesn't show anything anymore — EdChum
– EdChum, Commented May 22, 2014 at 12:09
@EdChum yeah, I have got a question but managed to solve it later. so I deleted the question. Thanks anyway! — dcc
– dcc, Commented May 22, 2014 at 12:18

EdChum · Accepted Answer · 2014-05-22 07:33:29Z

2

You should do this instead:

In [28]:

df.loc[(df['A'] == 1) & (df['B'] == 2),'C']=0
df
Out[28]:
   A  B    C
0  1  1  200
1  1  1  433
2  1  1   67
3  1  1   23
4  1  2    0
5  1  2    0
6  1  2    0
7  1  3   30

[8 rows x 3 columns]

You should use loc and select the column of interest 'C' in the square brackets at the end

answered May 22, 2014 at 7:33

EdChum

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