Replace value in column in pandas dataframe based on another column value in same row?

Question

I have a dataframe with two columns. Column A contains values 0 and 1 and column B contains values 0 and 99. Like so:

    df = pd.DataFrame({'A': [0,0,0,1,1,0,0,1,1,0], 
                   'B': [99,1,0,99,99,1,1,99,99,99]})

   A   B
0  0  99
1  0   1
2  0   0
3  1  99
4  1  99
5  0   1
6  0   1
7  1  99
8  1  99
9  0  99

I need to replace all values of 99 with 0s within column B when the corresponding value of column A is 1, and I tried this:

    df = df[df['A']==1].replace({'B': {99: 0}})

   A  B
3  1  0
4  1  0
7  1  0
8  1  0

but when trying this, I lose the portion of the dataframe where A is 0. How can I perform this without losing that portion?

why you have a df['A']==1? you didn't had anything indicating if B=99 be updated when A is 1? — Naveed
– Naveed, Commented Oct 7, 2022 at 19:31
just edited question to reflect that, realized I forgot to mention that aspect. — Luke Haws
– Luke Haws, Commented Oct 7, 2022 at 19:39
This question is similar to: Change values in one column on the basis of the values in another column. If you believe it’s different, please edit the question, make it clear how it’s different and/or how the answers on that question are not helpful for your problem. — robertspierre
– robertspierre, Commented May 5 at 17:04

Naveed · Accepted Answer · 2022-10-07 19:46:47Z

2

here is one way to do it

using Loc
df.loc[(df['A']== 1) & (df['B']==99), 'B'] = 0
df

OR

# using mask
df['B']= df['B'].mask((df['A']== 1) & (df['B']==99), 0)
df

edited Oct 7, 2022 at 19:46

answered Oct 7, 2022 at 19:27

Naveed

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2 Comments

Luke Haws Over a year ago

realized my initial question did not mention I need to only change B's value when A's corresponding value is 1, not 0. I apologize

Luke Haws Over a year ago

thank you Naveed! mask solution worked for the edit as well

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