Create a categorical column based on different binary columns in python

Question

I have a dataset that looks like this:

df = pd.DataFrame(data= [[0,0,1],[1,0,0],[0,1,0]], columns = ['A','B','C'])

    A   B   C
0   0   0   1
1   1   0   0
2   0   1   0

I want to create a new column where on each row appears the value of the previous column where there is a 1:

    A   B   C value
0   0   0   1   C
1   1   0   0   A
2   0   1   0   B

Scott Boston · Accepted Answer · 2018-10-18 15:02:10Z

3

Use dot:

df['value'] = df.values.dot(df.columns)

Output:

   A  B  C value
0  0  0  1     C
1  1  0  0     A
2  0  1  0     B

answered Oct 18, 2018 at 15:02

Scott Boston

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Comments

jpp · Accepted Answer · 2018-10-18 15:01:54Z

2

df['value'] = df.idxmax(1)

print(df)

   A  B  C value
0  0  0  1     C
1  1  0  0     A
2  0  1  0     B

answered Oct 18, 2018 at 15:01

jpp

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