Pandas : Select rows from dataframe having equal value_counts of a specific column

Question

I have the following dataframe:

df

    Place  Target
1    A       0
2    B       0
3    C       1
4    B       0
5    F       1
6    Z       0

df['Target'].value_counts()

0   4
1   2

What I want is to a new df with the same value_count for all the column values and I want it to be equal to the minority one (here, it’s 2).

One desired df would look like:

df2

    Place   Target
1     A       0
2     B       0
3     C       1
5     F       1

df2['Target'].value_counts()

0   2
1   2

Note that the selection (or suppression) process can be done randomly.
Thank you for your help!

Asked By: chessPL

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Source

Answer 1

Here’s a solution using groupby and head:

df = pd.DataFrame({'Place': ['A', 'B', 'C', 'B', 'F', 'Z'], 'Target': [0, 0, 1, 0, 1 , 0]})

v_counts = df.Target.value_counts()
minimum = min(v_counts)

df2 = df.groupby('Target').head(minimum)

Output:

  Place  Target
0     A       0
1     B       0
2     C       1
4     F       1

Answered By: Tobias Molenaar

Pandas : Select rows from dataframe having equal value_counts of a specific column

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