Replace value in column based on a condition

Question

I have a DF

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Product       Rate      Imputed_rate      min_rate

1              0        10                5
2              0        4                 7
3              0        34                2
4              0        3                 8
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I want to replace the row when Rate=0 ; with the 'min_rate' only if 'Imputed_rate'<min_rate

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What is the best way to do this?

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Desired Output:

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Product       Rate      Imputed_rate      min_rate

1             0         10                5
2             7         4                 7
3             0         34                2
4             8         3                 8
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Answer 1

np.where is your friend https://numpy.org/doc/stable/reference/generated/numpy.where.html

df['Rate'] = np.where(((df['Rate'] == 0) & (df['Imputed_rate'] < df['min_rate'])), df['min_rate'],df['Rate'])

it is basically an if then else for rows in pandas.

Answer 2

Here is another answer without using numpy:

df['Rate'] = df.apply(lambda row: row['min_rate'] if row['Imputed_rate'] < row['min_rate'] else row['Rate'],axis = 1)

#Output:
   Product  Rate  Imputed_rate  min_rate
0        1     0            10         5
1        2     7             4         7
2        3     0            34         2
3        4     8             3         8