A tip A day – Python Tip #3 – Pandas Apply Function

Apply function takes a function as an argument and execute the function in all the elements of the dataframe.

For example, if we want to create a new column which is the square root of another column’s values or apply a complex function and combine one or more columns or when creating new features using the existing features for feature engineering.

Syntax: df.apply(func, axis=0, broadcast=None, raw=False, reduce=None, result_type=None, args=(), **kwds)

df – a pandas series.

func – A lambda function or a normal function

axis – 0 – rows which is default, 1 – columns

import pandas as pd
import numpy as np


Lets try this using an example.

fruit = {
    'orange' : [3,2,0,1],
    'apples' : [0,3,7,2]
}
df = pd.DataFrame(fruit)
df

Output:

	orange	apples
0	3	0
1	2	3
2	0	7
3	1	2

For example, we need to create a new series by taking square root of another column. The below code does this.

lst= []
print("Original values in Orange column:")
print(df['orange'])
for i in df['orange']:
    lst.append(np.sqrt(i))
    
print("Square root value if Orange column:")
print(lst)

Output:

Original values in Orange column:
0    3
1    2
2    0
3    1
Name: orange, dtype: int64

Square root value if Orange column:
[1.7320508075688772, 1.4142135623730951, 0.0, 1.0]

Apply function simplifies this.

df['orange_sqrt'] = df['orange'].apply(np.sqrt)
df

Output:

	orange	apples	orange_sqrt
0	3	0	1.732051
1	2	3	1.414214
2	0	7	0.000000
3	1	2	1.000000

We have done the same functionality with less code.

Using Lambda function:

df['orange_sq'] = df['orange'].apply(lambda x: x*x)
df

Out[25]:

	orange	apples	orange_sqrt	orange_sq
0	3	0	1.732051	9
1	2	3	1.414214	4
2	0	7	0.000000	0
3	1	2	1.000000	1

Today we learned about Apply function.

Hope you are excited to practice what we have learned now.

We will meet with a new tip in Python. Thank you! 👍

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Happy Programming!🎈