In this python pandas program, we will replace NaNs with the median value using the pandas library.
Steps to solve the program
- Import pandas library as pd.
- Create a dataframe using pd.DataFrame().
- Now replace the NaN values in the age column with the median value of the same column using df[‘Age’].fillna(df[‘Age’].median(),inplace=True).
- Print the output.
import pandas as pd
import numpy as np
df = pd.DataFrame({'Sr.no.':[1,2,3,4],
'Name':['Alex','John','Peter','Klaus'],
'Age':[30,np.nan,29,22]})
print("Original Dataframe: \n",df)
df['Age'].fillna(df['Age'].median(),inplace=True)
print("After replacing missing values by mean: \n",df)
Output :
Original Dataframe:
Sr.no. Name Age
0 1 Alex 30.0
1 2 John NaN
2 3 Peter 29.0
3 4 Klaus 22.0
After replacing missing values by mean:
Sr.no. Name Age
0 1 Alex 30.0
1 2 John 29.0
2 3 Peter 29.0
3 4 Klaus 22.0
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