Python Pandas - Replace all NaN elements in a DataFrame with 0s

To replace NaN values, use the fillna() method. Let’s say the following is our CSV file opened in Microsoft Excel with some NaN values −

At first, import the required library −

import pandas as pd

Load data from a CSV file into a Pandas DataFrame −

dataFrame = pd.read_csv("C:\Users\amit_\Desktop\SalesData.csv")

Replace NaN values with 0s using the fillna() method −

dataFrame.fillna(0)

Example

Following is the code

import pandas as pd # Load data from a CSV file into a Pandas DataFrame dataFrame = pd.read_csv("C:\Users\amit_\Desktop\SalesData.csv") print("DataFrame...\n",dataFrame) # replace NaN values with 0s res = dataFrame.fillna(0) print("\nDataFrame after replacing NaN values...\n",res)

Output

This will produce the following output −

DataFrame...        Car   Reg_Price   Units 0      BMW        2500   100.0 1    Lexus        3500     NaN 2     Audi        2500   120.0 3   Jaguar        2000     NaN 4  Mustang        2500   110.0 DataFrame after replacing NaN values...        Car   Reg_Price   Units 0      BMW        2500   100.0 1    Lexus        3500     0.0 2     Audi        2500   120.0 3   Jaguar        2000     0.0 4  Mustang        2500   110.0