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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
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