Use the interpolate() method to fill NaN values. Let’s say the following is our CSV file opened in Microsoft Excel with some NaN values −

Load data from a CSV file into a Pandas DataFrame −
dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\SalesData.csv")Fill NaN values with interpolate() −
dataFrame.interpolate()
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)
# fill NaN values with interpolate()
res = dataFrame.interpolate()
print("\nDataFrame after interpolation...\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 interpolation... Car Reg_Price Units 0 BMW 2500 100.0 1 Lexus 3500 110.0 2 Audi 2500 120.0 3 Jaguar 2000 115.0 4 Mustang 2500 110.0