Python - How to drop the null rows from a Pandas DataFrame

To drop the null rows in a Pandas DataFrame, use the dropna() method. Let’s say the following is our CSV file with some NaN i.e. null values −

Let us read the CSV file using read_csv(). Our CSV is on the Desktop −

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

Remove the null values using dropna() −

dataFrame = dataFrame.dropna() 

Example

Following is the complete code −

import pandas as pd # reading csv file dataFrame = pd.read_csv("C:\Users\amit_\Desktop\CarRecords.csv") print("DataFrame...\n",dataFrame) # count the rows and columns in a DataFrame print("\nNumber of rows and column in our DataFrame = ",dataFrame.shape) dataFrame = dataFrame.dropna() print("\nDataFrame after removing null values...\n",dataFrame) print("\n(Updated) Number of rows and column in our DataFrame = ",dataFrame.shape) 

Output

This will produce the following output −

DataFrame...            Car       Place   UnitsSold 0         Audi   Bangalore        80.0 1      Porsche      Mumbai       110.0 2   RollsRoyce        Pune         NaN 3          BMW       Delhi       200.0 4     Mercedes   Hyderabad        80.0 5  Lamborghini  Chandigarh         NaN 6         Audi      Mumbai         NaN 7     Mercedes        Pune       120.0 8  Lamborghini       Delhi       100.0 Number of rows and column in our DataFrame = (9, 3) DataFrame after removing null values...            Car      Place   UnitsSold 0         Audi  Bangalore        80.0 1      Porsche     Mumbai       110.0 3          BMW      Delhi       200.0 4     Mercedes  Hyderabad        80.0 7     Mercedes       Pune       120.0 8  Lamborghini      Delhi       100.0 (Updated) Number of rows and column in our DataFrame = (6, 3)