How to drop rows in Pandas DataFrame by index labels?

Pandas provide data analysts a way to delete and filter data frame using .drop() method. Rows can be removed using index label or column name using this method.

Syntax:
DataFrame.drop(labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors=’raise’)

Parameters:

labels: String or list of strings referring row or column name.
axis: int or string value, 0 ‘index’ for Rows and 1 ‘columns’ for Columns.
index or columns: Single label or list. index or columns are an alternative to axis and cannot be used together.
level: Used to specify level in case data frame is having multiple level index.
inplace: Makes changes in original Data Frame if True.
errors: Ignores error if any value from the list doesn’t exists and drops rest of the values when errors = ‘ignore’

Return type: Dataframe with dropped values



Now, Let’s create a sample dataframe

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# import pandas library
import pandas as pd
   
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya','Shivangi'],
    'Age' : [23, 21, 22,21],
    'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
   
# creating a Dataframe object 
df = pd.DataFrame(details,columns = ['Name','Age','University'],
                  index = ['a', 'b', 'c', 'd'])
   
df

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Output:

pandas-drop-row-1

Example #1: Delete a single Row in DataFrame by Row Index Label

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# import pandas library
import pandas as pd
  
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
    'Age' : [23, 21, 22, 21],
    'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
  
# creating a Dataframe object 
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],
                  index = ['a', 'b', 'c', 'd'])
  
# return a new dataframe by dropping a 
# row 'c' from dataframe
update_df = df.drop('c')
  
update_df

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Output :

drop-rows-2

Example #2: Delete Multiple Rows in DataFrame by Index Labels

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# import pandas library
import pandas as pd
  
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
    'Age' : [23, 21, 22, 21],
    'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
  
# creating a Dataframe object 
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],
                  index = ['a', 'b', 'c', 'd'])
  
# return a new dataframe by dropping a row
# 'b' & 'c' from dataframe
update_df = df.drop(['b', 'c'])
  
update_df

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Output :



pandas-drop-row-3

Example #3: Delete a Multiple Rows by Index Position in DataFrame

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# import pandas library
import pandas as pd
  
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
    'Age' : [23, 21, 22, 21],
    'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
  
# creating a Dataframe object 
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],
                  index = ['a', 'b', 'c', 'd'])
  
# return a new dataframe by dropping a row
# 'b' & 'c' from dataframe using their
# respective index position
update_df = df.drop([df.index[1], df.index[2]])
  
update_df

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Output :

pandas-drop-row

Example #4: Delete rows from dataFrame in Place

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# import pandas library
import pandas as pd
  
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
    'Age' : [23, 21, 22, 21],
    'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
  
# creating a Dataframe object 
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],
                  index = ['a', 'b', 'c', 'd'])
  
# droppping a row 'c' & 'd' from actual dataframe 
df.drop(['c', 'd'], inplace = True )
  
df

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Output :

pandas-drop-row-6

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