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 

Python3

# 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

Output:

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

Python3

# 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

Output :

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

Python3

# 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

Output :

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

Python3

# 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

Output :

Example #4: Delete rows from dataFrame in Place

Python3

# 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'])

# dropping a row 'c' & 'd' from actual dataframe
df.drop(['c', 'd'], inplace = True )

df

Output :