Drop one or multiple rows in Pandas Dataframe

Pandas-drop-data

In this post, we are going to learn how to Drop one or multiple rows in Pandas Dataframe by using the dataframe built-in method drop(). It is used to drop a row or multiple rows from the dataframe by index label or using the column name.

Pandas Dataframe.drop() method

The Dataframe.drop() method drop the specified label row or columns. It removes specified label names and corresponding axis or directly specifying index or column names.

Syntax

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

Parameters

  • label: single or list label that specifies row or column label to drop.
  • axis: It cab be int or string value, 0 ‘index’ for Rows and 1 ‘columns’ for Columns.
  • Index /columns: Alternative to axis.
  • level: index or level name,For MultiIndex, level from which the labels will be removed.
  • inplace : if true amkes chnages in original dataframe else return a copy.
  • errors: It has two values ‘ignore’ or ‘raise’ default is ‘raise’.

1. Drop single row in DataFrame

In this example, we are dropping a row in the dataframe by passing the index label to the drop() method and after deleting it is returning the result dataframe.

Program Example

import pandas as pd
 
Student_dict = {
    'Name': ['Jack', 'Rack', 'Max', 'David'],
    'Marks':[100,100, 100,100],
    'Subject': ['Math', 'Math', 'Music', 'Physic']
}
 
df = pd.DataFrame(Student_dict,index=['R1','R2','R3','R4'])


result_df = df.drop('R1')
print(result_df)

Output

     Name  Marks Subject
R2   Rack    100    Math
R3    Max    100   Music
R4  David    100  Physic

2. Drop mutiple rows in dataframe

In this example, we are passing the multiple index label to drop() method to drop multiple rows from the dataframe.

Program Example

import pandas as pd
 
Student_dict = {
    'Name': ['Jack', 'Rack', 'Max', 'David'],
    'Marks':[100,100, 100,100],
    'Subject': ['Math', 'Math', 'Music', 'Physic']
}
 
df = pd.DataFrame(Student_dict,index=['R1','R2','R3','R4'])
 
result_df  = df.drop(['R2','R4'])
print(result_df)

Output

    Name  Marks Subject
R1  Jack    100    Math
R3   Max    100   Music

3. Drop list of rows by index label in Dataframe

We can pass multiple row index labels as a list to drop() method of dataframe to drop a list of rows from the dataframe. We have passed the inplace=’True’ argument because we do not want to return a new dataframe changing in the original dataframe.

Program Example

import pandas as pd
 
Student_dict = {
    'Name': ['Jack', 'Rack', 'Max', 'David'],
    'Marks':[100,100, 100,100],
    'Subject': ['Math', 'Math', 'Music', 'Physic']
}
 
df = pd.DataFrame(Student_dict,index=['R1','R2','R3','R4'])
 
df.drop(['R2','R4','R1'],inplace=True)
print(df)

Output

  Name  Marks Subject
R3  Max    100   Music

4. Drop mutiple rows by index range in dataframe

To drop a range of rows from the dataframe we can pass a range of index to drop() method and it will drop rows in a given index range as we are doing in the below example.

Program Example

import pandas as pd
 
Student_dict = {
    'Name': ['Jack', 'Rack', 'Max', 'David'],
    'Marks':[100,100, 100,100],
    'Subject': ['Math', 'Math', 'Music', 'Physic']
}
 
df = pd.DataFrame(Student_dict,index=['R1','R2','R3','R4'])
 
df.drop(df.index[1:3],inplace=True)

print(df)

Output

     Name  Marks Subject
R1   Jack    100    Math
R4  David    100  Physic

Summary

In this post, we have learned to Drop one or multiple rows in Pandas Dataframe with code example by using the dataframe inbuilt drop() method by using the above mention way single or multiple rows can be drop at once.

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