Drop List of Rows from a Pandas DataFrame

April 30, 2023 / Dataframe, Pandas, Python / By

In this article we will discuss how to drop a list of rows from a Pandas DataFrame either by providing row index positions or row names in a list.

A DataFrame is a data structure that will store the data in rows and columns. We can create a DataFrame using pandas.DataFrame() method.

Let’s create a dataframe with 4 rows and 4 columns

import pandas as pd

# Create dataframe for students
df=pd.DataFrame({'id':[58,59,60,61],
                 'name':['sravan','jyothika','preethi','srinadh'],
                 'age':[22,21,22,23],
                 'subjects':['java','php','sql','python']})

# Display the Dataframe
print(df)

Output:

   id      name  age subjects
0  58    sravan   22     java
1  59  jyothika   21      php
2  60   preethi   22      sql
3  61   srinadh   23   python

We are using dataframe.drop() function to remove list of rows from the dataframe. This function is used to drop the rows based on row index / row name in the given dataframe.

Syntax is as follows:

df.drop( axis=0, index=None, columns=None, level=None, inplace=False)

Where, df is the input dataframe and other parameters are,

Frequently Asked:

  • axis = 0 specifies the row position
  • index specifies row index , By default it is None
  • columns are the column names to be specified.
  • inplace is a parameter used to make changes in the dataframe if it is set to true.

It returns the new Dataframe with modified contents of inplace parameter is False, otherwise returns None.

Drop Single Row from Dataframe based on row numbers in a list

Here we are going to drop single row.In a list we are providing the row index

import pandas as pd

# Create dataframe for students
df=pd.DataFrame({'id':[58,59,60,61],
                 'name':['sravan','jyothika','preethi','srinadh'],
                 'age':[22,21,22,23],
                 'subjects':['java','php','sql','python']})

# Display dataframe
print(df)

# Delete the rows by index position given in list
df = df.drop([1])

# Display dataframe
print(df)

Output:

   id      name  age subjects
0  58    sravan   22     java
1  59  jyothika   21      php
2  60   preethi   22      sql
3  61   srinadh   23   python


   id     name  age subjects
0  58   sravan   22     java
2  60  preethi   22      sql
3  61  srinadh   23   python

Here , the second row with index number 1 is removed and displayed the remaining rows.

Drop multiple rows from Dataframe by index positions in List

Here we are going to drop more than one row at a time. In a list we are providing row indices separated by comma. We are also providing axis parameter which sets to 0. It is an optional parameter.

import pandas as pd

# Create Dataframe for students
df=pd.DataFrame({'id':[58,59,60,61],
                 'name':['sravan','jyothika','preethi','srinadh'],
                 'age':[22,21,22,23],
                 'subjects':['java','php','sql','python']})

# Display the Dataframe
print(df)

print("---------------")

# Drop first, second and third row
df = df.drop( [0,1,2], axis=0)

# Display the Dataframe
print(df)

Output:

   id      name  age subjects
0  58    sravan   22     java
1  59  jyothika   21      php
2  60   preethi   22      sql
3  61   srinadh   23   python
---------------
   id     name  age subjects
3  61  srinadh   23   python

Here , the first three rows got removed and displayed the remaining row.

Drop List of Rows from Dataframe using index() with drop()

In this case, we are using index() function inside drop() function to remove the rows based on the index.

Syntax:

df.drop(df.index[index_values])

It takes a list of index positions of rows. and selects those rows only. Then we pass that to drop() function, which deletes those rows in a copy of dataframe and returns that modified copy.

Drop single row

Here we are going to drop single row using index.

Example: In this example, we are going to drop first row

import pandas as pd

# Create dataframe for students
df=pd.DataFrame({'id':[58,59,60,61],
                 'name':['sravan','jyothika','preethi','srinadh'],
                 'age':[22,21,22,23],
                 'subjects':['java','php','sql','python']})

# Display dataframe
print(df)

print("---------------")

# Drop first row
df = df.drop(df.index[0])

# Display dataframe
print(df)

Output:

   id      name  age subjects
0  58    sravan   22     java
1  59  jyothika   21      php
2  60   preethi   22      sql
3  61   srinadh   23   python
---------------
   id      name  age subjects
1  59  jyothika   21      php
2  60   preethi   22      sql
3  61   srinadh   23   python

Drop multiple rows

Here we are going to drop multiple rows using index with slice operator

Syntax:

df.drop(df.index[start:stop])

where,

  • start is the starting index of row.
  • stop is the ending index of row.

Example:

In this example, we are going to drop from first row to third row

#import pandas module
import pandas as pd

# Create dataframe for students
df=pd.DataFrame({'id':[58,59,60,61],
                 'name':['sravan','jyothika','preethi','srinadh'],
                 'age':[22,21,22,23],
                 'subjects':['java','php','sql','python']})

# Display dataframe
print(df)

print("---------------")

# Drop from first row to third row by index
df = df.drop(df.index[0:3])

# Display dataframe
print(df)

Output:

   id      name  age subjects
0  58    sravan   22     java
1  59  jyothika   21      php
2  60   preethi   22      sql
3  61   srinadh   23   python
---------------
   id     name  age subjects
3  61  srinadh   23   python

Drop Rows from Dataframe by List of Row names

Here we are going to use row names inside drop function. This will accept a list of row names to be removed.

Drop single row

Here we are going to specify only one row name inside drop() position.

Syntax:

df.drop(['row_name'])

Example: Here, we are going to drop third row.

import pandas as pd

#create dataframe for students
df=pd.DataFrame({'id':[58,59,60,61],
                 'name':['sravan','jyothika','preethi','srinadh'],
                 'age':[22,21,22,23],
                 'subjects':['java','php','sql','python']},
                 index=['row1','row2','row3','row4'])

# display dataframe
print(df)

print("---------------")

# drop third row
print(df.drop(['row3']))

Output:

      id      name  age subjects
row1  58    sravan   22     java
row2  59  jyothika   21      php
row3  60   preethi   22      sql
row4  61   srinadh   23   python

---------------

      id      name  age subjects
row1  58    sravan   22     java
row2  59  jyothika   21      php
row4  61   srinadh   23   python

Drop multiple rows by List of Row names

Here we are going to specify only multiple row names inside drop() position.

Syntax:

df.drop(['row_name',......,'row_name'])

Example: Here, we are going to drop second and third row.

import pandas as pd

# Create dataframe for students
df=pd.DataFrame({'id':[58,59,60,61],
                 'name':['sravan','jyothika','preethi','srinadh'],
                 'age':[22,21,22,23],
                 'subjects':['java','php','sql','python']},index=['row1','row2','row3','row4'])

# Display dataframe
print(df)

print("---------------")

# Drop second and third row
print(df.drop(['row2','row3']))

Output:

      id      name  age subjects
row1  58    sravan   22     java
row2  59  jyothika   21      php
row3  60   preethi   22      sql
row4  61   srinadh   23   python
---------------
      id     name  age subjects
row1  58   sravan   22     java
row4  61  srinadh   23   python

Summary

We learned about different ways to delete list of rows from Dataframe by row index positions or labels.

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