Filter Pandas DataFrame Based on Index

Last Updated : 23 Mar, 2022

In this article, we are going to see how to filter Pandas Dataframe based on index. We can filter Dataframe based on indexes with the help of filter(). This method is used to Subset rows or columns of the Dataframe according to labels in the specified index. We can use the below syntax to filter Dataframe based on index.

Syntax: DataFrame.filter ( items=None, like=None, regex=None, axis=None )

Parameters:

items : List of info axis to restrict to (must not all be present).
like : Keep info axis where “arg in col == True”
regex : Keep info axis with re.search(regex, col) == True
axis : The axis to filter on. By default this is the info axis, ‘index’ for Series, ‘columns’ for DataFrame

Returns : This method is return same type of object as input object.

Example 1:

The following program is to understand how to filter Dataframe based on numeric value indexes.

Python

# import pandas
import pandas as pd

# define data
data = {"Name": ["Mukul", "Suraj", "Rohit",
                 "Rahul", "Mohit", "Nishu",
                 "Rishi", "Manoj", "Mukesh", 
                 "Rohan"],
        "Age": [22, 23, 25, 21, 27, 24, 26,
                23, 21, 27],
        "Qualification": ["BBA", "BCA", "BBA", 
                          "BBA", "MBA", "BCA",
                          "MBA", "BBA", "BCA", 
                          "MBA"]
        }

# define dataframe
df = pd.DataFrame(data, columns=['Name', 'Age', 'Qualification'])

# display original dataframe
print("\n Original Dataframe \n", df)

# filter 5 index value
df_1 = df.filter(items=[5], axis=0)

# display result
print("\n Display only 5 index value \n", df_1)

# filter only 5 and 8  index value
df_2 = df.filter(items=[5, 8], axis=0)

# display result
print("\n Display only 5 and 8 index value \n", df_2)

Output:

Example 2:

The following program is to know how to filter Dataframe based on non-numeric value indexes.

Python

# import pandas
import pandas as pd

# define data
data = {"Name": ["Mukul", "Suraj", "Rohit",
                 "Rahul", "Mohit"],
        "Age": [22, 23, 25, 21, 27],
        "Qualification": ["BBA", "BCA", "BBA",
                          "BBA", "MBA"]
        }

# define dataframe
df = pd.DataFrame(data, columns=['Name', 'Age', 'Qualification'], index=[
                  'Person_A', 'Person_B', 'Person_C', 'Person_D', 'Person_E'])

# display original dataframe
print("\n Original Dataframe \n", df)

# filter Person_B index value
df_1 = df.filter(items=['Person_B'], axis=0)

# display result
print("\n Display only Person_B index value \n", df_1)

# filter only Person_B and Person_D index value
df_2 = df.filter(items=['Person_B', 'Person_D'], axis=0)

# display result
print("\n Display Person_B and Person_D index value \n", df_2)

Output:

Example 3:

The following program is to understand how to filter Dataframe for indexes that contain a specific string.

Python

# import pandas
import pandas as pd

# define data
data = {"Name": ["Mukul", "Suraj", "Rohit", 
                 "Rahul", "Mohit"],
        "Age": [22, 23, 25, 21, 27],
        "Qualification": ["BBA", "BCA", "BBA", 
                          "BBA", "MBA"]
        }

# define dataframe
df = pd.DataFrame(data, columns=['Name', 'Age', 'Qualification'], index=[
                  'Person_A', 'Person_B', 'Person_AB', 'Person_c', 'Person_AC'])

# display original dataframe
print("\n Original Dataframe \n", df)

# filter index that contain Person_A string.
df_1 = df.filter(like='Person_A', axis=0)

# display result
print("\n display index that contain Person_A string \n", df_1)

Output

Example 4:

The following program is to know how to filter Dataframe for indexes that contain a specific character.

Python

# import pandas
import pandas as pd

# define data
data = {"Name": ["Mukul", "Suraj", "Rohit",
                 "Rahul", "Mohit"],
        "Age": [22, 23, 25, 21, 27],
        "Qualification": ["BBA", "BCA", "BBA",
                          "BBA", "MBA"]
        }

# define dataframe
df = pd.DataFrame(data, columns=['Name', 'Age', 'Qualification'], index=[
                  'Person_A', 'Person_B', 'Person_AB', 'Person_C', 'Person_BC'])

# display original dataframe
print("\n Original Dataframe \n", df)

# filter index that contain an specific character.
df_1 = df.filter(like='B', axis=0)

# display result
print("\n display all indexes that contain Specific character \n", df_1)

Output

Label-based indexing to the Pandas DataFrame

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Filter Pandas DataFrame Based on Index

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