To alter index name, use the index.rename() method in Pandas. At first, import the required libraries −import pandas as pdCreating Pandas index −index = pd.Index(['Car', 'Bike', 'Airplane', 'Ship', 'Truck', 'Suburban'], name ='Transport') Display the Pandas index −print("Pandas Index...", index)Rename the index −print("Rename the index...", index.rename('Mode_of_Transport')) ExampleFollowing is the code −import ... Read More

To return the maximum value of the Pandas Index, use the index.max() method. At first, import the required libraries -import pandas as pdCreating Pandas indexindex = pd.Index([10, 20, 70, 40, 90, 50, 25, 30]) Display the Pandas index −print("Pandas Index...", index)Get the maximum value −print("Maximum value..", index.max()) ExampleFollowing is the ... Read More

To return the minimum value of the Pandas Index, use the index.min() method. At first, import the required libraries -import pandas as pdCreating Pandas index −index = pd.Index([10.5, 20.4, 40.5, 25.6, 5.7, 6.8, 30.8, 50.2]) Display the Pandas index −print("Pandas Index...", index)Get the minimum value −print("Minimum value..", index.min()) ExampleFollowing is ... Read More

To check if the Pandas Index is of the object dtype, use the index.is_object() method. At first, import the required libraries -import pandas as pdCreating Pandas index −index = pd.Index(["Electronics", 6, 10.5, "Accessories", 25.6, 30]) Display the Pandas index −print("Pandas Index...", index)Check whether index values has object dtype −print("Is the ... Read More

To check if the Pandas Index only consists of numeric data, use the index.is_numeric() method. At first, import the required libraries -import pandas as pd import numpy as npCreating Pandas index with integer, float and NaNsindex = pd.Index([5, 10.2, 25, 50, 75.2, 100, np.nan]) Display the Pandas index −print("Pandas Index...", ... Read More

To check if the Pandas Index with some NaNs is a floating type, use the index.is_floating() method. At first, import the required libraries −import pandas as pd import numpy as npCreating Pandas index with some NaNs −index = pd.Index([5.7, 6.8, 10.5, np.nan, 17.8, 25.6, np.nan ,np.nan, 50.2]) Display the Pandas ... Read More

To check if the Pandas Index holds Interval objects, use the index.is_interval() method in Pandas.At first, import the required libraries -import pandas as pdCreate Interval objects −interval1 = pd.Interval(10, 30) interval2 = pd.Interval(30, 50)Display the intervals −print("Interval1...", interval1) print("Interval2...", interval2)Creating Pandas index with Interval object1 and 2 −index = pd.Index([interval1, ... Read More

To check if the Pandas Index is a floating type, use the index.is_floating() method in Pandas. At first, import the required libraries -import pandas as pdCreating Pandas index −index = pd.Index([5.7, 6.8, 10.5, 20.4, 25.6, 30.8, 40.5, 50.2]) Display the Pandas index −print("Pandas Index...", index)Check whether index values have only ... Read More

To check if the Pandas Index holds categorical data, use the index.is_categorical() method in Pandas. At first, import the required libraries -import pandas as pdCreating Pandas index with type set as category using the astype() method −index = pd.Index(["Electronics", "Accessories", "Furniture"]).astype("category") Display the Pandas index −print("Pandas Index...", index)Check whether index ... Read More

To check if the Pandas Index only consists of booleans, use the index.is_boolean() method in Pandas. At first, import the required libraries -import pandas as pdCreating Pandas indexindex = pd.Index([True, True, False, False, True, True, True]) Display the Pandas index −print("Pandas Index...", index)Check whether index values have only booleans −print("Index ... Read More