To drop the value when any level is NaN in a Multi-index, use the multiIndex.dropna() method. Set the parameter how with value any.At first, import the required libraries -import pandas as pd import numpy as npCreate a multi-index with some NaN values. The names parameter sets the names for the ... Read More

To return Index without NaN values, use the index.dropna() method in Pandas. At first, import the required libraries −import pandas as pd import numpy as npCreating Pandas index with some NaN values as well −index = pd.Index([50, 10, 70, np.nan, 90, 50, np.nan, np.nan, 30]) Display the Pandas index −print("Pandas ... Read More

To fill NaN values with the specified value in an Index object, use the index.fillna() method in Pandas. At first, import the required libraries −import pandas as pd import numpy as npCreating Pandas index with some NaN values as well −index = pd.Index([50, 10, 70, np.nan, 90, 50, np.nan, np.nan, ... Read More

To remove multiples levels using the level names and return the index, use the multiIndex.droplevel(). Set the level names as parameter.At first, import the required libraries -import pandas as pdCreate a multi-index. The names parameter sets the names for the levels in the indexmultiIndex = pd.MultiIndex.from_arrays([[5, 10], [15, 20], [25, ... Read More

To remove a level using the name of the level and return the index, use the multiIndex.droplevel() method in Pandas. Set the name of the level to be removed as parameter.At first, import the required libraries -import pandas as pdCreate a multi-index. The names parameter sets the names for the ... Read More

To return index with a specific level removed, use the multiIndex.droplevel() method in Pandas. At first, import the required libraries -import pandas as pdCreate a multi-index. The names parameter sets the names for the levels in the indexmultiIndex = pd.MultiIndex.from_arrays([[5, 10], [15, 20], [25, 30], [35, 40]], names=['a', 'b', 'c', ... Read More

To return index with a level removed, use the multiIndex.droplevel() method in Pandas. At first, import the required libraries −import pandas as pdCreate a multi-index. The names parameter sets the names for the levels in the index −multiIndex = pd.MultiIndex.from_arrays([[5, 10], [15, 20], [25, 30], [35, 40]], names=['a', 'b', 'c', ... Read More

To set index name for an already created Index object, use the index.set_names() method in Pandas. At first, import the required libraries −import pandas as pdCreating Pandas index −index = pd.Index(["Electronics", "Mobile Phones", "Accessories", "Home Decor", "Books"]) Display the Pandas index −print("Pandas Index...", index)Set the name of index −print("Set the ... Read More

To return a Series containing counts of unique values from Index object considering NaN values as well with the index.value_counts() method. Set the parameter dropna with value False.At first, import the required libraries -import pandas as pd import numpy as npCreating Pandas index with some NaN values as well −index ... Read More

To return the relative frequency from Index object, use the index.value_counts() method with parameter normalize as True.At first, import the required libraries -import pandas as pdCreating Pandas index −index = pd.Index([50, 10, 70, 110, 90, 50, 110, 90, 30]) Display the Pandas index −print("Pandas Index...", index)Get the count of unique ... Read More