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To create a DataFrame from original index but enforce a new index, use the index.to_frame(). Set the parameter index to False.At first, import the required libraries −import pandas as pdCreating Pandas index −index = pd.Index(['Electronics', 'Accessories', 'Decor', 'Books', 'Toys'], name ='Products')Display the Pandas indexprint("Pandas Index...", index) Enforce new index and convert index to DataFrame. Here, the actual index gets replaced by another index −print("Index to DataFrame...", index.to_frame(index=False))ExampleFollowing is the code −import pandas as pd # Creating Pandas index index = pd.Index(['Electronics', 'Accessories', 'Decor', 'Books', 'Toys'], name ='Products') # Display the Pandas index print("Pandas Index...", index) # Return ... Read More
To create a DataFrame with both the original index and name, use the index.to_frame() method in Pandas.At first, import the required libraries −import pandas as pdCreating Pandas index −index = pd.Index(['Electronics', 'Accessories', 'Decor', 'Books', 'Toys'], name ='Products')Display the Pandas index −print("Pandas Index...", index)Convert index to DataFrame −print("Index to DataFrame...", index.to_frame())ExampleFollowing is the code −import pandas as pd # Creating Pandas index index = pd.Index(['Electronics', 'Accessories', 'Decor', 'Books', 'Toys'], name ='Products') # Display the Pandas index print("Pandas Index...", index) # Return the number of elements in the Index print("Number of elements in the index...", index.size) # Return ... Read More
To create a Series with both the original index and name, use the index.to_series() method in Pandas. At first, import the required libraries -import pandas as pdCreating Pandas index:index = pd.Index(['Electronics', 'Accessories', 'Decor', 'Books', 'Toys'], name ='Products')Convert index to series −print("Index to series...", index.to_series())ExampleFollowing is the code −import pandas as pd # Creating Pandas index index = pd.Index(['Electronics', 'Accessories', 'Decor', 'Books', 'Toys'], name ='Products') # Display the Pandas index print("Pandas Index...", index) # Return the number of elements in the Index print("Number of elements in the index...", index.size) # Return the dtype of the data print("The ... Read More
To return a list of the Index values, use the index.to_list() method in Pandas. At first, import the required libraries -import pandas as pdCreating Pandas index −index = pd.Index([50.4, 10.2, 70.5, 110.5, 90.8, 50.6]) Display the Pandas index −print("Pandas Index...", index)Return a list −print("List of the index values...", index.to_list()) ExampleFollowing is the code −import pandas as pd # Creating Pandas index index = pd.Index([50.4, 10.2, 70.5, 110.5, 90.8, 50.6]) # Display the Pandas index print("Pandas Index...", index) # Return the number of elements in the Index print("Number of elements in the index...", index.size) # Return the ... Read More
To create an Index with values cast to dtypes, use the index.astype() method in Pandas. At first, import the required libraries −import pandas as pdCreating Pandas index −index = pd.Index([50.4, 10.2, 70.5, 110.5, 90.8, 50.6]) Display the Pandas index −print("Pandas Index...", index)Convert datatype to int64 −index.astype('int64') ExampleFollowing is the code −import pandas as pd # Creating Pandas index index = pd.Index([50.4, 10.2, 70.5, 110.5, 90.8, 50.6]) # Display the Pandas index print("Pandas Index...", index) # Return the number of elements in the Index print("Number of elements in the index...", index.size) # Return the dtype of the ... Read More
To show which entries in a Pandas Index are not NA, use the index.notna() method. At first, import the required libraries -import pandas as pd import numpy as npCreating Pandas index with some NaN values −index = pd.Index([5, 65, np.nan, 17, 75, np.nan]) Display the Pandas index −print("Pandas Index...", index)Show which entries in a Pandas index are not-NA. Return True for non-NA entries −print("Check which entries are not-NA...", index.notna()) ExampleFollowing is the code −import pandas as pd import numpy as np # Creating Pandas index with some NaN values index = pd.Index([5, 65, np.nan, 17, 75, np.nan]) # ... Read More
To show which entries in a Pandas Index are NA, use the index.isna() in Pandas. At first, import the required libraries -import pandas as pd import numpy as npCreating Pandas index with some NaN values −index = pd.Index([5, 65, np.nan, 17, 75, np.nan]) Display the Pandas index −print("Pandas Index...", index)Show which entries in a Pandas index are NA. Return True for NA entries −print("Check which entries are NA...", index.isna()) ExampleFollowing is the code −import pandas as pd import numpy as np # Creating Pandas index with some NaN values index = pd.Index([5, 65, np.nan, 17, 75, np.nan]) # ... Read More
To drop the value when all levels are NaN in a Multi-index, use the multiIndex.dropna() method. Set the parameter how with value all.At first, import the required libraries -import pandas as pd import numpy as npCreate a multi-index with all NaN values. The names parameter sets the names for the levels in the index −multiIndex = pd.MultiIndex.from_arrays([[np.nan, np.nan], [np.nan, np.nan]], names=['a', 'b'])Drop the value when all levels iareNaN in a Multi-index. With all NaN values, the dropna() will drop all the values, if the "how" parameter of the dropna() is set "all" −print("Dropping the values when all levels are NaN...", ... Read More
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 levels in the index −multiIndex = pd.MultiIndex.from_arrays([[5, 10], [np.nan, 20], [25, np.nan], [35, 40]], names=['a', 'b', 'c', 'd'])Drop the value when any level is NaN in a Multi-index. Even with a single NaN value, the dropna() will drop all the values. The "how" parameter of the dropna() is used with ... 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 Index...", index)Drop only the NaN values −print("The Index object after removing NaN values...", index.dropna())ExampleFollowing is the code −import pandas as pd import numpy as np # Creating Pandas index with some NaN values as well index = pd.Index([50, 10, 70, np.nan, 90, 50, np.nan, np.nan, 30]) # Display ... Read More