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Python Articles
Page 561 of 852
Python Pandas - Create an Index with values cast to dtypes
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 MorePython - Show which entries in a Pandas Index are not NA
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 MorePython Pandas - Drop the value when any level is NaN in a Multi-index
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 MorePython Pandas - Return Index without NaN values
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 MorePython Pandas - Fill NaN values with the specified value in an Index object
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, 30]) Display the Pandas index −print("Pandas Index...", index)Fill the NaN with some specific value −print("Index object after filling NaN value...", index.fillna('Amit')) 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, ...
Read MorePython – Remove multiples levels using the level names and return the index
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, 30], [35, 40]], names=['a', 'b', 'c', 'd']) Display the multi-index −print("Multi-index...", multiIndex)Dropping multiple levels using the level names. We have passed the names of the levels to be removed as a parameter −print("Dropping multiple level...", multiIndex.droplevel(['a', 'd'])) ExampleFollowing is the code −import pandas as pd # Create a multi-index ...
Read MorePython – Return index with a level removed
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', 'd']) Dropping a level from the multiindex −print("Dropping a level...", multiIndex.droplevel())ExampleFollowing is the code −import pandas as pd # Create 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', 'd']) ...
Read MorePython Pandas - Return the relative frequency from Index object
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 values using value_counts(). Set the parameter "normalize" to True to get the relative frequency −print("Get the relative frequency by dividing all values by the sum of values...", index.value_counts(normalize=True))ExampleFollowing is the code −import pandas as pd # Creating Pandas index index = pd.Index([50, 10, 70, 110, 90, 50, 110, 90, ...
Read MorePython Pandas - Return unique values in the index
To return unique values in the index, use the index.unique() method in Pandas. At first, import the required libraries -import pandas as pdCreating Pandas index −index = pd.Index([10, 50, 70, 10, 90, 50, 10, 30]) Display the Pandas index −print("Pandas Index...", index)Get the unique values from the index. Unique values are returned in order of appearance, this does NOT sort −index.unique() ExampleFollowing is the code −import pandas as pd # Creating Pandas index index = pd.Index([10, 50, 70, 10, 90, 50, 10, 30]) # Display the Pandas index print("Pandas Index...", index) # Return the number of elements ...
Read MorePython Pandas - Mask and replace NaNs with a specific value
To mask and replace NaNs with a specific value, use the index.putmask() method. Within that, set the index.isna() method.At first, import the required libraries -import pandas as pd import numpy as npCreating Pandas index with some NaNs −index = pd.Index([5, 65, 10, np.nan, 75, np.nan]) Display the Pandas index −print("Pandas Index...", index)Mask and replace NaN index values with a specific value −print("Mask...", index.putmask(index.isna(), 111)) ExampleFollowing is the code −import pandas as pd import numpy as np # Creating Pandas index with some NaNs index = pd.Index([5, 65, 10, np.nan, 75, np.nan]) # Display the Pandas index print("Pandas Index...", ...
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