How to Remove columns in Numpy array that contains non-numeric values? Last Updated : 25 Oct, 2020 Comments Improve Suggest changes Like Article Like Report Many times we have non-numeric values in NumPy array. These values need to be removed, so that array will be free from all these unnecessary values and look more decent. It is possible to remove all columns containing Nan values using the Bitwise NOT operator and np.isnan() function. Example 1: Python3 # Importing Numpy module import numpy as np # Creating 2X3 2-D Numpy array n_arr = np.array([[10.5, 22.5, np.nan], [41, 52.5, np.nan]]) print("Given array:") print(n_arr) print("\nRemove all columns containing non-numeric elements ") print(n_arr[:, ~np.isnan(n_arr).any(axis=0)]) Output: In the above example, we remove columns containing non-numeric values from the 2X3 Numpy array. Example 2: Python3 # Importing Numpy module import numpy as np # Creating 3X3 2-D Numpy array n_arr = np.array([[10.5, 22.5, 10.5], [41, 52.5, 25], [100, np.nan, 41]]) print("Given array:") print(n_arr) print("\nRemove all columns containing non-numeric elements ") print(n_arr[:, ~np.isnan(n_arr).any(axis=0)]) Output: In the above example, we remove columns containing non-numeric values from the 3X3 Numpy array. Example 3: Python3 # Importing Numpy module import numpy as np # Creating 5X3 2-D Numpy array n_arr = np.array([[10.5, 22.5, 3.8], [23.45, 50, 78.7], [41, np.nan, np.nan], [20, 50.20, np.nan], [18.8, 50.60, 8.8]]) print("Given array:") print(n_arr) print("\nRemove all columns containing non-numeric elements ") print(n_arr[:, ~np.isnan(n_arr).any(axis=0)]) Output: In the above example, we remove columns containing non-numeric values from the 5X3 Numpy array. Comment More infoAdvertise with us Next Article How to Remove columns in Numpy array that contains non-numeric values? vanshgaur14866 Follow Improve Article Tags : Python Python-numpy Python numpy-arrayManipulation Practice Tags : python Similar Reads How to Remove rows in Numpy array that contains non-numeric values? Many times NumPy arrays may contain NaN values that need to be removed to ensure the array is free from unnecessary or invalid data. This can be achieved using the np.isnan() function along with the Bitwise NOT operator. Note that this approach specifically targets NaN values and may not handle othe 2 min read How to remove NaN values from a given NumPy array? In this article, we are going to learn how to remove Nan values from a given array. Nan values are those values that do not have a specific value associated with them or they are different from the type of values that are to be used in the declared array. 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