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This time I will bring you numpy.deleteHow to delete a column, what are the precautions for numpy.delete to delete a column, the following is a practical case, let's take a look.
Basic introduction:
numpy.delete numpy.delete(arr, obj, axis=None)[source] Return a new array with sub-arrays along an axis deleted. For a one dimensional array, this returns those entries not returned by arr[obj]. Parameters: arr : array_like Input array. obj : slice, int or array of ints Indicate which sub-arrays to remove. axis : int, optional The axis along which to delete the subarray defined by obj. If axis is None, obj is applied to the flattened array. Returns: out : ndarray A copy of arr with the elements specified by obj removed. Note that delete does not occur in-place. If axis is None, out is a flattened array.
Example:
1. Delete one column
>>> dataset=[[1,2,3],[2,3,4],[4,5,6]] >>> import numpy as np >>> dataset = np.delete(dataset, -1, axis=1) >>> dataset array([[1, 2], [2, 3], [4, 5]])
2. Delete multiple columns
arr = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]]) np.delete(arr, [1,2], axis=1) array([[ 1, 4], [ 5, 8], [ 9, 12]])
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