NumPy
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Accessing a value in a 2D arrayAccessing columns of a 2D arrayAccessing rows of a 2D arrayCalculating the determinant of a matrixChecking allowed values for a NumPy data typeChecking if a NumPy array is a view or copyChecking the version of NumPyChecking whether a NumPy array contains a given rowComputing Euclidean distance using NumpyConcatenating 1D arraysConverting array to lowercaseConverting type of NumPy array to stringCreating a copy of an arrayDifference between Python List and Numpy arrayDifference between the methods array_equal and array_equivDifference between the methods mod and fmodDifference between the methods power and float_powerFinding the closest value in an arrayFinding the Index of Largest Value in a Numpy ArrayFinding the Index of Smallest Value in a Numpy ArrayFinding the most frequent value in a NumPy arrayFlattening Numpy arraysGetting constant PiGetting elements from a two dimensional array using two dimensional array of indicesGetting indices of N maximum valuesGetting indices of N minimum valuesGetting the number of columns of a 2D arrayGetting the number of non-zero elements in a NumPy arrayGetting the number of rows of a 2D arrayInitializing an array of onesInitializing an array of zerosInitializing an identity matrixLimiting array values to a certain rangePerforming linear regressionPrinting full or truncated NumPy arrayPrinting large Numpy arrays without truncationRemoving rows containing NaN in a NumPy arrayReversing a NumPy arraySaving NumPy array to a fileShape of Numpy ArraysSorting value of one array according to anotherSuppressing scientific notation
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Reversing a NumPy array
schedule Aug 12, 2023
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To reverse a NumPy array use the flipud(~) method for one-dimensional NumPy arrays and fliplr(~) for multi-dimensional NumPy arrays.
Examples
One-dimensional
Consider the following one-dimensional array:
a = np.array([1,2,3])a
array([1, 2, 3])
To reverse the order of the array:
array([3, 2, 1])
Note here that a view object is returned. The view object shares the same memory as the original array meaning that changing one will also change the other. If this is not desired, create a copy of the array before using flipud(~) like so:
copy_a = a.copy()
array([3, 2, 1])
Multi-dimensional
Consider the following multi-dimensional array:
a = np.array([[1,2,3],[4,5,6],[7,8,9]])a
array([[7, 8, 9], [4, 5, 6], [1, 2, 3]])
To reverse the order of the array column-wise (horizontal flip):
array([[3, 2, 1], [6, 5, 4], [9, 8, 7]])
Note that this method is equivalent to np.flip(a, axis=1), where a is the input array.
Published by Arthur Yanagisawa
Edited by 0 others
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