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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Accessing a value in a NumPy 2D array
schedule Mar 5, 2023Last updated
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To access a value in a Numpy 2D array, use the
Suppose we have the following 2D Numpy array:
x = np.array([[1,2,3], [4,5,6]])xarray([[1, 2, 3],[4, 5, 6]])
Accessing a value
To access the value residing at row 0 column 1 (i.e. the value 2):
To access the value residing at row 1 column 2 (i.e. the value 6):
Do not use
In this previous code snippet, we could have used
x instead of
x[1,2], which would also return the value 6. However, it is not good practice to use double
s in Numpy.
x involves two steps: firstly accessing row 1 (i.e.
[4,5,6]), and then accessing the 2nd index (i.e. 6). On the other hand,
x[1,2] involves just one step, that is, the value is directly fetched, and is therefore faster than double
Published by Isshin Inada
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