Shape and Reshape HackerRank
import numpy
arr = numpy.array(input().split(),dtype=int)
print(arr.reshape(3,3))
Sampleinput:
1 2 3 4 5 6 7 8 9Sample output:[[1 2 3]
[4 5 6]
[7 8 9]]Mean, Var, and Std in numpy HackerRank
mean The mean tool computes the arithmetic mean along the specified axis. import numpy my_array = numpy.array([ [1, 2], [3, 4] ]) print numpy.mean(my_array, axis = 0) #Output : [ 2. 3.] print numpy.mean(my_array, axis = 1) #Output : [ 1.5 3.5] print numpy.mean(my_array, axis = None) #Output : 2.5 print numpy.mean(my_array) #Output : 2.5 By default, the axis is None . Therefore, it computes the mean of the flattened array. var The var tool computes the arithmetic variance along the specified axis. import numpy my_array = numpy.array([ [1, 2], [3, 4] ]) print numpy.var(my_array, axis = 0) #Output : [ 1. 1.] print numpy.var(my_array, axis = 1) #Output : [ 0.25 0.25] print numpy.var(my_array, axis = None) #Output : 1.25 print numpy.var(my_array) #Output : 1.25 By default, the axis is None . Therefore, it computes the variance of the flattened array. std The std ...
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