HackerRank Python Solution - Numpy Topic - Mean, Var, and Std

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.

HackerRank Python Solution - Numpy Topic - Min and Max

Min:

The tool min returns the minimum value along a given axis.

import numpy

my_array = numpy.array([[2, 5], 
                        [3, 7],
                        [1, 3],
                        [4, 0]])

print numpy.min(my_array, axis = 0)         #Output : [1 0]
print numpy.min(my_array, axis = 1)         #Output : [2 3 1 0]
print numpy.min(my_array, axis = None)      #Output : 0
print numpy.min(my_array)                   #Output : 0

By default, the axis value is None. Therefore, it finds the minimum over all the dimensions of the input array.

HackerRank Python Solution - Numpy Topic - Sum and Prod

Sum:

The sum tool returns the sum of array elements over a given axis.

import numpy

my_array = numpy.array([ [1, 2], [3, 4] ])

print numpy.sum(my_array, axis = 0)         #Output : [4 6]
print numpy.sum(my_array, axis = 1)         #Output : [3 7]
print numpy.sum(my_array, axis = None)      #Output : 10
print numpy.sum(my_array)                   #Output : 10

By default, the axis value is None. Therefore, it performs a sum over all the dimensions of the input array. 

HackerRank Python Solution - Numpy Topic - Floor, Ceil and Rint

Floor:

The tool floor returns the floor of the input element-wise. The floor of x is the largest integer i where i<=x.

import numpy

my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
print numpy.floor(my_array)         #[ 1.  2.  3.  4.  5.  6.  7.  8.  9.]

Ceil:

The tool ceil returns the ceiling of the input element-wise. The ceiling of x is the smallest integer i where i >= x.

HackerRank Python Solution - Numpy Topic - Shape and Reshape

Shape:

The shape tool gives a tuple of array dimensions and can be used to change the dimensions of an array. 

(a). Using shape to get array dimensions

import numpy

my__1D_array = numpy.array([1, 2, 3, 4, 5])
print my_1D_array.shape     #(5,) -> 1 row and 5 columns

my__2D_array = numpy.array([[1, 2],[3, 4],[6,5]])
print my_2D_array.shape     #(3, 2) -> 3 rows and 2 columns