PythonNumpyWarmUp.py

# coding: utf-8

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# Handy for matrix manipulations, likE dot product and tranpose

from numpy import *


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# Declare and initialize a 2d numpy array (just call it a matrix, for simplicity)
# This how we will be organizing our data. very simple, and easy to manipulate.

data = array([[1, 2, 3], [1, 2, 3]])
print data


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# Get dimensions of matrix

data.shape


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# Declare and initialize a matrix of zeros

zeros_matrix = zeros((1,2))
print zeros_matrix


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# Declare and initialize a matrix of ones

ones_matrix = ones((1,2))
print ones_matrix


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# Declare and initialize a matrix of random integers from 0-10

rand_matrix = random.randint(10, size = (10, 5))
print rand_matrix


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# Declare and initialize a column vector

col_vector = random.randint(10, size = (10, 1))
print col_vector


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# Access and print the first element of the column vector

print col_vector[0]


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# Change the first element of the column vector

col_vector[0] = 100
print col_vector


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# Access and print the first element of rand_matrix
print rand_matrix[0, 0]


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# Access and print the all rows of first column of rand_matrix
print rand_matrix[:, 0:1]


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# Access and print the all columns of first row of rand_matrix
print rand_matrix[0:1, :]


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# Access the 2nd, 3rd and 5th columns fo the first row rand_matrix
# Get the result in a 2d numpy array
cols = array([[1,2,3]])
print rand_matrix[0, cols]


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# Flatten a matrix
flattened = rand_matrix.T.flatten()
print flattened


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# Dot product
rand_matrix_2 = random.randint(10, size = (5,2))
dot_product = rand_matrix.dot(rand_matrix_2)
print dot_product


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