Python Warm Up

Python Exercise on Google Colab

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In this exercise, we will take a look at some basic Python Concepts needed for day-to-day coding.

Check the installed Python version.

! python --version

Python 3.7.6

Simple For Loop

for i in range(10):
  print(i)

0
1
2
3
4
5
6
7
8
9

List

list_items = ['a', 'b', 'c', 'd', 'e']

Retrieving an Element

list_items[2]

'c'

Append New Values

list_items.append('f')

list_items

['a', 'b', 'c', 'd', 'e', 'f']

Remove an Element

list_items.remove('a')

list_items

['b', 'c', 'd', 'e', 'f']

Dictionary

dictionary_items = {'a':1, 'b': 2, 'c': 3}

Retrieving an Item by Key

dictionary_items['b']

2

Append New Item with Key

dictionary_items['c'] = 4

dictionary_items

{'a': 1, 'b': 2, 'c': 4}

Delete an Item with Key

del dictionary_items['a'] 

dictionary_items

{'b': 2, 'c': 4}

Comparators

x = 10
y = 20 
z = 30

x > y 

False

x < z

True

z == x

False

if x < z:
  print("This is True")

This is True

if x > z:
  print("This is True")
else:
  print("This is False")  

This is False

Arithmetic

k = x * y * z
k

6000

j = x + y + z
j

60

m = x -y 
m

-10

n = x / z
n

0.3333333333333333

Numpy

Create a Random Numpy Array

import numpy as np

a = np.random.rand(100)
a.shape

(100,)

Reshape Numpy Array

b = a.reshape(10,10)
b.shape

(10, 10)

Manipulate Array Elements

c = b * 10
c[0]

array([3.33575458, 7.39029235, 5.54086921, 9.88592471, 4.9246252 ,
       1.76107178, 3.5817523 , 3.74828708, 3.57490794, 6.55752319])

c = np.mean(b,axis=1)
c.shape

10

print(c)

[0.60673061 0.4223565  0.42687517 0.6260857  0.60814217 0.66445627 
  0.54888432 0.68262262 0.42523459 0.61504903]