5. Primer Functions

Note

This Chapter Primer Functions is for beginner. If you have some Python programming experience, you may skip this chapter.

The following functions have been heavily used in my daily Data Scientist work.

5.1. *

Single asterisk as used in function declaration allows variable number of arguments passed from calling environment. Inside the function it behaves as a tuple.

:: Python Code:

my_list = [1,2,3]
print(my_list)
print(*my_list)

:: Ouput:

[1, 2, 3]
1 2 3

5.2. range

:: Python Code:

print(range(5))
print(*range(5))
print(*range(3,8))

:: Ouput:

range(0, 5)
0 1 2 3 4
3 4 5 6 7

5.3. random

More details can be found at:

  1. random: https://docs.python.org/3/library/random.html#random.randint

  2. np.random: https://docs.scipy.org/doc/numpy/reference/routines.random.html

5.3.1. random.random

:: Python Code:

import random
random.random()

# (b - a) * random() + a
random.uniform(3,8)

:: Ouput:

0.33844051243073625
7.772024014335885

5.3.2. np.random

:: Python Code:

np.random.random_sample()
np.random.random_sample(4)
np.random.random_sample([2,4])

# (b - a) * random_sample() + a
a = 3; b = 8
(b-a)*np.random.random_sample([2,4])+a

:: Ouput:

0.11919402208670005
array([0.07384755, 0.9005251 , 0.30030561, 0.38221819])
array([[0.76851156, 0.56973309, 0.47074505, 0.7814957 ],
       [0.5778028 , 0.94653057, 0.51193493, 0.48693931]])

array([[4.65799262, 6.32702018, 6.55545234, 5.45877784],
       [7.69941994, 4.68709357, 5.49790728, 4.60913966]])

5.4. round

Sometimes, we really do not need the scientific decimals for output results. So you can use this function to round an array to the given number of decimals.

:: Python Code:

np.round(np.random.random_sample([2,4]),2)

:: Ouput:

array([[0.76, 0.06, 0.41, 0.4 ],
       [0.07, 0.51, 0.84, 0.76]])

5.5. TODO..

:: Python Code:

:: Ouput:

:: Python Code:

:: Ouput:

:: Python Code:

:: Ouput:

:: Python Code:

:: Ouput: