Python for data science

Operations:

Output: Sample prints

print(5 + 5) #Addition

print(5 - 5) # subtraction

print(3 * 5) # Multiplication

print(10 / 2) #Division

print(18 % 7) #Modulo

print(4 ** 2) #exponentiation

# How much is your INR 100 worth after 7 years at the rate of interest per year is 10%?

print(100 * 1.1 ** 7)

Variables:

Str -  “sangeeth”, ‘gowtham’

Bool - True /False

Int – 1, 9

Float – 1.98, 8.78

Function: Type() - //to find unknown type of variables

List:

My_list = []

Ex:

= [1, 3, 4, 2]

= [[1, 2, 3], [4, 5, 7]]

= [1 + 2, "a" * 5, 3] = [3,aaa,3]

= ["room1", 11.2478, "room2", 8.459, "room3", 74.56, "room4", 74.698, "room5", 10.25]

Subset listing:

List Index get:  [0,1,2,3…] (Asc),  [….-3,-2,-1] [Desc]

List Slicing:  [Start (inclusive) : End (exclusive)]

My_list = ["room1", 11.2478, "room2", 8.459, "room3", 74.56, "room4", 74.698, "room5", 10.25]

Get_First_6list = My_list [:6] or Get_First_6list = My_list [1:6] or Get_last_list = My_list[6:]

Sub setting lists of lists:

My_list = [["a", "b", "c"], ["d", "e", "f"], ["g", "h", "i"]]

My_list[2][0]

My_list[2][:2]

List Manipulation:

My_list = ["room1", 11.2478, "room2", 8.459, "room3", 74.56, "room4", 74.698, "room5", 10.25]

To update list

My_list[<index position>] = “room5” or 9.897

Adding to new list by amending

My_list_1 = My_list + [“room6”, 24.5896]

Delete list

del(My_list [10]); del(My_list [11])

del(My_list [10:11])

del(My_list [-4:-2])

del(My_list [-3]); del(My_list [-4])

                Assigning one list to another

                                My_list _Copy = My_list (Note: while update My_list_copy it will affect My_list)

My_list_copy1 = My_list [:] (Note: This will copy all list values from My_list, but while update My_list_copy1 it will affect My_list)

Functions:

Max

Min

Sorted

len

Complex

Help(<functionName>) – to get details for function and arguments

Methods:

Upper (Ex: <StrVariables>.upper()), Count (Ex: <Variables>.count(..))

print(<list>.index(20.0)) – Index position finding

print(<list>.count(9.50)) – getting count of repeated times in list values

append(), that adds an element to the list it is called on,

remove(), that removes the first element of a list that matches the input, and

reverse(), that reverses the order of the elements in the list it is called on.

Packages:

import math

import numpy

from math import radians (Note: To import radians function from math package)

from scipy.linalg import inv as my_inv (Note: Suppose you want to use the function inv(), which is in the linalg subpackage of the scipy package)

Numpy: (Numeric Python)

Adv:

Powerful

Collection of values

Hold different types

Change add remove

Data Science

                Mathematical operation over collection

                Speed

NumPy array:

                Calculation over entire arrays

                Easy and fast for complex calculation

Syntax: Example

import numpy as np

np_array1 = np.array(array1)

Manipulation with np array = np_array1 + np_array2 (+, _ ,*, /, **)

Ex:

height = [180, 175, 165, 168, 189, 195]

weight = [74, 52, 42, 85, 96, 53]

import numpy as np

np_height = np.array(height)

print(np_height)

np_height_m = np_height * 0.0254

print(np_height_m)

np_height_m = np.array(height) * 0.0254

np_weight_kg = np.array(weight) * 0.453592

bmi = np_weight_kg / np_height_m ** 2

print(bmi[light])

2D – NumPy Array

N dimensional array

My_list = [[180, 78.4],           

           [215, 102.7],           

           [210, 98.5],           

           [188, 75.2]]

import numpy as np

np_ My_list = np.array(My_list)

print(type(np_My_list))

print(np_My_list.shape)

Output:

<class 'numpy.ndarray'>

(4, 2) (Shape will return total size of array (row, column))

               

Ex:

# Print out the 4th row of np_My_list

print(np_My_list [4,:])

# Select the entire second column of np_My_list

np_array1 np_My_list [:,1]

# Print out value of 3th player

print(np_baseball[2, 0])

Output:

[ 70 195]

75

Basic statistics:

Data Analysis: