1 Introduction to Python (1)

Question 1

1 What is Python?

Answer 1

A general-purpose programming language

Question 2

2 What is Data Science?

Answer 2

An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data

Question 3

3 Data Science as an intersection of three fields. Which ones?

Answer 3

1. Computer Science IT
2. Math and Statistics
3. Domains/Business Knowledge

Question 4

4 What is an algorithm ?

Answer 4

A finite sequence of computer-implementable instructions

Question 5

5 What is a Python script?

Answer 5

A collection of commands in a file designed to be executed like a program

Question 6

6 What is a Shell?

Answer 6

A software program that interprets commands from the user so that the operating system can understand them and perform the appropriate functions. The shell is a command-line interface, which means it is solely text-based

Question 7

7 Outcome of:

print(10/2)

Answer 7

5

Question 8

8 How to write exponentiation?

Answer 8

**

2**3=8

Question 9

9 What does % Modulo?

Answer 9

Returns the remainder of a division

18 % 7 =5

Question 10

10 What is a variable assignment

Answer 10

A name attached to a particular object

variable_a= 18

Question 11

11 Create a variable ‘savings’ with value 100 and print it

Answer 11

savings = 100

print(savings)

Question 12

12 Write a script to compound these variables:

savings =100
growth_multiplier = 1.1
t=1

Answer 12

result = savings*growth_multiplier**t

result

Question 13

13 What is type conversion?

Answer 13

An object from one data type to another data type

Question 14

14 Outcome of:

type(‘a’)

Answer 14

str

Question 15

15 Outcome of:

type(False)

Answer 15

bool

Question 16

16 Outcome of:

type(3)

Answer 16

int

Question 17

17 Outcome of:

type(3.3)

Answer 17

float

Question 18

18 Complete code:

’'’savings = 100
result =savings*1.10**7
print(…)

Outcome:
I started with $100 and now I have 194.9

Answer 18

savings = 100
savings = 100
result = round(savings * 1.10**7,1)
print('I started with $' + str(savings)
 \+ ' and now I have $' +str(result))

Question 19

19 What is a list?

Answer 19

A data structure in Python that is a mutable, or changeable, ordered sequence of elements. Each element or value that is inside of a list is called an item.
Lists are defined by having values between square brackets [ ]

Question 20

20 Create a list called house with elements ‘room, kitchen’

#Outcome:
['room', 'kitchen']

Answer 20

house = [‘room’, ‘kitchen’]

house

Question 21

21 Can a list contain different types of data such as a string and a float?

Answer 21

Yes

[1+2,’a’*5]

Question 22

22 What is a list of lists or a multi-dimensional list?

Answer 22

A list inside a list (nested)

Question 23

23 Use list a get this outcome:

[[‘a’,’b’],’c’]

Answer 23

m_list=[[‘a’,’b’],’c’]

m_list

Question 24

24 What is subsetting?

Answer 24

The process of retrieving just the parts of large files

Question 25

#25 Get the output (2 ways) x= ['a', 'b' , 'c', 'd'] #Output: 'b'

Answer 25

x[1];x[-3]

Question 26

#26 What is an index in a list?

Answer 26

Refers to a position within an ordered list

Question 27

#27 Subset and operate x= ['a', 'b' , 'c', 'd'] #Outcome:bc 'bc'

Answer 27

print(x[1]+x[2]) | x[1]+x[2]

Question 28

#28 What is slicing?

Answer 28

Slicing in Python is a feature that enables accessing parts of sequences like strings, tuples, and lists

Question 29

#29 Slice x= ['a', 'b' , 'c', 'd'] #Outcome: ['b', 'c']

Answer 29

x[1:3]

Question 30

#30 Slice (2 ways) x= ['a', 'b' , 'c', 'd'] #Outcome: ['b', 'c']

Answer 30

print(x[1:3]) | print(x[-3:-1])

Question 31

#31 Subsetting lists of lists x=[['a', 'b', 'c' ], ['d','e', 'f']] #Outcome: d

Answer 31

print(x[1][0])

Question 32

#32 Replace list elements x = ['a', 'b', 'c','d'] #Outcome: ['a', 'b', 7, 8]

Answer 32

x[2:]= [7,8] | x

Question 33

#33 Code to extend the list ``` x = ['a', 'b', 'c','d'] y= x+(...code..) ``` #Outcome: ['a', 'b', 'c', 'd', 'e', 'f']

Answer 33

x = ['a', 'b', 'c','d'] y = x + ['e', 'f'] print(y)

Question 34

#34 Delete list elements x = ['a', 'b', 'c','d'] #Outcome: ['a', 'c', 'd']

Answer 34

del(x[1]) | print(x)

Question 35

#35 What is ';' used for?

Answer 35

To place commands on the same line command1; command2

Question 36

#36 What is # used for?

Answer 36

A comment in Python starts with the hash character, # , and extends to the end of the physical line ``` #This is a comment print('a') ```

Question 37

#37 Outcome of: x = ['a', 'b', 'c','d'] y = x del(y[0]) print(x)

Answer 37

['b', 'c', 'd']

Question 38

#38 Outcome of: x = ['a', 'b', 'c','d'] y = list(x) del(y[0]) print(x)

Answer 38

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

Question 39

``` #39 Get number of elements: x = ['a', 'b', 'c','d'] ``` #Outcome: 4

Answer 39

len(x)

Question 40

#40 Function to convert to string

Answer 40

str()

Question 41

#41 Function to convert to integer

Answer 41

int()

Question 42

#42 Function to convert to float

Answer 42

float()

Question 43

#43 Function to convert to boolean

Answer 43

bool()

Question 44

#44 Outcome of: a= 3.4 str(a)

Answer 44

3.4'

Question 45

#45 Outcome of: a= 3.4 int(a)

Answer 45

3

Question 46

#46 Outcome of: a= 3.4 bool(a)

Answer 46

TRUE

Question 47

#47 Think of two ways to get information about a function

Answer 47

help(function) ?function

Question 48

#48 Code (look at the order of the elements) x = ['z','a', 'c','d'] #Outcome: ['z', 'd', 'c', 'a']

Answer 48

sorted(x,reverse=True)

Question 49

#49 Three arguments in the function sorted()

Answer 49

sorted(iterable,key,reverse)

Question 50

#50 What is an iterable in python

Answer 50

When an object is said to be iterable, it means that you can step through (i.e. iterate) the object as a collection

Question 51

#51 Code (look at the order of the elements) x = ["cccc", "b", "dd", "aaa"] #Outcome: ['b', 'dd', 'aaa', 'cccc']

Answer 51

sorted(l, key =len)

Question 52

#52 Code (string method) my_house ='My house' #Outcome: 'MY HOUSE'

Answer 52

my_house.upper()

Question 53

#53 Code (string method) ``` #Count letter 'o' p='pool' ``` #Outcome: 2 Outcome: 2

Answer 53

p.count('o')

Question 54

#54 What is a method in python?

Answer 54

A function that “belongs to” an object

Question 55

#55 Get the position of c (list method) x=['a', 'b', 'c' ] #Outcome: 1

Answer 55

x.index('b')

Question 56

#56 How many a in the list? (list method) x=['a', 'b', 'c' ,'a'] #Outcome: 2

Answer 56

x.count('a')

Question 57

#57 Add d (list method) x=['a', 'b', 'c' ] #Outcome: ['a', 'b', 'c', 'd']

Answer 57

x.append('d') | print(x)

Question 58

#58 Delete c (list method) x=['a', 'b', 'c' ] #Outcome: ['a', 'b']

Answer 58

x.remove('c') | print(x)

Question 59

#59 Change order (list method) x=['a', 'b', 'c' ] #Outcome: ['c', 'b', 'a']

Answer 59

x.reverse() | print(x)

Question 60

#60 Transform it into a numpy array baseball = [180, 215, 210, 210] ``` #Outcome: array([180, 215, 210, 210, 188]) ```

Answer 60

import numpy as np np_baseball =np.array(baseball) np_baseball

Question 61

#61 What is a numpy array?

Answer 61

A grid of values, all of the same type, and is indexed by a tuple of nonnegative integers

Question 62

#62 What is a tuple in python?

Answer 62

An immutable sequence of Python objects | 2,3,6,9

Question 63

#63 Code baseball = [180, 215, 210, 210] #Outcome: numpy.ndarray

Answer 63

import numpy as np np_baseball=np.array(baseball) type(np_baseball)

Question 64

#64 Code baseball = [180, 215, 210, 210] #Outcome:

Answer 64

import numpy as np np_baseball=np.array(baseball) print(type(np_baseball))

Question 65

#65 Code baseball = [180, 215, 210, 210] #Outcome: [1800 2150 2100]

Answer 65

print(np_baseball*10)

Question 66

#66 Complete code (subset arrays) '''height = [180, 215, 210] height_np=... tall = ...>200 print(...)''' #Outcome: [215 210]

Answer 66

import numpy as np height = [180, 215, 210] height_np=np.array(height) tall = height_np>200 print(height_np[tall])

Question 67

#67 Why do we do vectorization?

Answer 67

Vectorization is the process of converting an algorithm from operating on a single value at a time to operating on a set of values (vector) at one time

Question 68

#68 What is type coercion?

Answer 68

Coercion is the implicit conversion of an instance of one type to another during an operation which involves two arguments of the same type.

Question 69

#69 What happens if one tries to build a numpy array with different data types?

Answer 69

If you try to build such a list, some of the elements' types are changed to end up with a homogeneous list. This is known as type coercion.

Question 70

#70 Transform it into a 2D array and show its dimensions (rows,columns) baseball = [[180, 78.4], [215, 102.7], [210, 98.5], [188, 75.2]] #Outcome: (4,2)

Answer 70

import numpy as np np_baseball=np.array(baseball) np_baseball.shape

Question 71

#71 Difference between method and attribute in python

Answer 71

Attributes are the features of the objects or the variables used in a class whereas the methods are the operations or activities performed by that object defined as functions in the class. Attribute = np_ar.shape Method =np_ar.sum()

Question 72

#72 Code (Subset 2D NumPy arrays) x = [["a", "b"], ["c", "d"]] #Outcome: ['a' 'c']

Answer 72

import numpy as np np_x = np.array(x) print(np_x[:,0])

Question 73

#73 Code x = [["a", "b"], ["c", "d"]] ``` #Outcome: #[['a' 'b'] #['c' 'd']] ```

Answer 73

import numpy as np np_x = np.array(x) print(np_x)

Question 74

#74 Code (Arithmetic) np_mat = np.array([[1, 2], [3, 4], [5, 6]]) ``` #Outcome: #array([[11, 12], #[13, 14], #[15, 16]]) ```

Answer 74

import numpy as np | np_mat + np.array([10, 10])

Question 75

#75 Get the mean (numpy) x = [1, 4, 8, 10, 12] #Outcome: 7.0

Answer 75

import numpy as np | np.mean(x)

Question 76

``` #76 Get the median (numpy) x = [1, 4, 8, 10, 12] ``` #Outcome: 8.0

Answer 76

import numpy as np | np.median(x)

Question 77

#77 Get the standard deviation(numpy) x = [1, 4, 8, 10, 12] #Outcome: 4.0

Answer 77

import numpy as np | np.std(x)

Question 78

#78 Get the correlation between both columns (numpy) baseball = [[180, 78.4], [215, 102.7], [210, 98.5], [188, 75.2]] ``` #Outcome: # [[1. 0.95865738] # [0.95865738 1. ]] ```

Answer 78

``` import numpy as np np_baseball=np.array(baseball) a=np_baseball[:,0] b=np_baseball[:,1] print(np.corrcoef(x=a,y=b)) ```

Question 79

#79 What is a correlation matrix?

Answer 79

A correlation matrix is a table showing correlation coefficients between variables. [[1. 0.95865738] [0.95865738 1. ]]

Question 80

#80 Get Mike's height: np_heights=np.array([180,170,130,150]) np_name=np.array(['Mike','Maria','David','Wang']) #Outcome: [180]

Answer 80

mike_height=np_heights[np_name =='Mike'] print(mike_height)