introduction to data science in python assignment answers

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Data Science in Practice

Python introduction, python introduction ¶.

This is a demo assignment that is openly available for the Data Science in Practice Course.

How to complete assignments ¶

Whenever you see:

You need to replace (meaning: delete) these lines of code with some code that answers the questions and meets the specified criteria. Make sure you remove the ‘raise’ line when you do this (or your notebook will raise an error, regardless of any other code, and thus fail the grading tests).

You should write the answer to the questions in those cells (the ones with # YOUR CODE HERE ), but you can also add extra cells to explore / investigate things if you need / want to.

Any cell with assert statements in it is a test cell. You should not try to change or delete these cells. Note that there might be more than one assert that tests a particular question.

If a test does fail, reading the error that is printed out should let you know which test failed, which may be useful for fixing it.

Note that some cells, including the test cells, may be read only, which means they won’t let you edit them. If you cannot edit a cell - that is normal, and you shouldn’t need to edit that cell.

All outside packages/modules that will be used will be specified. You may not use other libraries in the assignments.

Finally, note that questions have points as specified in the detailed instructions.

Introduction ¶

The purpose of this assignment is to make sure you have the tools you’ll need to use for COGS108. Notably, we’ll be using Python, Jupyter notebooks, and git/GitHub. Since we’re using datahub , you won’t need a local version of Jupyter or Python on your computer. So, for this assignment, we’ll focus on getting you set up on GitHub.

Most assignments will be completed completely within the Jupyter Notebook and submitted on datahub; however, for this first assignment, we want you to be comfortable in GitHub. Tasks to complete Part 1 below will require work outside of this notebook.

Python (5 points) ¶

This part of the assignment is focused on some practice with Python, and with practicing working with the format of the assignments.

This class assumes some prior knowledge of Python. In the following questions, you will need to work with basic (standard library) data types (floats, lists, dictionaries, etc.) and control flow (conditionals, loops, functions, etc). If the questions in this section are totally unfamiliar to you, you may need to revisit some practice materials to catch up with some of the programming.

Through these questions, we will also prompt you to use a couple slightly more advanced standard library functions (for example, enumerate and zip ), that may be new to you.

Each question should be answerable with a relatively small number of lines of code, up to about 5-7 lines at most.

If you are having any trouble, remember to visit the course tutorials ( https://github.com/COGS108/Tutorials ). Assignment questions often follow the structure of examples provided in the tutorials, and a large number of relevant links and external materials are also indexed in the tutorials.

Q1: Defining Variables (0.25 points)

Create the following variables:

a variable called my_int that stores the integer 29

a variable called my_float that stores the float 7.29

a variable called my_string that stores the string ‘COGS108’

a variable called my_bool that stores the boolean True

Q2: Defining Variables: Lists & Tuples (0.25 points)

Define a list called var_a , that contains individual letters a-j (inclusively).

Define a tuple called var_b , that contains the numbers 1-10 (inclusively).

Q3: Defining Variables: Dictionaries (0.5 points)

Create a Python dict called dictionary where the keys are the elements in var_a and the values are the corresponding elements in var_b . (Note: Use var_a and var_b you created above.)

The zip function may be useful.

You might also make use of a Python dictionary comprehension.

Q4: Value Comparisons (0.5 points)

Store values in the variables comp_val_1 , comp_val_2 , comp_val_3 , and comp_val_4 such that the assert cell will pass silently (meaning the tests will pass and not produce an error).

Q5: Control Flow (0.5 points)

Loop through the provided list my_list . For each element, check if it is an even number. If the element is an even number, append the INDEX of that element to the list inds .

Note that you are adding the index to inds , not the element itself . (Reminder: Python uses zero-based indexing, so the index of the first element in the list is 0.)

To check if a number is even, you can use the modulo % operator.

To loop through an iterable, keeping track of the index, you can use the enumerate function.

Q6: Indexing (0.5 points)

Using the four lists provided in the cell below, complete the following indexing:

Use forward indexing to store the second value in list_1 to index_1

Use negative indexing to store the last value in list_2 to index_2

Store the first three values of list_3 to index_3

Store the last two values of list_4 to index_4

Q7: Looping through Dictionaries (0.75 points)

Using the students dictionary provided below, write a for loop that loops across the dictionary and collects all subject numbers (ex. ‘S2’) where the dictionary value is False .

Imagine, for example, the dictionary indicates whether a student has completed an assignment, and we wanted to get a list of the students who had not yet completed the assignment .

To answer this question, use a for loop across the students dictionary. You then need to get the associated value in each iteration, and check if it is True . If it is True , you can use continue to skip ahead to the next iteration. Otherwise, append the subject number (i.e. ‘S2’) to a list called incomplete .

Q8: Functions I (0.5 points)

Write a function return_odd that will take a list as its input and return a list of all the odd values as its output.

Note that this differs from what you did above in two ways: (1) it returns the values, not the index, and (2) it’s looking for odd values, not even.

For example:

Q9: Functions II (0.5 points)

Write a function squared_diff that takes two number inputs and returns the squared difference of the two numbers i.e., \((a - b)^2\) . For example:

Q10: Putting it all together (0.75 points)

Here, we’ll update the values in dictionary , storing the output in a dictionary called other_dictionary . This new dictionary will have the same keys, but some values will be updated.

The values in other_dictionary should be updated, such that if the value in the original dictionary is…

odd: update the the value stored in the dictionary to store the squared difference of the original value and ‘10’. Remember, you created a function to do this above.)

even: store the original value (from dictionary ).

to loop through key-value pairs in a dictionary, check out the .items method

You created a squared_diff function above.

This is the end of the first assignment!

The goal here was to check your basic Python understanding. From here, assignments will be more data science centric, using lots of pandas and working with data!

Have a look back over your answers, and also make sure to Restart & Run All from the kernel menu to double check that everything is working properly. You can also use the ‘Validate’ button above, which runs your notebook from top to bottom and checks to ensure all assert statements pass silently. When you are ready, submit on datahub!

Appendix: Version Control

• Python Basics
• Interview Questions
• Python Quiz
• Popular Packages
• Python Projects
• Practice Python
• AI With Python
• Learn Python3
• Python Automation
• Python Web Dev
• DSA with Python
• Python OOPs
• Dictionaries

Python Operators

Precedence and associativity of operators in python.

• Python Arithmetic Operators
• Difference between / vs. // operator in Python
• Python - Star or Asterisk operator ( * )
• What does the Double Star operator mean in Python?
• Division Operators in Python
• Modulo operator (%) in Python
• Python Logical Operators
• Python OR Operator
• Difference between 'and' and '&' in Python
• not Operator in Python | Boolean Logic

Ternary Operator in Python

• Python Bitwise Operators

Python Assignment Operators

Assignment operators in python.

• Walrus Operator in Python 3.8
• Increment += and Decrement -= Assignment Operators in Python
• Merging and Updating Dictionary Operators in Python 3.9
• New '=' Operator in Python3.8 f-string

Python Relational Operators

• Comparison Operators in Python
• Python NOT EQUAL operator
• Difference between == and is operator in Python
• Chaining comparison operators in Python
• Python Membership and Identity Operators
• Difference between != and is not operator in Python

In Python programming, Operators in general are used to perform operations on values and variables. These are standard symbols used for logical and arithmetic operations. In this article, we will look into different types of Python operators. 

• OPERATORS: These are the special symbols. Eg- + , * , /, etc.
• OPERAND: It is the value on which the operator is applied.

Types of Operators in Python

• Arithmetic Operators
• Comparison Operators
• Logical Operators
• Bitwise Operators
• Assignment Operators
• Identity Operators and Membership Operators

Arithmetic Operators in Python

Python Arithmetic operators are used to perform basic mathematical operations like addition, subtraction, multiplication , and division .

In Python 3.x the result of division is a floating-point while in Python 2.x division of 2 integers was an integer. To obtain an integer result in Python 3.x floored (// integer) is used.

Example of Arithmetic Operators in Python

Division operators.

In Python programming language Division Operators allow you to divide two numbers and return a quotient, i.e., the first number or number at the left is divided by the second number or number at the right and returns the quotient. 

There are two types of division operators: 

Float division

• Floor division

The quotient returned by this operator is always a float number, no matter if two numbers are integers. For example:

Example: The code performs division operations and prints the results. It demonstrates that both integer and floating-point divisions return accurate results. For example, ’10/2′ results in ‘5.0’ , and ‘-10/2’ results in ‘-5.0’ .

Integer division( Floor division)

The quotient returned by this operator is dependent on the argument being passed. If any of the numbers is float, it returns output in float. It is also known as Floor division because, if any number is negative, then the output will be floored. For example:

Example: The code demonstrates integer (floor) division operations using the // in Python operators . It provides results as follows: ’10//3′ equals ‘3’ , ‘-5//2’ equals ‘-3’ , ‘ 5.0//2′ equals ‘2.0’ , and ‘-5.0//2’ equals ‘-3.0’ . Integer division returns the largest integer less than or equal to the division result.

Precedence of Arithmetic Operators in Python

The precedence of Arithmetic Operators in Python is as follows:

• P – Parentheses
• E – Exponentiation
• M – Multiplication (Multiplication and division have the same precedence)
• D – Division
• A – Addition (Addition and subtraction have the same precedence)
• S – Subtraction

The modulus of Python operators helps us extract the last digit/s of a number. For example:

• x % 10 -> yields the last digit
• x % 100 -> yield last two digits

Arithmetic Operators With Addition, Subtraction, Multiplication, Modulo and Power

Here is an example showing how different Arithmetic Operators in Python work:

Example: The code performs basic arithmetic operations with the values of ‘a’ and ‘b’ . It adds (‘+’) , subtracts (‘-‘) , multiplies (‘*’) , computes the remainder (‘%’) , and raises a to the power of ‘b (**)’ . The results of these operations are printed.

Note: Refer to Differences between / and // for some interesting facts about these two Python operators.

Comparison of Python Operators

In Python Comparison of Relational operators compares the values. It either returns True or False according to the condition.

= is an assignment operator and == comparison operator.

Precedence of Comparison Operators in Python

In Python, the comparison operators have lower precedence than the arithmetic operators. All the operators within comparison operators have the same precedence order.

Example of Comparison Operators in Python

Let’s see an example of Comparison Operators in Python.

Example: The code compares the values of ‘a’ and ‘b’ using various comparison Python operators and prints the results. It checks if ‘a’ is greater than, less than, equal to, not equal to, greater than, or equal to, and less than or equal to ‘b’ .

Logical Operators in Python

Python Logical operators perform Logical AND , Logical OR , and Logical NOT operations. It is used to combine conditional statements.

Precedence of Logical Operators in Python

The precedence of Logical Operators in Python is as follows:

• Logical not
• logical and

Example of Logical Operators in Python

The following code shows how to implement Logical Operators in Python:

Example: The code performs logical operations with Boolean values. It checks if both ‘a’ and ‘b’ are true ( ‘and’ ), if at least one of them is true ( ‘or’ ), and negates the value of ‘a’ using ‘not’ . The results are printed accordingly.

Bitwise Operators in Python

Python Bitwise operators act on bits and perform bit-by-bit operations. These are used to operate on binary numbers.

Precedence of Bitwise Operators in Python

The precedence of Bitwise Operators in Python is as follows:

• Bitwise NOT
• Bitwise Shift
• Bitwise AND
• Bitwise XOR

Here is an example showing how Bitwise Operators in Python work:

Example: The code demonstrates various bitwise operations with the values of ‘a’ and ‘b’ . It performs bitwise AND (&) , OR (|) , NOT (~) , XOR (^) , right shift (>>) , and left shift (<<) operations and prints the results. These operations manipulate the binary representations of the numbers.

Python Assignment operators are used to assign values to the variables.

Let’s see an example of Assignment Operators in Python.

Example: The code starts with ‘a’ and ‘b’ both having the value 10. It then performs a series of operations: addition, subtraction, multiplication, and a left shift operation on ‘b’ . The results of each operation are printed, showing the impact of these operations on the value of ‘b’ .

Identity Operators in Python

In Python, is and is not are the identity operators both are used to check if two values are located on the same part of the memory. Two variables that are equal do not imply that they are identical. 

Example Identity Operators in Python

Let’s see an example of Identity Operators in Python.

Example: The code uses identity operators to compare variables in Python. It checks if ‘a’ is not the same object as ‘b’ (which is true because they have different values) and if ‘a’ is the same object as ‘c’ (which is true because ‘c’ was assigned the value of ‘a’ ).

Membership Operators in Python

In Python, in and not in are the membership operators that are used to test whether a value or variable is in a sequence.

Examples of Membership Operators in Python

The following code shows how to implement Membership Operators in Python:

Example: The code checks for the presence of values ‘x’ and ‘y’ in the list. It prints whether or not each value is present in the list. ‘x’ is not in the list, and ‘y’ is present, as indicated by the printed messages. The code uses the ‘in’ and ‘not in’ Python operators to perform these checks.

in Python, Ternary operators also known as conditional expressions are operators that evaluate something based on a condition being true or false. It was added to Python in version 2.5. 

It simply allows testing a condition in a single line replacing the multiline if-else making the code compact.

Syntax :   [on_true] if [expression] else [on_false] 

Examples of Ternary Operator in Python

The code assigns values to variables ‘a’ and ‘b’ (10 and 20, respectively). It then uses a conditional assignment to determine the smaller of the two values and assigns it to the variable ‘min’ . Finally, it prints the value of ‘min’ , which is 10 in this case.

In Python, Operator precedence and associativity determine the priorities of the operator.

Operator Precedence in Python

This is used in an expression with more than one operator with different precedence to determine which operation to perform first.

Let’s see an example of how Operator Precedence in Python works:

Example: The code first calculates and prints the value of the expression 10 + 20 * 30 , which is 610. Then, it checks a condition based on the values of the ‘name’ and ‘age’ variables. Since the name is “ Alex” and the condition is satisfied using the or operator, it prints “Hello! Welcome.”

Operator Associativity in Python

If an expression contains two or more operators with the same precedence then Operator Associativity is used to determine. It can either be Left to Right or from Right to Left.

The following code shows how Operator Associativity in Python works:

Example: The code showcases various mathematical operations. It calculates and prints the results of division and multiplication, addition and subtraction, subtraction within parentheses, and exponentiation. The code illustrates different mathematical calculations and their outcomes.

To try your knowledge of Python Operators, you can take out the quiz on Operators in Python . 

Python Operator Exercise Questions

Below are two Exercise Questions on Python Operators. We have covered arithmetic operators and comparison operators in these exercise questions. For more exercises on Python Operators visit the page mentioned below.

Q1. Code to implement basic arithmetic operations on integers

Q2. Code to implement Comparison operations on integers

Explore more Exercises: Practice Exercise on Operators in Python

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