Start your data science journey with Python. Learn practical Python programming skills for basic data manipulation and analysis.

- Home
- Python Essentials for Data Analysis IToggle Dropdown
- 1.1 Getting started - Hello, World!
- 1.2 Variables
- 1.3 Data types
- 1.4 Printing
- 1.5 Lists
- 1.6 Dictionaries
- 1.7 Input function
- 1.8 Arithmetic operators
- 1.9 Comparison operators
- 1.10 Logical operators
- 1.11 Identity operators
- 1.12 Membership operators
- 1.13 Conditional statements (if-elif-else)
- 1.14 Importing modules
- 1.15 For loops
- 1.16 While loops

- Python Essentials for Data Analysis II
- 2.1 Introduction to Functions in Python
- 2.2 Functions - Arguments
- 2.3 Functions with Return Values
- 2.4 Functions - A Fun Exercise!
- 2.5 Functions - Arbitrary Arguments (*args)
- 2.6 Functions - Arbitrary Keyword Arguments (**kwargs)
- 2.7 Recursive Functions
- 2.8 Lambda Expressions
- 2.9 Functions - More Exercises

- Data Analysis with PandasToggle Dropdown
- PD.1 Introduction to Pandas
- PD.2 Basics of Pandas
- PD.3 Finding and Describing data
- PD.4 Assigning Data
- PD.5 Manipulating Data
- PD.6 Handling Missing Data
- PD.7 Removing and adding data
- PD.8 Renaming data
- PD.9 Combining data
- PD.10 Using Pandas with other functions/mods
- PD.11 Data classification and summary
- PD.12 Data visualisation

- Data Analysis with NumPyToggle Dropdown
- NP.1 Introduction to NumPy
- NP.2 Create Arrays Using lists
- NP.3 Creating Arrays with NumPy Functions
- NP.4 Array Slicing
- NP.5 Array Reshaping
- NP.6 Math with NumPy I
- NP.7 Combining 2 arrays
- NP.8 Adding elements to arrays
- NP.9 Inserting elements into arrays
- NP.10 Deleting elements from arrays
- NP.11 Finding unique elements and sorting
- NP.12 Math with NumPy II
- NP.13 Analysing data across arrays
- NP.14 NumPy Exercises

- Learning Resources
- Contact Us

Using `return`

, you can write a function that returns a value. You can assign the returned values to a variable which can be used in whatever manner you choose.

This is useful when you need to use the results your function produces for something else.

First let's create a simple multiplication function. We will see an output of 40.

Now let us add 2 to the variable `mul`

print(mul+2)

With the updated function below, we will see an output of 42.

You can also create a function that takes in multiple arguments, and add them both together.

**Results:**

4

11

15

Since we do not declare variables in Python, this means that we can use the addition function we created above to add any 2 sets of data together as long as they are both the same type (string, float, integer).

Let's add these codes into our trinket and see what happens!

print(addition("one","time")) print(addition([1,1],[1,1]))

The results shows that the function concatenated "one" and "time", and merged the 2 lists to become [1, 1, 1, 1].

- Last Updated: Feb 6, 2024 10:02 AM
- URL: https://libguides.ntu.edu.sg/python
- Print Page

You are expected to comply with University policies and guidelines namely, Appropriate Use of Information Resources Policy, IT Usage Policy and Social Media Policy.
Users will be personally liable for any infringement of Copyright and Licensing laws.

Unless otherwise stated, all guide content is licensed by CC BY-NC 4.0.