Jupyter Notebook setup and usage in Data Analysis Python - Mini Project: Build & Apply

Jupyter Notebook Setup and Usage

📖 Scenario: You have just installed Jupyter Notebook to explore data science interactively. You want to create a simple notebook to practice basic Python commands and see how outputs appear immediately.

🎯 Goal: Learn how to create variables, run simple Python code, and display outputs inside a Jupyter Notebook environment.

📋 What You'll Learn

Create a variable with a specific value

Create a helper variable for configuration

Use a simple Python operation

Display the result using a print statement

💡 Why This Matters

🌍 Real World

Data scientists use Jupyter Notebooks to write and test code quickly, explore data, and share results with others.

💼 Career

Knowing how to use Jupyter Notebook is essential for data analysis, machine learning, and reporting in many data science roles.

1

Create a variable in Jupyter Notebook

Create a variable called number and set it to 10 in a Jupyter Notebook cell.

Data Analysis Python

# Create a variable called number and set it to 10
# Your code here

Need a hint?

Type number = 10 in a cell and run it by pressing Shift + Enter.

2

Add a helper variable for configuration

Create a variable called multiplier and set it to 5 in the next cell.

Data Analysis Python

# Create a variable called multiplier and set it to 5
# Your code here

Need a hint?

Just like before, assign 5 to multiplier and run the cell.

3

Calculate a new value using the variables

Create a variable called result that multiplies number by multiplier.

Data Analysis Python

# Create a variable called result that multiplies number by multiplier
# Your code here

Need a hint?

Use the * operator to multiply number and multiplier.

4

Display the result in the notebook

Use print(result) to display the value of result in the output cell.

Data Analysis Python

# Print the result
# Your code here

Need a hint?

Type print(result) and run the cell to see the output.