2 Introduction to Google Colab

2.1 Learning Objectives

Understand what Google Colab is and its advantages for data science and AI
Learn how to access and navigate Google Colab
Create and manage notebooks in Google Colab
Run Python code in Colab cells
Use text cells for explanations and formatting
Import and use pre-installed libraries for data analysis
Import and use data to perform analysis
Share Colab notebooks

2.2 Introduction

Google Collaboratory, or Colab for short, is a free online platform that allows you to work with Python or R code in your browser. It’s a great way to get started with Python, as you don’t have to install anything on your computer.

Some limitations if you’re running heavy workload though. Can get timeout. But for beginner data analysts, it’s perfect and free.

Note that this document is a summary of the video, rather than a replacement. You should watch the video for a more complete experience.

2.3 Getting Started With Colab

Search for “Google Colab” in your favorite search engine.
Usually the first result will be the correct one. Currently, it’s colab.research.google.com, but it may change in the future.
Sign in with your Google account (create a Gmail account if you don’t have one)

2.4 Creating and Managing Notebooks

Notebooks are the main way to organize work in Colab. They contain code cells and text cells.
Create a new notebook: File > New Notebook
Rename your notebook for better organization

2.5 Working With Code Cells

There should be a button at the top left that allows you to add code or text cells
Code cells are where you write and execute Python code
Type ``1 + 1 in a cell then run it
Run a cell by clicking the play button or using keyboard shortcuts:
- Command + Enter on Mac or Ctrl + Enter on Windows: Run the current cell
- Shift + Enter: Run the current cell and create a new one below
Try to get comfortable with the keyboard shortcuts
Your code cell may take a while to run the first time, as the Python engine needs to be initialized
When you run a cell, the final output is displayed below the cell
To see multiple outputs, explicitly print them with print() For example:

print(1)
print(2)

2.6 Text Cells

Use text cells for explanations and titles
The toolbar above the text cell allows you to format text, but pay attention to the generated markdown

2.7 Example of Working With Data

Click on the Files tab to see the “sample_data” folder
Import the California housing test dataset:

import pandas
housing_data = pandas.read_csv("/content/sample_data/california_housing_test.csv")
housing_data.describe()

View the dataset by typing housing_data in a cell and running it

2.8 Practice Q: Importing Data

Import the “california_housing_train” dataset
Use the describe() function to get a summary of the dataset

2.9 Getting Data From Your Drive

In the Files tab, click the button to mount your drive
Create a folder and upload a CSV file from your computer to the folder
We can import the data with pandas as before

2.10 Practice Q: Importing Data

Import a CSV file you uploaded to your drive
Use the describe() function to get a summary of the dataset

2.11 Where Is Your Notebook Saved?

All work is automatically saved to your Google Drive
Access your notebooks at drive.google.com in the “Colab Notebooks” folder

2.13 Conclusion

Google Colab provides a powerful, accessible platform for data science and AI projects. Its pre-configured environment and easy sharing features make it an excellent way to get started with data analysis.