Google Calendar Analysis Notebook

Overview

This notebook was used to write the blog post A Year in Time: My 2024 Google Calendar Analysis, which analyzes how I spent my time in 2024 based on my Google Calendar data. The gcal_analysis_2024.ipynb etches, processes, and visualizes event data, generating insights on time spent across categories, word clouds, and monthly hour distributions. It can also be adapted for other years.

Features

• Fetches events from Google Calendar using OAuth 2.0 authentication.
• Analyzes event data to calculate total hours spent on various categories.
• Generates a word cloud visualization of event summaries.
• Provides insights into event distribution over weeks and months.

Requirements

To run this project, you need the following Python packages:

• pytz
• matplotlib
• pandas
• collections
• statistics
• google-auth
• google-auth-oauthlib
• google-api-python-client

You can install the required packages using pip:

pip install pytz matplotlib pandas google-auth google-auth-oauthlib google-api-python-client

Setup

1. Clone the Repository:

   Clone this repository to your local machine:

   git clone [email protected]:eltsai/gcal_analysis.git
   cd gcal_analysis

2. Google Calendar API Setup:

   • Go to the Google Cloud Console.
   • Create a new project.
   • Enable the Google Calendar API for your project.
   • Create OAuth 2.0 credentials and download the credentials.json file.
   • Place the credentials.json file in the project directory.

3. Run the Jupyter Notebook:

   Open gcal_analysis_2024.ipynb and run the cells to fetch and analyze your Google Calendar events.

Usage

• The notebook is structured into several sections:
  • Fetch Data From Google Calendar: This section handles authentication and fetching events.
  • Load Data: Loads the fetched event data from a JSON file (you'll probably need to rewrite the mapping between color and category).
  • Data Analysis: Analyzes the events to calculate total hours spent on different categories.
  • Visualizations: Generates visualizations such as word clouds and monthly hour distributions.

Important Notes

• Ensure that you have the necessary permissions to access your Google Calendar data.
• The project includes a .gitignore file to exclude sensitive files like credentials.json and any generated data files.

License

This project is licensed under the MIT License. See the LICENSE file for more details.