Python for Data Wrangling

A training course covering Python fundamentals for data wrangling using pandas, numpy, and visualization libraries.

Prerequisites

• Python 3.12

Installation

1. Install uv

uv is a fast Python package and project manager.

macOS/Linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows (PowerShell):

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

After installation, restart your terminal or run:

source $HOME/.local/bin/env

2. Initialize the project

Clone the repository and navigate to the project directory:

cd training-python-for-data-wrangling

Initialize the project:

uv init

Create a virtual environment and install dependencies:

uv venv
uv pip install numpy pandas matplotlib seaborn bokeh jupyter jupyterlab

3. Activate the environment

macOS/Linux:

source .venv/bin/activate

Windows:

.venv\Scripts\activate

4. Launch Jupyter

jupyter lab

This will open JupyterLab in your browser at http://localhost:8888. Navigate to the notebook files (.ipynb) in the file browser on the left to open them.

Course Materials

• Chapter 2: Data Types - Covers Python data types (integers, floats, strings, lists, tuples, dictionaries, sets, numpy arrays)
• Chapter 3: Basic Data Wrangling - End-to-end data wrangling with CSV files using pandas

Data

The course uses Citibike trip data (202009CitibikeTripdataExample.csv) for hands-on exercises.