Python Tutorials
Welcome to the Python tutorials section. Here you'll find comprehensive guides covering the essential Python libraries for data science, scientific computing, and visualization.
Available Libraries
| Library | Description | Use Cases |
|---|---|---|
| Pandas | Tabular data manipulation with DataFrames and Series | Data wrangling, ETL, financial analysis, time series |
| xarray | Multi-dimensional labeled arrays for scientific data | Climate/weather data, geospatial, satellite imagery, NetCDF |
| NumPy | N-dimensional arrays, linear algebra, and random sampling | Numerical computing, signal processing, ML foundations |
| Matplotlib | Publication-quality static and interactive visualizations | Data exploration, scientific figures, dashboards, reports |
How to Use These Tutorials
Each library has three parts:
- Overview — Course outline and what you'll learn
- Tutorial — Comprehensive walkthrough with code examples
- Common Methods — Quick-reference guide for frequently used functions
📥 Sample Datasets
Each tutorial includes downloadable sample datasets so you can follow along with every example in your own environment. Click on any tutorial above, then look for the Download the Sample Data section at the top of the tutorial page.
Available datasets
| File | Used In | Description |
|---|---|---|
sales_data.csv | Pandas | Sales transactions for the capstone project (~500 rows) |
employees.csv | Pandas | Employee records for merge/join examples (20 rows) |
departments.csv | Pandas | Department data for merge/join examples (5 rows) |
weather_data.csv | Pandas | Daily weather time series (2 years) |
student_scores.csv | Pandas | Student scores for reshape/pivot examples (30 rows) |
population_data.csv | Matplotlib | Population growth for 3 cities (2000–2024) |
experiment_data.csv | Matplotlib | Experiment results with control & treatment groups (200 rows) |
sensor_readings.csv | NumPy | Sensor temperature, humidity & pressure readings (1000 rows) |
sample_data.txt | NumPy | Tab-separated values for I/O examples (50 rows) |
grid_data.csv | xarray | 3D gridded weather data (time × latitude × longitude) — 15,000 rows |