Metadata-Version: 2.4
Name: dsba-python1-alpha
Version: 0.1.1
Summary: Auto-checkers for the DSBA Python for Data Science course
Project-URL: Homepage, https://github.com/your-org/dsba-checkers
License: MIT
Requires-Python: >=3.8
Requires-Dist: numpy>=1.21
Requires-Dist: pandas>=1.3
Requires-Dist: scipy>=1.7
Description-Content-Type: text/markdown

# dsba-python1-alpha

Auto-checkers for the **DSBA Python for Data Science** course.  
Inspired by Kaggle's `learntools` — same `.check()` / `.hint()` / `.solution()` API,  
all datasets bundled inside the package (no internet required).

## Install

```bash
pip install dsba-python1-alpha
```

## Workshop 14 — scipy.stats

```python
from dsba_checkers.workshops.w14_scipy import q1, q2, q3, q4, q5, q6, q7

# After writing your code:
q1.check(mean_charges, median_charges, skewness_charges, n_outliers)
# ✓  Correct!

# Stuck? Ask for a hint:
q1.hint()

# Give up? Show the solution (also shown automatically after 3 failed attempts):
q1.solution()
```

## Available workshops

| Module | Topic |
|--------|-------|
| `dsba_checkers.workshops.w14_scipy` | scipy.stats: descriptive stats, correlation, t-tests, Bonferroni |

More workshops coming in future versions.
