---
license: mit
task_categories:
- tabular-classification
tags:
- tabular
- classification
- student-grades
- label-errors
- noisy-labels
- data-centric-ai
---

# Student Grades Demo Dataset

This dataset contains student grades data with both true labels and noisy (corrupted) labels.

## Dataset Description

The dataset includes:
- Student exam scores (exam_1, exam_2, exam_3)
- Notes field
- True letter grades (`letter_grade`)
- Noisy/corrupted letter grades (`noisy_letter_grade`)

This is useful for demonstrating and validating label error detection methods.

## Usage

```python
import pandas as pd

# Load the dataset
df = pd.read_csv("hf://datasets/Cleanlab/student-grades-demo/student-grades-demo.csv")
print(df.head())

# Find rows where labels were corrupted
import numpy as np
true_errors = np.where(df["letter_grade"] != df["noisy_letter_grade"])[0]
print(f"Number of label errors: {len(true_errors)}")
```

## License

MIT License