README.md

---
dataset_info:
  features:
  - name: Row_ID
    dtype: int64
  - name: Topic
    dtype: string
  - name: Subtopic
    dtype: string
  - name: Question
    dtype: string
  - name: Answer_1
    dtype: string
  - name: Explanation_1
    dtype: string
  - name: Answer_2
    dtype: string
  - name: Explanation_2
    dtype: string
  - name: Answer_3
    dtype: string
  - name: Explanation_3
    dtype: string
  - name: Difficulty
    dtype: string
  splits:
  - name: train
    num_examples: 62941756
license: mit
language:
- en
tags:
- chemistry
size_categories:
- 10M<n<100M
---
# Chemistry Questions Dataset (62M Rows)

## Description
A dataset of 62,941,756 chemistry questions covering Organic Chemistry (Alkenes, Nomenclature), Inorganic Chemistry (Oxidation States), and Physical Chemistry (Kinetics). Each row includes a question, 2-3 answers with explanations, and difficulty level.

## Columns
- **Row_ID**: Unique identifier (1 to 62,941,756).
- **Topic**: Main chemistry category (e.g., Organic Chemistry).
- **Subtopic**: Specific topic (e.g., Alkenes).
- **Question**: The chemistry question.
- **Answer_1**, **Answer_2**, **Answer_3**: Possible answers (Answer_3 often N/A).
- **Explanation_1**, **Explanation_2**, **Explanation_3**: Explanations for each answer.
- **Difficulty**: Hard or Expert.

## Analysis
- Unique value counts are visualized in [unique_value_counts.png](unique_value_counts.png).
- Sample analysis (based on 100k rows): See image for approximate counts per column.

## Usage
```python
from datasets import load_dataset
dataset = load_dataset("XythicK/chemistry")
```

## Size
- Uncompressed: ~9.06GB