---
license: cc-by-4.0
tags:
- anime
- entertainment
- streaming
- machine-learning
- demographics
size_categories:
- 1K<n<10K
---

![Anime Watchers Dataset](https://huggingface.co/datasets/Mikey-TraceGod/Anime-Viewers-Data/resolve/main/cover.png)

# 📺 Anime Watchers Dataset (1960–2025)

**📦 Dataset Size:** 10,000 Records  
**📄 Format:** CSV  
**📜 License:** CC-BY-4.0  

---

## 📖 Overview
This dataset contains **10,000 synthetic profiles of anime watchers**, spanning from the **Classic Era (1960s–1989)** to the **Modern Era (2010–2025)**.  

It is designed for:
- **Data Analysis**
- **Machine Learning**
- **Recommendation Systems**
- **Trend Prediction** in anime consumption.

---

## 📂 Features
Each record represents an individual anime watcher with detailed attributes:

- **Demographics:** `Age`, `Gender`, `Country`, `Year of Birth`
- **Anime Preferences:** `Favorite Genre`, `Most Watched Title`, `Top 3 Anime List`
- **Viewing Habits:** `Start Year Watching`, `Average Weekly Watch Hours`, `Anime Era Preference`
- **Platforms & Devices:** `Primary Platform (TV, Netflix, Crunchyroll, etc.)`, `Device Used`
- **Engagement:** `Manga Reading`, `Online Community Participation`, `Merchandise Spending`
- **Language Preference:** `Subbed`, `Dubbed`, or `Regional Languages`

---

## 📊 Generational Patterns
- **Classic Era Fans (1960–1989):** Prefer Mecha, watched via TV/VHS, low online activity  
- **Golden Era Fans (1990–2009):** Popular titles like *Dragon Ball Z*, *Naruto*, *Evangelion*  
- **Modern Era Fans (2010–2025):** Stream via Crunchyroll/Netflix, binge-watch, active in online communities  

---

## ✅ Example Usage in Python
```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Mikey-TraceGod/Anime-Viewers-Data")

# Access first example
print(dataset['train'][0])