Duplicate from mramazan/User-Animelist-Dataset

Co-authored-by: Ramazan <mramazan@users.noreply.huggingface.co>

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+*.pcm filter=lfs diff=lfs merge=lfs -text
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+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
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+animes.csv filter=lfs diff=lfs merge=lfs -text
+ratings.csv filter=lfs diff=lfs merge=lfs -text
+ratings.dat filter=lfs diff=lfs merge=lfs -text
+animes.csv.w filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+preview_file_name: ratings.csv
+license: cc-by-4.0
+pretty_name: User Animelist Dataset
+size_categories:
+- 1M<n<10M
+modalities:
+- tabular
+task_categories:
+- tabular-regression
+- tabular-classification
+language:
+- en
+tags:
+- Anime
+- Recommendation
+- Tabular
+- Dataset
+- Recommender
+- MovieLens
+---
+
+# About Dataset
+
+**This dataset consists of user ratings for anime titles. Each user in the dataset has provided at least 5 ratings,
+ensuring a minimum level of engagement. The dataset includes detailed information about both users and anime, making it 
+suitable for tasks such as recommendation systems, user behavior analysis, and genre-based filtering. 
+Dataset is freshly-created so it cover newer animes. Data is published in MovieLens format except timestamp data so
+this dataset is easy to use with GitHub that trains with MovieLens dataset**
+
+## Dataset Statistics
+
+   - Number of Users: 1,774,522
+   - Number of Animes: 20,237
+   - Total Ratings: 148,170,496
+   - Sparsity/Density: 0.0041
+   - Average Ratings per User: ~83.50
+   - Average Ratings per Anime: ~7,321.76
+   - Rating Range: 0.1 to 10.0
+   - Mean Rating: 7.64
+   - Standard Deviation of Ratings: 1.89
+
+## Anime Metadata
+
+### Each anime entry includes:
+
+   - Title
+   - Year of release
+   - Episode Count
+   - Type (e.g., TV, Movie, OVA)
+   - Score (aggregated or average rating)
+   - Image URL (for visual reference)
+   - MyAnimeList URL
+   - Genres Detailed Genres
+
+## Usage
+
+```bash
+file_path = 'ratings.npy'
+
+# ratings_array shape: (n_ratings, 3) - columns: [user_id, anime_id, rating]
+ratings_array = np.load(file_path)
+    
+# Create DataFrame from numpy array
+df = pd.DataFrame(ratings_array, columns=['user_id', 'anime_id', 'rating'])
+```
+
+## Links
+
+Dataset GitHub repo: https://github.com/MRamazan/User-Animelist-Dataset
+
+Dataset Kaggle link: https://www.kaggle.com/datasets/tavuksuzdurum/user-animelist-dataset
+
+BERT Anime Recommender GitHub repo: https://github.com/MRamazan/AnimeRecBERT

animes.csv

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