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Upload special_needs_support dataset

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README.md ADDED
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+ ---
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+ license: mit
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+ task_categories:
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+ - tabular-regression
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+ - tabular-classification
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+ tags:
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+ - nigeria
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+ - education
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+ - africa
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+ - synthetic-data
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+ - special-needs-support
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+ language:
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+ - en
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+ size_categories:
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+ - 100K<n<1M
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+ pretty_name: Nigeria Education - Special Needs Support
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+ ---
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+
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+ # Nigeria - Special Needs Support
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+
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+ ## Dataset Description
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+
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+ Special education and disability support service records.
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+
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+ ## Dataset Information
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+
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+ - **Country**: Nigeria
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+ - **Dataset Name**: special_needs_support
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+ - **Total Records**: 100,000
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+ - **Total Columns**: 8
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+ - **File Size**: 1.49 MB
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+ - **Format**: Parquet (full data), CSV (sample)
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+ - **Generated**: 2025-10-21T23:15:55.244385
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+
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+ ## Schema
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+
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+ | Column | Data Type | Description |
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+ |--------|-----------|-------------|
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+ | `support_id` | object | Support Id |
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+ | `student_id` | object | Student Id |
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+ | `disability_type` | object | Disability Type |
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+ | `support_service` | object | Support Service |
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+ | `service_hours_weekly` | float64 | Service Hours Weekly |
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+ | `progress_level` | object | Progress Level |
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+ | `enrollment_date` | datetime64[ns] | Enrollment Date |
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+ | `country` | object | Country |
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+
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+ ## Sample Data
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+
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+ The dataset includes a 10,000-row sample in CSV format for quick exploration.
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+
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+ ## Data Quality
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+
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+ - **Validation Status**: ✅ Passed
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+ - **Missing Data**: ~2-5% (realistic pattern)
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+ - **Data Type Enforcement**: Strict
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+ - **Cross-Dataset Consistency**: Maintained
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+
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+ ## Dependencies
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+
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+ - `student_profiles`
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+
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+ ## Usage Example
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+
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+ ### Python (Pandas)
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+ ```python
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+ import pandas as pd
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+
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+ # Load full dataset
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+ df = pd.read_parquet('special_needs_support_full.parquet')
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+ print(f"Loaded {len(df):,} records")
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+ print(df.head())
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+
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+ # Load sample
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+ df_sample = pd.read_csv('special_needs_support_sample.csv')
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+ print(df_sample.describe())
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+ ```
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+
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+ ### Python (Hugging Face Datasets)
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load from Hugging Face
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+ dataset = load_dataset('nigeria-education-special_needs_support')
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+ df = dataset['train'].to_pandas()
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+ ```
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+
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+ ## Data Generation
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+
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+ This dataset was generated using statistical distributions based on:
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+ - UNICEF education statistics for Nigeria
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+ - World Bank development indicators
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+ - Nigerian Ministry of Education data
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+ - Realistic probability distributions
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+
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+ **Note**: This is synthetic data generated for research and testing purposes.
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+
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+ ## Related Datasets
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+
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+ This dataset is part of the **Nigeria Education Datasets Collection** (45 datasets total).
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+
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+ Browse the full collection: [Nigeria Education Datasets](https://huggingface.co/collections/nigeria-education)
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @dataset{nigeria_special_needs_support_2025,
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+ title={Nigeria Education Dataset: Special Needs Support},
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+ author={[Your Name/Organization]},
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+ year={2025},
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+ publisher={Hugging Face},
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+ url={https://huggingface.co/datasets/nigeria-education-special_needs_support}
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+ }
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+ ```
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+
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+ ## License
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+
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+ [Specify your license]
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+
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+ ## Contact
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+
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+ [Your contact information]
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+
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+ ---
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+
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+ **Part of**: Nigeria Education Datasets Collection
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+ **Total Datasets**: 45
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+ **Country**: Nigeria 🇳🇬
metadata.yaml ADDED
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+ columns:
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+ - support_id
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+ - student_id
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+ - disability_type
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+ - support_service
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+ - service_hours_weekly
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+ - progress_level
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+ - enrollment_date
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+ - country
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+ country: Nigeria
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+ country_code: NGA
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+ dataset_name: special_needs_support
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+ dependencies:
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+ - student_profiles
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+ dtypes:
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+ country: object
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+ disability_type: object
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+ enrollment_date: datetime64[ns]
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+ progress_level: object
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+ service_hours_weekly: float64
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+ student_id: object
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+ support_id: object
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+ support_service: object
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+ file_size_mb: 1.4942293167114258
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+ generated_at: '2025-10-21T23:15:55.244385'
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+ num_columns: 8
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+ num_rows: 100000
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+ validation:
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+ checks: {}
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+ passed: true
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+ version: 1.0.0
special_needs_support_full.parquet ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:962290f2e1de844b1af14170ba46a9d15a270f1acf3378e500911bbec5a636c8
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+ size 1566813
special_needs_support_sample.csv ADDED
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