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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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- counseling-records |
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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 - Counseling Records |
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--- |
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# Nigeria - Counseling Records |
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## Dataset Description |
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Student counseling session records with types, outcomes, and session counts. |
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## Dataset Information |
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- **Country**: Nigeria |
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- **Dataset Name**: counseling_records |
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- **Total Records**: 100,000 |
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- **Total Columns**: 7 |
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- **File Size**: 1.43 MB |
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- **Format**: Parquet (full data), CSV (sample) |
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- **Generated**: 2025-10-21T23:16:04.539695 |
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## Schema |
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| Column | Data Type | Description | |
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|--------|-----------|-------------| |
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| `counseling_id` | object | Counseling Id | |
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| `student_id` | object | Student Id | |
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| `session_type` | object | Session Type | |
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| `session_count` | float64 | Session Count | |
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| `outcome` | object | Outcome | |
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| `session_date` | datetime64[ns] | Session Date | |
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| `country` | object | Country | |
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## Sample Data |
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The dataset includes a 10,000-row sample in CSV format for quick exploration. |
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## Data Quality |
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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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## Dependencies |
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- `student_profiles` |
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- `academic_outcomes` |
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## Usage Example |
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### Python (Pandas) |
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```python |
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import pandas as pd |
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# Load full dataset |
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df = pd.read_parquet('counseling_records_full.parquet') |
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print(f"Loaded {len(df):,} records") |
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print(df.head()) |
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# Load sample |
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df_sample = pd.read_csv('counseling_records_sample.csv') |
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print(df_sample.describe()) |
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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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# Load from Hugging Face |
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dataset = load_dataset('nigeria-education-counseling_records') |
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df = dataset['train'].to_pandas() |
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``` |
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## Data Generation |
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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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**Note**: This is synthetic data generated for research and testing purposes. |
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## Related Datasets |
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This dataset is part of the **Nigeria Education Datasets Collection** (45 datasets total). |
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Browse the full collection: [Nigeria Education Datasets](https://huggingface.co/collections/nigeria-education) |
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## Citation |
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```bibtex |
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@dataset{nigeria_counseling_records_2025, |
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title={Nigeria Education Dataset: Counseling Records}, |
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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-counseling_records} |
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} |
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``` |
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## License |
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[Specify your license] |
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## Contact |
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[Your contact information] |
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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 🇳🇬 |
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