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--- |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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dataset_info: |
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features: |
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- name: dates |
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dtype: string |
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- name: product_id |
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dtype: string |
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- name: sales |
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dtype: float64 |
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splits: |
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- name: train |
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num_bytes: 38430 |
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num_examples: 1098 |
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download_size: 10860 |
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dataset_size: 38430 |
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license: apache-2.0 |
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language: |
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- en |
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pretty_name: time-series-data |
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size_categories: |
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- 1K<n<10K |
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--- |
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# time-series-data |
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## Overview |
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The time-series-data is a fake dataset containing a sales history of three years of a particular product (chocolate). |
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## Dataset Details |
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The dataset is used in this [notebook](https://github.com/Nkluge-correa/TeenyTinyCastle/blob/master/ML-Intro-Course/14_time_series_forecasting.ipynb) |
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to introduction to time series forecasting and XGBoost. |
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- Dataset Name: time-series-data |
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- Language: English |
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- Total Size: 1,098 |
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## Contents |
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The dataset consists of a data frame with the following columns: |
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- dates |
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- product_id |
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- sales |
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```bash |
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{ |
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dates: "2020-01-01", |
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product_id: "chocolate", |
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sales: 137 |
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} |
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``` |
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## How to use |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("AiresPucrs/time-series-data", split='train') |
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``` |
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## License |
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This dataset is licensed under the Apache-2.0. |