# timeseriesdatasets

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The `timeseriesdatasets` package provides a curated collection of time series
datasets for data analysis, forecasting, statistical analysis, and machine learning
in Python. It includes stock market prices, climate and weather data,
energy consumption, air passengers, cryptocurrency, sensor readings, sales records,
and more — sourced from Kaggle.

## Installation
You can install the `timeseriesdatasets` package from PyPI:
```bash
pip install timeseriesdatasets
```

## Usage
```python

import timeseriesdatasets as ts

# List all available datasets

datasets = ts.list_datasets()
print(datasets)

# Load a specific dataset

df = ts.load_dataset('microsoft_stock')
print(df.head())

# Describe dataset

df_01 = ts.describe('nvidia_stock')
print(df_01)

```

## 📊 Some Available Datasets

| Dataset | Description | 
|---------|-------------|
| `microsoft_stock` | Microsoft stock price time series from 2015 to 2021.| 
| `yahoo_stock` | Yahoo stock price time series data for forecasting.| 
| `tesla_stock` | Tesla stock price time series data for daily trading and forecasting.| 
| `nvidia_stock` | NVIDIA stock price time series from 1999 to 2025.| 

> Run `timeseriesdatasets.list_datasets()` or `ts.list_datasets()` (using `ts` as alias) to see the full list of available datasets.


## License

The `timeseriesdatasets` library is released under the **MIT License**, allowing free use for both commercial and non-commercial purposes.
See the [LICENSE](LICENSE) file for details.