metadata
license: apache-2.0
size_categories:
- 100K<n<1M
SOLUSDT Raw Dataset
Dataset Summary
Raw minute-by-minute trading data for SOL/USDT pair from Binance exchange. The dataset covers 180 days of trading activity, providing comprehensive market data including price, volume, and trade information. This data is suitable for various financial analysis tasks, time series forecasting, and market research.
Supported Tasks
- Time Series Forecasting
- Price Prediction
- Market Analysis
- Trading Strategy Development
- Volume Analysis
- Market Microstructure Research
Dataset Structure
The dataset contains 259,200 records with 10 features.
Time Range
- Start Date: 2024-04-29 17:24:00
- End Date: 2024-10-26 17:23:00
- Interval: 1 minute
Features
| Feature Name | Description | Type |
|---|---|---|
| open_time | Timestamp of the candlestick open | timestamp |
| open | Opening price in USDT | float |
| high | Highest price in USDT | float |
| low | Lowest price in USDT | float |
| close | Closing price in USDT | float |
| volume | Trading volume in SOL | float |
| quote_asset_volume | Trading volume in USDT | float |
| number_of_trades | Number of trades executed | float |
| taker_buy_base_asset_volume | Taker buy volume in SOL | float |
| taker_buy_quote_asset_volume | Taker buy volume in USDT | float |
Dataset Creation
Source Data
- Source: Binance Public API
- Original Format: Minute candlesticks
- Collection Method: Direct API download
Additional Information
Example Usage
import pandas as pd
# Load the dataset
df = pd.read_csv('data_SOLUSDT_180d.csv')
# Convert timestamp to datetime
df['open_time'] = pd.to_datetime(df['open_time'], unit='ms')
# Basic statistics
print(df.describe())
Citation
@misc{solusdt_dataset,
title={SOLUSDT 180 Days Trading Data},
author={roadz},
year={2024},
publisher={Hugging Face},
howpublished={\url{https://huggingface.co/datasets/roadz/solusdt_180_days}}
}
Acknowledgements
Data sourced from Binance exchange through their public API.