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roadz/solusdt_enhanced_180

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… See the full description on the dataset page: https://huggingface.co/datasets/roadz/solusdt_enhanced_180.

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Dataset Card

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 NameDescriptionType
open_timeTimestamp of the candlestick opentimestamp
openOpening price in USDTfloat
highHighest price in USDTfloat
lowLowest price in USDTfloat
closeClosing price in USDTfloat
volumeTrading volume in SOLfloat
quoteassetvolumeTrading volume in USDTfloat
numberoftradesNumber of trades executedfloat
takerbuybaseassetvolumeTaker buy volume in SOLfloat
takerbuyquoteassetvolumeTaker buy volume in USDTfloat

Dataset Creation

Source Data
  • Source: Binance Public API
  • Original Format: Minute candlesticks
  • Collection Method: Direct API download

Additional Information

Example Usage
python
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
bibtex
@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.