metadata
license: apache-2.0
dataset_info:
features:
- name: Date
dtype: timestamp[ms]
- name: Open
dtype: float64
- name: High
dtype: float64
- name: Low
dtype: float64
- name: Close
dtype: float64
- name: Volume
dtype: float64
- name: Dividends
dtype: float64
- name: Stock Splits
dtype: float64
- name: Ticker
dtype: large_string
splits:
- name: train
num_bytes: 405404053
num_examples: 5385871
download_size: 101258281
dataset_size: 405404053
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- tabular-classification
- time-series-forecasting
- table-question-answering
language:
- en
tags:
- finance
- stock-market
- tabular
- time-series
- historical-data
pretty_name: stock pile
size_categories:
- 1M<n<10M
Stock-pile
Stock-pile is a comprehensive financial dataset covering historical daily and weekly stock market performance for 750 of the world's richest companies—spanning from their founding/IPO dates up to the present day.
Dataset Overview
- Entities Covered: 750 world-leading companies by market cap & wealth.
- Time Horizon: Complete lifetime historical data (from founding/IPO date to present).
- Frequencies Included: Daily and Weekly aggregate records.
- Total Records: Over 5 Million rows (~101 MB in compressed Parquet format).
Dataset Structure
The dataset contains standard OHLCV (Open, High, Low, Close, Volume) data alongside relevant corporate metadata.
Data Fields
| Column Name | Data Type | Description |
|---|---|---|
date |
timestamp |
Trade date |
frequency |
string |
Frequency interval (daily or weekly) |
open |
float64 |
Opening price |
high |
float64 |
Highest price during the period |
low |
float64 |
Lowest price during the period |
close |
float64 |
Closing price |
volume |
int64 |
Total trading volume |
Dividends |
float64 |
Total dividends |
Stock splits |
float32 |
Amount of spilt stocks |
Quickstart & Usage
Loading with Datasets
import datasets
dataset = datasets.load_dataset("helloadhavan/Stock-pile")
print(dataset)