Skip to main content

A Python package to access historical stock data for NASDAQ and NYSE.

Project description

Stocks Historical Library 📊

A Python library for accessing historical stock data from major stock exchanges and equity markets. This library simplifies the process of fetching and formatting stock data using the Stocks Historical API, making it easy to retrieve and analyze stock data programmatically. Currently, it supports data for top 100 stocks from NYSE and NASDAQ markets, with plans to include data from additional markets in the future.

Library inspired by Yahoo Historical.


Features

  • Retrieve historical stock data for NASDAQ and NYSE.
  • Supports specifying date ranges with start and optional end dates.
  • Formats data into Pandas DataFrames for easy analysis.
  • Fetch Open, High, Low, and Close data.

Installation

Install the library via pip:

pip install stocks-historical

Usage

Import and Initialize

You can use the Nasdaq or Nyse classes to fetch stock data:

from stocks_historical import Nasdaq, Nyse

# Fetch NASDAQ data
nasdaq_data = Nasdaq(symbol="AAPL", start="2023-01-03", end="2023-01-09")  # Start and end are dates (YYYY-MM-DD)
data = nasdaq_data.get_data()
print(data.head())

# Fetch NYSE data
nyse_data = Nyse(symbol="GE", start="2023-01-03")  # End is optional
data = nyse_data.get_data()
print(data.head())

Output: The data is returned as a Pandas DataFrame with columns:

  • Date: Timestamp of the record (in human-readable format).
  • Open: Opening price of the stock.
  • High: Highest price of the stock.
  • Low: Lowest price of the stock.
  • Close: Closing price of the stock.

Example DataFrame:

Fetched Data:
                 Date     Open     High     Low   Close
0 2023-01-03 01:00:00  130.280  130.900  124.17  125.07
1 2023-01-04 01:00:00  126.890  128.656  125.08  126.36
2 2023-01-05 01:00:00  127.130  127.770  124.76  125.02
3 2023-01-06 01:00:00  126.010  130.290  124.89  129.62
4 2023-01-09 01:00:00  130.465  133.410  129.89  130.15

API Reference

This library is built on top of the Stocks Historical API. If you prefer to work directly with the API, refer to the API repository for documentation: Stocks Historical API


Credits

The stock data used in this library is sourced from Kaggle Datasets:

  1. Top 100 NYSE Daily Stock Prices by Steven Van Ingelgem

  2. Top 100 NASDAQ daily stock prices by Steven Van Ingelgem

All credits goes to the Kaggle community for providing these datasets!


Contributions

Contributions are welcome 🤗! If you'd like to improve this library, feel free to fork the repository and submit a pull request.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

stocks_historical-1.0.1.tar.gz (4.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

stocks_historical-1.0.1-py3-none-any.whl (5.8 kB view details)

Uploaded Python 3

File details

Details for the file stocks_historical-1.0.1.tar.gz.

File metadata

  • Download URL: stocks_historical-1.0.1.tar.gz
  • Upload date:
  • Size: 4.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.13.0

File hashes

Hashes for stocks_historical-1.0.1.tar.gz
Algorithm Hash digest
SHA256 f6ccf3fedc3343ae073a2a4fc4510b4e69bb03969dfa30224b00d0d72bb39a11
MD5 4d76330a16450d0a9b7496450421aef1
BLAKE2b-256 dfebb825fb42e55cd2f4a6cea8080ea46b2bf5191664176d9809fd78d25af016

See more details on using hashes here.

File details

Details for the file stocks_historical-1.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for stocks_historical-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 9ee1b5d5de2407f0314ca3ae026f8c3cb02ee4e268b0ade548919ef2039723da
MD5 acae09ea6c58287b056a1c631a2c3da5
BLAKE2b-256 c0e51e640acc1043ef26c8a2042652a9a763213d56f1adf2c48a64004986b8cc

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page