A basic scrapper for stock exchanges
# Zimbabwe-Stock-Exchange-Daily-Pricesheets
This project is dedicated to building and maintaining a **comprehensive, daily-updated dataset of trade activity from the Zimbabwe Stock Exchange (ZSE)**. It serves as an automated scraper that collects and organizes daily pricesheet information, creating a valuable historical record of market movements.
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## Features
* **Daily Data Collection:** Automatically scrapes and compiles daily pricesheet data from the ZSE website.
* **Structured Output:** Generates organized datasets in easily digestible CSV and Excel formats.
* **Public API Access:** The accumulated dataset is made accessible via a dedicated API for broader usage:
* ZExchange API on RapidAPI
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## Purpose & Goals
* **Open Data Initiative:** To create an openly accessible historical dataset of Zimbabwe Stock Exchange activity, empowering:
* **Data Analysts & Data Scientists:** For market research, trend analysis, and model development.
* **Researchers:** For academic studies on emerging markets.
* **Learning & Development:** To serve as a practical learning project for Python programming, data scraping techniques, and exploring new libraries.
* **Automation:** To automate the routine and time-consuming task of manually collecting ZSE daily data.
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## Data Output
The scraper generates daily files in the following directories:
* `csv-daily-pricesheets/`: Contains daily price sheets in **CSV** format.
* `xls-daily-price-sheets/`: Contains daily price sheets in **Excel (XLSX)** format.
Each file includes key metrics such as **Company Name, Opening Price, Closing Price, and Volume Traded**.
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## Disclaimer
The information provided by this project is for **informational and educational purposes only** and does not constitute financial, investment, or trading advice. Users should conduct their own research and consult with qualified financial professionals before making any investment decisions.
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## Contribution
Contributions to this project …