The purpose of this project is to collect NASDAQ stock information (from https://www.centralcharts.com/), analyze the data, and produce a bar chart of the top 10 companies by trading volume. The program also exports the scraped data to a CSV file for personalized analysis.
The motivation behind this project was to get some experience using web scraping in combination with the Pandas and Matplotlib libraries. The project is useful because it automatically produces a visual of the top companies by trading volume that was not available on the https://www.centralcharts.com/ website.
- Implemented 'asyncio' library to write asynchronous code. Instead of waiting for the program to receive a response from the server before sending another request, all the requests are set up front. The program then pauses (awaits) until all the responses are collected. Lastly, all responses are scraped. This reduces the speed of the program by 96% (172 seconds down to 7 seconds).
- Uses pandas and matplotlib libraries to sort data and present it as a bar graph.
- Install
virtualenv. From the command line:
python3 -m pip install virtualenv
- Create a folder for the project root directory.
- Open a terminal in the project root directory and run:
virtualenv env
- Then execute the command (for Windows):
env\Scripts\activate.bat
- Install the dependencies:
(env) python3 -m pip install -r requirements.txt
- Now you are ready to run the program!
https://www.centralcharts.com/
GNU General Public License v3.0