Scraping UPI apps statistics
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Updated
Jan 21, 2024 - Python
Scraping UPI apps statistics
This is a Python web scraping project that extracts information from the GitHub Topics page (https://github.com/topics).
This Python script is designed to scrape applicant information from the NEC website.
This repository contains web scraping scripts for extracting various types of data from the Samvidha website, which serves as the CMS of our Collge IARE.
Analysis of Economic Trends through Alternative Data.
Importance of Web scrapping, scrapping using python BeautifulSoup, Selenium and requests libraries.
This is a capstone level classification ML project for predicting IPL team finishing position for an year based on Individual player's performance. The project includes web-scraping ESPN cricinfo website for ipl player statistics, pre-processing the data, and comparing different classification models and hyperparameter tuning them.
This application scraps the reviews for the given item.
Our submission for Hackrx2.0 hackathon by Bajaj Finserv
Python Data Science - Analysis of Professional eSports players (Counter-Strike:Global Offensive)
Python - Flask web application - E-commerce - Scraping Instagram shops based in Algeria
Un programa en Python que se encarga de buscar todos los artículos que vos solicites y te entregue un archivo con el nombre, precio y link de cada uno de los productos. Desarollado en conjunto con @ostizjuan
This is a beginner friendly project which lets us to find the meaning, phonetic transcription, parts of speech of the given word and its usage from online dictionary(a website) by using simple web scraping concepts in python.
A collection of basic Python projects perfect for beginners, including tools like an audio recorder, background remover, notepad, slot machine, text-to-speech converter, Tic Tac Toe game, and web scraping scripts with a Streamlit website.
NewsReader application developed in python language that can tell you top news feeds through voice recognition.
The following Python script extracts data from the DataCamp DAX cheat sheet webpage and saves it to a text file. The script uses Selenium to automate the web scraping process and write the extracted information into a text file.
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