Panel: The powerful data exploration & web app framework for Python
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Updated
Dec 23, 2024 - Python
Panel: The powerful data exploration & web app framework for Python
A repository of awesome panel examples. The apps are running entirely in the browser as webassembly apps. NO SERVER REQUIRED.
Large scale visualizations of unstructured mesh data
Our goal was to create a ML bot that analyzes real time trading data to determine the most opportune times buy and sell stock
This project utilizes Python visualizations packages, such as Plotly Express, HVPlot and PyPlot/Matplotlib to create an interactive dashboard exploring the San Francisco real estate housing market. Uses MapBox API.
Schulungsmaterialen für die Cusy Python-Schulungen: https://cusy.io/de/seminare
Real estate analysis dashboard with interactive visualizations to explore investment opportunities
Unsupervised Machine Learning analysis to find patterns in Cryptocurrencies market valuations.
This is an application that fetches historical data on 1 index, 4 stocks, and 2 crypto currencies and performs analytical calculations to assist in conducting a relative analysis between the index and the crypto currencies to determine if a relationship exists and the type of relationship for the purpose of conducting portfolio analysis and Mont…
This repo is about calculating the buying power of economies based on dividing gold price by minimum wages per countries.
In this project, I explored Python requests, APIs, and JSON traversals to answer a fundamental question: "What is the weather like as we approach the equator?
💃 Correlation graphs with NetworkX
Creating a Python script to visualise the weather of over 500 cities of varying distances from the equator using citipy Python libraryLinks and OpenWeatherMap APILinks to create a representative model of weather across those cities.
Fake News! Detector aims to find a way to weed out the real news from the fake news. We create this machine learning model to identify authentic news from the swam of fake news on social media.
Analysing Chicago Crime Data
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