hvplot

A high-level app and dashboarding solution for Python

High-level tools to simplify visualization in Python.

A repository of awesome panel examples. The apps are running entirely in the browser as webassembly apps. NO SERVER REQUIRED.

Large Scale Sea level visualizations of unstructured mesh data

Some Python scripts & notebooks for Delft3D4-FLOW turbidity current simulations

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

Data science project - collect, clean, process and display using machine learning and interactive dashboard

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 a postGRESQL and fraud finding techniques

This repo is about calculating the buying power of economies based on dividing gold price by minimum wages per countries.

💃 Correlation graphs with NetworkX

dashboard for visualizing F1 statistics

Unsupervised Machine Learning analysis to find patterns in Cryptocurrencies market valuations.

Pangeo tutorial at FOSS4G 2022

A Panel-based dashboard showing recent shootings in Philadelphia using Altair, Folium, and Hvplot

This project uncovers patterns in Azuki, Cryptopunks & Boyed Ape Yatch Club NFT trading.

A visualization index designed to analyze fluctuations in crypto exchange data as it correlates with global crypto-specific news stories sentiment data

Cryptocurrencies analysis with unsupervised machine learning

We created a report that includes what cryptocurrencies are on the trading market and how they could be grouped to create a classification system for this new investment.The data Martha provided us was not ideal, so we processed to fit the machine learning models. Since there is no known output for what Martha is looking for, we decided to use u…