Tuspe Special Mix is an indicator that contains many features that make day trading easier.

Open source momentum base trend following systematic trading strategies inspired from top trend following traders (Richard Denis, Olivier Seban and Nick Radge) implemented for various trading platforms as TradingView, cTrader, Multicharts and TradeStation.

Bayesian Change-Point Detection and Time Series Decomposition

📈 A small, fast chart for time series, lines, areas, ohlc & bars

The python package to analyse and illustrate trends using innovative trend analysis method.

Web Dashboard for Youtube Channel & Video Trend Analysis

Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple steps to arrive at a set of trend files related to land-cover changes.

A machine learning based application to predict factory productivity.

An R Package with a Shiny Dashboard for Visualizing and Comparing Library Statistics Data Published from the Annual Survey of Association of Research Libraries (ARL; URL: www.arlstatistics.org/data/main)

This project aims to analyze air quality data from major cities in Indonesia. The analysis includes data cleaning, exploration, visualization, and building predictive models to classify air quality levels.

Time Series Analysis of CO2_emission. Study from exercise E3 of 'Physics and Finance'

Pedalling Forward: The Evolution of Dedicated Cycling Infrastructure in Canadian Cities from 2010 to 2022

Correlation Trend Application This Streamlit-based web application allows users to analyze the correlation trends of the top 10 cryptocurrencies in relation to Bitcoin (BTC) and visualize these trends in a table.

In this project, I developed a comprehensive end-to-end data pipeline utilizing SQL and Python to clean, transform, and load data into Power BI. Leveraging my proficiency in MySQL, Pandas, Matplotlib, and Seaborn, I ensured accurate and efficient data processing to support in-depth analysis.

Let’s uncover passenger rail trends and station metrics. It starts by extracting and processing over 30k+ passenger records. Then to focus on improving data quality and developing an interactive Power BI dashboard. I’ll wrap up this analysis with visualizing trends and feasibility study recommendations.

Supply chain analytics is a valuable part of data-driven decision-making in various industries such as manufacturing, retail, healthcare, and logistics. It is the process of collecting, analyzing and interpreting data related to the movement of products and services from suppliers to customers.

Library for automated signal segmentation, trend classification and analysis.

Technical Analysis Library using Pandas and Numpy

Data Analytics Project of AI Trends in Tech news using Python

This repo contains all code that was used for data analysis process for my research paper. my paper was about estimating the rainfall ratio for himalayan catchment using physchometeri method.