Data visualizations of Uber pickups from April 2014 to September 2014 in New York with R. The following packages were used for this project: ggplot2, ggthemes, dplyr, tidyr, lubridate, DT, scales.
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Updated
Dec 6, 2020
Data visualizations of Uber pickups from April 2014 to September 2014 in New York with R. The following packages were used for this project: ggplot2, ggthemes, dplyr, tidyr, lubridate, DT, scales.
Screen for stocks in the SPY500 that yield potentially actionable price pattern setups for options trading.
Portfolio of the latest projects.
Exploratory data analysis on the entire world educational dataset ( avaiable on Kaggle). This meticulously curated dataset offers a panoramic view of education on a global scale , delivering profound insights into the dynamic landscape of education across diverse countries and regions.
This Repository contains a Data Driven analysis on ATP Tennis matches happened in 2023. This project discusses about player rankings, player performance statistics, match statistics and a model to predict the players chance of winning a match by inputting all the player specific and match specific inputs.
This is a personal portfolio of data visualizations, shiny apps, and other assorted projects.
R package for the exploration and visualization of proteomics data obtained with the process of fractionation
A repository dedicated to visualizations and reporting examples
Bar charts showing top rated dataviz projects
Leveraging K-Means clustering, our project categorizes retail customers based on purchasing behaviors and demographics. This provides businesses with actionable insights to tailor marketing efforts, enhancing customer experience and boosting sales.
Predicting the Quality of Red and White Wine using Random Forest Classifier, Data Visualizations, and Data Analysis.
Free and Open Source Data Analytics Tool for Laravel Apps
Assessing data via Twitter API, cleaning data using pandas and numpy, create data visualizations by matplotlib.
Web app to give movie recommendations based on your choice.
multivariate multiple regression model to study the effect of eight input variables on two output variables, which are the heating load and the cooling load, of residential buildings.
Google Data Analytics Capstone Project
Using the Rain in australia dataset for rainfall perdiction
Analyzed Data By Creating Interactive Dashboard Using MS Excel
To design and populate a data warehouse for AIS messages from Data@Liánchéng in PostgreSQL and build an interface to query the data warehouse
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