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cado

CADO (Cool Avocado Data Observations) is a team project responsible for creating an application to analyze and explore data analysis and price predictions for Hass Avocados in the United States.

carsales

Team 6 Research Analysts project examines factors affecting the change in car sales between 2019 and 2020.

d3-challenge

The D3-Challenge consists of constructing an interactive scatter plot displaying relationships between factors shaping people's lives, such as rates of income, obesity, poverty, and more.

etl_project

The ETL Project is a team proposal regarding Texas Real Estate vs. Texas School Districts.

javascript-challenge

This project consists of code written using JavaScript, HTML, and CSS to create a table dynamically based upon a dataset provided. Users are also allowed to filter the table data for specific values.

leaflet-challenge

This project utilizes Leaflet, JavaScript, and D3 to visualize the earthquake data from the United States Geological Survey (USGS).

matplotlib-power-of-plots

This project is composed of statistical analysis of drug regimens that involve mice testing. This project includes a summary of statistics with the mean, median, variance, standard deviation, and sem of the tumor volume for each drug regimen in the project. Visualizations included are bar charts, pie charts, line plots, and scatter plots.

pandas-challenge

In this challenge, the goal is to apply my knowledge about Python Pandas and apply it to analyze the data for the most recent fantasy game, Heroes of Pymoli. The analysis presents as a report that breaks down the game's purchasing data into meaningful insights.

performancetask

plot.ly-challenge

The purpose of the Plot.ly Challenge is to build an interactive dashboard utilizing a dataset from Belly Button Biodiversity to display its findings.

project-2

The project includes visualization of GeoJSON real estate data utilizing Leaflet, JavaScript, Mapbox, and deployed using Flask and Heroku.

python-api-challenge

This project consists of two activities. The first activity is called WeatherPy, which requires creating a python script to display the weather of 500+ cities across the world. Comparisons between temperature, humidity, cloudiness, wind speed, and latitude are in this project section. The second activity, VacationPy, consists of creating maps utilizing data from the first activity.

python-challenge

The Python-Challenge consists of two projects called "PyBank" and "PyPoll" to conduct an analysis. Each project includes a resources folder with a comma-separated values file (CSV) document used to create a script and an analysis folder that displays each project's results.

sql-challenge

This project utilizes Data Engineering and Data Analysis to build a SQL database of employees of a corporation called Pewlett Hackard from the 1980s and 1990s.

tableau-homework

This project aims to aggregate the Citi Bike Trip History Logs data to build a data dashboard utilizing Tableau Public.

vba-challenge

This project focuses on the analysis of the stock market while utilizing VBA scripting to display the data. This project includes two files, one called alphabetical testing solution, used while developing the script to test the results faster, and the second called multiple year stock data, which was tested last for the final report for the project. The final report will consist of yearly data from 2014 to 2016.

web-design-challenge

The Web Design challenge consists of gathering, analyzing, and charting data with Python. This project also consists of a website created with HTML/CSS and Bootstrap to display results.

web-scraping-challenge

The objective is to create a web application that scrapes various websites for data related to the “Mission to Mars” project and displays the information in a single HTML page in the web-scraping challenge.