Pet Shelter

React, Mongo, Nodejs, Express, Hosted on EC2

Full-stack web development, where you can upload a picture of pet’s profile with CRUD functions using NoSQL database MongoDB with RESTful-API

• Technologies: React, Node.js, Express, and Mongo.
• Check out the code on GitHub:
• Click here for a Live Demo:

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Travel Buddy

Python using Django MVC Framework.

A travel organizer allowing registered users to coordinate travel plans and join travel itineraries created by others. Featuring login validations, Bcrypt password hashing, Session, and various schema relationships.

• Technologies: Python, Django, SQLite
• Check out the code on GitHub:
• Click here for a Live Demo:

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Django File Structure Creation App

Automated Directory Structure Creator

App that was created to automate and simplify steps needed to create a Django app. This originally started as a batch script and evolved into a python app.

• Technologies: Python, Django, Batch Scripting
• Check out the code on GitHub:

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Task List

Task list tracker app written in React.

This is a simple Task List app that allows the user to add, remove and tick items on a list. The list provides four methods, add, remove, check and uncheck objects of the list.

• Technologies: React, Node.js
• Check out the code on GitHub:

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Python/ Tesseract Receipt Parser

Receipt parser written in Python

Receipt parser written in Python that allowed a user to upload a picture of a receipt. The receipt image would then be sent to Tesseract to perform OCR. The resulting text is then run through a custom built parser to try and remove noise from the converted text.

• Technologies: Python, Batch Scripting
• Check out the code on GitHub:

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We Rate Dogs

Python,

Real world data is rarely ready for immediate use. Usually it must be cleaned before any useful information can be extracted. This project involved data wrangling, analyzing, and visualizing #WeRateDogs Twitter archive, a website that rates people's dogs along with funny comments. The higher the rating, the 'better' the dog. WeRateDogs has over 4 million followers and has received international media coverage.

Data was gathered data from three sources.

• The Twitter archive #WeRateDogs, a csv file that contains the tweet, rating, dog name, and dog 'stage' in life (such as puppy).
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• An 'image prediction' file, or what breed of dog is in each tweet, according to a neural network. This file was downloaded programmatically from Udacity's servers using the Requests library.
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• Twitter's API was used to gather retweet count and favorite count, both of which were missing from the provided Twitter archive file.

• Technologies: Python, Pandas, Numpy, Jupyter Notebook
• Check out the Jupyter Notebook on GitHub:

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Red Wine Analysis

Understanding the Variables that Effect Quality of Red Wine

This project investigated how variables of red wine like alcohol %, chlorides, sulphates content etc affects the quality of Red Wine.

• Technologies: R, Dplyr, ggplot2
• Check out the code on GitHub:
• Check out the code on RPubs:

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Titanic Survivor Analysis

Visualization of Passenger Survival by Class, Age, and Gender

This project used the Titanic Survival dataset from Kaggle to produce a series of visualization on Tableau. The dataset contained the demographic and passenger information about 891 of the 2224 passengers and crew abroad. The visualization compared the different passenger ticket class to their likelyhood to survive. It also divided the passengers into male and female to further show the survival rate based on gender

• Technologies: Python, Pandas, Numpy, Tableau, Jupyter Notebook
• Check it out on Tableau Public:

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Dr. Jekyll vs Mr. Hyde

Comparision of Name Count in Dr. Jekyll and Mr. Hyde

While watching Thor: Ragnorak I noticed that Hulk received a large portion of screen time compared to Dr Banner. This made me think about the book Dr. Jekyll and Mr. Hyde of which the Hulk was inspired from. From there I decided to analyze the word frequency of the book to discover who was mentioned more in the book Dr. Jekyll or Mr. Hyde.

• Technologies: Python, Pandas, Numpy, NLTK, Jupyter Notebook
• Check out the Jupyter Notebook on GitHub:

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The Stroop Effect

Testing a Perceptual Phenomenon.

In a Stroop task, participants are presented with a list of words, with each word displayed in a color of ink. The participant’s task is to say out loud the color of the ink in which the word is printed. The task has two conditions: a congruent words condition, and an incongruent words condition. In the congruent words condition, the words being displayed are color words whose names match the colors in which they are printed: for example RED, BLUE. In the incongruent words condition, the words displayed are color words whose names do not match the colors in which they are printed: for example RED, BLUE. In each case, we measure the time it takes to name the ink colors in equally-sized lists. Each participant will go through and record a time from each condition.

• Technologies: Python, Pandas, Numpy, Jupyter Notebook
• Check out the Jupyter Notebook on GitHub:

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Let's Build a Liquor Store

Determining Optimal Store Placement

This project looked at the publicly available liquor sales data for Iowa. The goal of the analysis was to determine the optimal location in Iowa in which to build a new liquor store.

• Technologies: Python, Pandas, Numpy, Jupyter Notebook
• Check out the Jupyter Notebook on GitHub:

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