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Travis Bostick's Projects

airbnbscraper icon airbnbscraper

A web scraper that visits links to air BNB and saves crucial information to a csv

articles icon articles

A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci

bellybutton icon bellybutton

The goal of this project is to build an interactive dashboard to analyze and explore a dataset microbes in the human navel. This interactive design will include a bar chart that toggles on the participant's ID, a bubble chart displaying each sample, an info card with demographic data, and a gauge chart displaying hygine info.

climate_analysis icon climate_analysis

The objective of the project was to turn 2 CSV files into an SQL database using the Python Library SQLAlchemy. These CSV files contained metadata about specific weather stations and weather observation data from these stations. Once created, this SQL database was analyzed to create visualizations about precipitation data and station specific data. Next, an API with multiple routes was created. This API returns precipitation data, temperature data, station metadata, and aggregate temperature data for a specific data range.

crime_watcher icon crime_watcher

This application uses machine learning to answer the question "How safe am I at this location in Minneapolis?". By using an algorithm to convert recently reported crimes in Minneapolis to danger scores for each of the 500 sections (created with clustering), a linear regression model calculates the current danger level of the user's location. The application also displays the user's location on a map along with recently reported crimes in that area.

disc_golf_dashboard icon disc_golf_dashboard

The overall goal of this project is to create a dashboard of visualizations with filter capabilities, giving users the ability to find the perfect area based on their preferences.

employeedatabase icon employeedatabase

The overall goal of this project is to bring a company's legacy database system into the modern age and perform an analysis. All that remains of this database from the 1980's are 6 CSV files. This task will be completed by creating an SQL database from these spreadsheets and using database queries to perform an analysis, fulfilling specific requests.

gitignore icon gitignore

A collection of useful .gitignore templates

javascript_alien icon javascript_alien

The goal of this project was to create a webpage that displays a table with multiple filtering options. The data source is a collection of details regarding 111 alien encounters.

mars_scraping icon mars_scraping

The objective of the project was to successfully scrape data from multiple space related websites and display the data on a webpage. After compiling the data that was scraped, I first stored it in a Mongo database. Once stored in the database, the data from our mongo database was stored on a webpage through a flask server. The webpage has a somewhat basic design and layout since this project is focused on scraping, using flask servers, and mongo databases.

pizzaimpactetl icon pizzaimpactetl

Using Python and Postgres to construct a database of how pizza effects the health of americans

spotifysonganalysisproject icon spotifysonganalysisproject

The goal of this project is to analyze the data available from Spotify to answer questions about Spotify Audio Features by song year, correlation between Audio Features and country metrics, and the Spotify Audio Features by song year. Technologies to be used are Python, Jupyter Notebooks, Pandas, Requests, and Matplotlib. Optionally, the Spotify API can be used but will match the Kaggle Data

weather_api icon weather_api

The overall goal of this project is to use Google's APIs to analyze the weather for different cities and determine the ideal vacation spot. To start, visualizations comparing different weather readings and latitude were created for 500 randomly selected cities. An analysis was then completed on these comparative graphs. Then, a heatmap showing the humidity readings was created. This heatmap was used as a backdrop to overlay a few cities and nearby hotels. We narrowed down our list of 500 cities by filtering out cities based on our ideal weather criteria.

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