david-fried Goto Github PK

analyzing-budget-and-election-data

Analyzing budget and election data for a class assignment.

analyzing-stock-market-data

Uses VBA to analyze stock market data from 2014 to 2016. For each year, identifies the percentage change from opening price to closing price for each stock, as well as its total volume. Identifies the stock with the greatest percentage increase and highest total volume.

brick-house-identifier

The deployment branch contains code for the corresponding Heroku website (https://brick-house-identifier.herokuapp.com/). The code for the model development can be found at https://github.com/gitgranthub/target_market.

creating-my-first-website

d3-challenge

employee_retention_via_phased_retirement

This research suggests that implementation of a phased retirement program may be used as a tool to retain dedicated workers.

etl-project

evaluating-cancer-treatments

Investigated the effects of four cancer treatments on tumor size in mice using correlation and regression. Used Pandas to merge and clean data; used Matplotlib to visualize data.

identifying-vacation-spots

Used Jupyter Notebook, Pandas, and Matplotlib to visualize regression analysis on data extracted from Open Weather API. Used Google Maps API to visualize differences in humidity between cities, and to show hotels for locations experiencing great weather.

investigating-school-performance

Using Pandas to compute descriptive statistics on student and school data.

investigating_chicago_crime

Investigated the influence of economic, birth, and health factors on Chicago neighborhood homicide rates using correlation, simple regression, and multiple regression analyses. Created a heatmap to visualize differences in homicide rates between Chicago neighborhoods.

investigating_employee_data

Created PostgreSQL database and performed SQL queries on employee information. Performed additional analysis with Pandas via SQLAlchemy.

sql-handlers

Used to perform CRUD operations on SQL or Access Databases

tableau-challenge

target_market

Using Machine Learning to classify if a property is brick, siding or unknown. Keras, Tensorflow.

using-javascript

using-js-leaflet

Used JavaScript Leaflet library to visualize earthquake data.

using-js-plotly

using_sql_alchemy

web-scraping-demo

worldwide-ufo-sightings

This is an interactive website that displays information from UFO sightings that occurred in North America between the years 1906 and 2014. Data were supplied to visualizations via Python Flask API calls to a SQLite database. Visualizations were created with HTML, CSS, and JavaScript Leaflet and D3 libraries.