luperrin Goto Github PK

01-kickstarter-analysis-lukeperrin

02-stock-analysis-lukeperrin

using VBA macros to analyze Wall Street stock market data

03-election-analysis-lukeperrin

module 3 challenge for using PyPoll for election analysis

04-pycityschools-lukeperrin

Module 04 Challenge with Pandas

05-pyber-lukeperrin

V. Isualize has given you and Omar a brand-new assignment. Using your Python skills and knowledge of Pandas, you’ll create a summary DataFrame of the ride-sharing data by city type. Then, using Pandas and Matplotlib, you’ll create a multiple-line graph that shows the total weekly fares for each city type. Finally, you’ll submit a written report that summarizes how the data differs by city type and how those differences can be used by decision-makers at PyBer.

06-pyweather-lukeperrin

Plot the relationship between latitude and weather parameters for more than 500 cities around the world using Python, Pandas, and the OpenWeatherMap and Google APIs.

06-world_weather_analysis

module 6 API practice and testing files

07-pewlett-hackard-analysis-lukeperrin

Module 7 challenge for SQL data analysis

08-movies-etl-lukeperrin

module 8 challenge

09-weather-analysis-lukeperrin

Module 9 Challenge: using Flask to analyze weather data and MongoDB to store the data.

10-mission-to-mars-lukeperrin

Module 10 Challenge: web scraping with HTML and CSS

11-ufo-sightings-lukeperrin

UFO sightings web app

12-bacteria-biodiversity-lukeperrin

13-mapping-earthquakes-lukeperrin

15-mechacar_statistical_analysis-lukeperrin

16-amazon_vine_analysis-lukeperrin

17-credit_risk_analysis-lukeperrin

18-cryptocurrencies-lukeperrin

19-neural_network_charity_analysis-lukeperrin

Analysis of Alphabet Soup charity organizations using neural networks

luke-ucb-testing

Test repository for UCB Data Bootcamp

purifai

predictive model for ideal SPE and LCMS method selection

purifai-lukeperrin

upgit

Another Typora image uploader