For my first blog post in well over a year, I chose to take a further look at the NYPD’s publicly available Shooting Incident Data. The link to the public dataset used for this blog post can be found here. As always, all the code that I have written to create the visualizations below will be available to view on my Github. The visualization below is a trended look at the number of Shootings by year.
Alongside applying for jobs and also taking courses on Python and SQL, I’ve been practicing some Data Wrangling and Data Visualization Skills using dplyr and ggplot2. The Data set I’ve used was Downloaded as a .csv File from Kaggle. The dataset contains 21 different variables, however not all 21 were used. The Horror Movies Dataset contains 21 columns and contains about 32,540 movies. However, after filtering for only English movies and already released movies, about 21,000 movies remain.
UPDATE 3/29/2023: I have updated this project for tweets all the way up to March 13th, 2023 This was a project that I undertook after Graduation in 2021. I downloaded my Twitter Data, extracted the tweets, and cut out the individual words. I then visualized the most commonly tweeted words using wordcloud2. The data below includes tweets all the way up to Mid-2021. I do plan on adding in an update for 2023.
The following project below was Part One of my Submission for My Data Wrangling and Data Management Class during my Final Semester at Rutgers University. The following packages were used in the creation of Part One: tidyverse, rvest, httr, jsonlite, leaflet, and broom. For the first stage of the final project, I aim to make an interactive map in R using brewery coordinates from the Open Brewery API. In this chunk, I connected to the API, limited my search to just microbreweries, and filtered out all values that did not have a latitude and a longitude.