Basic Tutorials

This section is for tutorials that focus on introductory topics using R. In most cases, I wanted to do something and couldn’t figure out how and by scouring online I eventually found it and I hope to be able to replicate that for someone!

  1. Basic Operations

In this seminar, we will go over how to install, and use R-Studio. We will discuss the different classes of data (integer, numeric, string, matrix,and data frame), as well as how to perform simple math and store data in vectors and variables.

  1. Introduction to Descriptive Statistics

In this seminar, we will go over how to create a data set to work with using the rnorm() and pnorm() functions. We will use the functions mean, median, and range to get measures of central tendency.

  1. String Manipulation using stringr and regular expressions.

Extracting text from a string, determining the length of a string, as well as generating text according to a pattern. A brief introduction to regular expressions.

  1. Plotting using ggplot2

A better alternative to the base plotting system found in R. You are given the ability to add several graphing geometries and modifying axis labels, etc.

In-Depth Tutorials

This section is devoted to going a bit more in depth: - Moving away from the base plotting system - Working exclusively with dplyr and the tidyverse ecosystem.

  1. Visualizations: stringr

Using the stringr::words, and stringr::sentences  datasets, we can see how to create new variables and examine the characteristics that make up these string oriented datasets using dplyr and ggplot2.

  1. Visualizations: babynames

Seeing how unique names exist in the babynames dataset is easy when you combine it with dplyr and stringr. Additional layers in ggplot2 are shown which help make a readable, and pretty graph.

  1. Visualizations: TV Show Ratings

Using read_html and geom_tile to scrape relevant information from a specified website to create a dataset that lists the Season, Episode Name, and User Rating of a TV show to then create a heatmap of the ratings per season, per episode.