Author: Martin Frigaard
How to calculate a rolling average in R
Rolling or moving averages are a way to reduce noise and smooth time series data. During the Covid-19 pandemic, rolling averages have been used by researchers and journalists around the […]
Update: How to geocode a CSV of addresses in R
This post is an update from the previous post, “How to geocode a CSV of addresses in R”. We will be using the ggmap package again, and be sure to investigate the usage […]
A roundup of coronavirus dashboards, datasets and resources
Access and availability of data on the novel coronavirus and the disease it causes, Covid-19, are essential for understanding how the virus spreads, who is most likely to get it, […]
Diagnosing the accuracy of your linear regression in R
In this post we’ll cover the assumptions of a linear regression model. There are a ton of books, blog posts, and lectures covering these topics in greater depth (and we’ll […]
How to explore correlations in R
This post will cover how to measure the relationship between two numeric variables with the corrr package. We will look at how to assess a variable’s distribution using skewness, kurtosis, […]
How to download YouTube data in R using “tuber” and “purrr”
Accessing YouTube’s metadata such as views, likes, dislikes and comments is simple in R thanks to thetuber package by Gaurav Sood. Sood wrote an excellent, easy-to-use package for accessing the […]
How to build a website with Blogdown in R
Want to build a website right in RStudio? blogdown is an R package that allows you to create websites from R markdown files using Hugo, an open-source static site generator […]
How to access APIs in R
APIs, or application program interfaces, are a way for people to access data in a plain text format using multiple programming languages. Many websites, organizations and services offer APIs for […]
Pivoting data from columns to rows (and back!) in the tidyverse
TLDR: This tutorial was prompted by the recent changes to the tidyr package (see the tweet from Hadley Wickham below). Two functions for reshaping columns and rows (gather() and spread()) […]
From deep learning to clean_names(), resources from Data Journalism in R
Books to check out Deep Learning in R This text is from by Francois Chollet and J. J. Allaire. The authors cover these topics in-depth with plenty of code examples. Analyzing Baseball Data […]
Scraping HTML tables and downloading files with R
The Department of Criminal Justice in Texas keeps records of every inmate they execute. This tutorial will show you how to scrape that data, which lives in a table on […]
How to install R on a Jupyter notebook
This post walks through how to install R on a Jupyter notebook, load in data and build a visualization. Start by installing python using homebrew. Install python Open Terminal and enter the […]
How to get Twitter data with rtweet in R
There’s a new process for getting data from Twitter with rtweet, so I put this document together as a guide for users looking for help in setting up the API, […]
How to build an animated map of tweets about the NBA finals in R
After beating the Cleveland Cavaliers in four games, the Golden State Warriors have won the 2018 NBA finals. We decided to build an animated map of Twitter mentions of #DubNation […]
Getting started with stringr for textual analysis in R
Manipulating characters – a.k.a. non-numerical data – is an essential skill for anyone looking to visualize or analyze text data. This tutorial will go over a few of the base […]
How to merge and clean up multiple CSVs using R
This tutorial solves a problem I was having when working through the exploratory data analysis exercises in Doing Data Science by Cathy O’Neil and Rachel Schutt. I highly recommended picking up a copy for yourself. […]
Getting started with data visualization in R using ggplot2
Creating a customized graph that communicates your ideas effectively can be challenging. This tutorial will introduce you to the popular R package ggplot2, its underlying grammar of graphics, and show […]
How to manipulate data with dplyr in R
In the last tutorial we introduced the concept of tidy data, which is characterized by having one observation per row, and one variable per column. We also went over how to change to […]
How to explore and manipulate a dataset from the fivethirtyeight package in R
The fivethirtyeight R package – released by Albert Y. Kim, Chester Ismay, and Jennifer Chunn last March – contains dozens of datasets used in FiveThirtyEight news articles like “A Handful Of Cities Are Driving […]
Getting Started with tidyverse in R
The tidyverse is a collection of R packages developed by RStudio’s chief scientist Hadley Wickham. These packages work well together as part of larger data analysis pipeline. To learn more […]
Getting Started With R in RStudio Notebooks
R is a powerful statistical programming language for manipulating, graphing, and modeling data. One of the major positive aspects of R is that it’s open-source (free). But “free” in this […]