2020 has been a tough year, and I've been doing my best to keep busy (and distracted from all the insanity - both at the personal and worldwide levels). Earlier this year, I took a course in machine learning techniques and have been working on applying...

2020 has been a tough year, and I've been doing my best to keep busy (and distracted from all the insanity - both at the personal and worldwide levels). Earlier this year, I took a course in machine learning techniques and have been working on applying...

UFO Sightings by Shape and Year Earlier last week, I taught part 2 of a course on using R and tidyverse for my work colleagues. I wanted a fun dataset to use as an example for coding exercises throughout. There was really only one choice.I found this great dataset through ...

UFO Sightings by Shape and Year Earlier last week, I taught part 2 of a course on using R and tidyverse for my work colleagues. I wanted a fun dataset to use as an example for coding exercises throughout. There was really only one choice. I found this great dataset through ...

I've spent the month of April blogging my way through the tidyverse, while using my reading dataset from 2019 as the example. Today, I thought I'd bring many of those analyses and data manipulation techniques together to do a post about my reading habits for the year. library(tidyverse) ## -- Attaching ...

Here we are at the last post in Blogging A to Z! Today, I want to talk about adding additional axes to your ggplot, using the options for fill or color. While these aren't true z-axes in the geometric sense, I think of them as a third, z, axis.Some ...

Yesterday, I talked about scale_x. Today, I'll continue on that topic, focusing on the y-axis.The key to using any of the scale_ functions is to know what sort of data you're working with (e.g., date, continuous, discrete). Yesterday, I talked about sc...

These next two posts will deal with formatting scales in ggplot2 - x-axis, y-axis - so I'll try to limit the amount of overlap and repetition.Let's say I wanted to plot my reading over time, specifically as a cumulative sum of pages across the year. My...

In this series, I've covered five terms for data manipulation:arrangefiltermutateselectsummariseThese are the verbs that make up the grammar of data manipulation. They all work with group_by to perform these functions groupwise.There are scoped version...

This will be a very short post for a line of code I've found unbelievably useful as I analyze data for work. I'm working with datasets containing millions of rows of data. (The most recent one I worked with had about 13 million records.) Because R load...

One of the easiest ways to make a beautiful ggplot is by using a theme. ggplot2 comes with a variety of pre-existing themes. I'll use the genre statistics summary table I created in yesterday's post, and create the same chart with different themes.libr...

Today, we'll finally talk about summarise! It's very similar to mutate, but instead of adding or altering a variable in a dataset, it aggregates your data, creating a new tibble with the columns containing your requested summary data. The number of rows will be equal to the number of groups ...

The tidyverse is full of functions for reading data, beginning with "read_". The read_csv I've used to access my reads2019 data is one example, falling under the read_delim functions. read_tsv allows you to quickly read in tab-delimited files. And you ...

Two years ago, when I did Blogging A to Z of R, I talked about qplots. qplots are great for quick plots - which is why they're named as such - because they use variable types to determine the best plot to generate. For instance, if I give it a ...

We've used ggplots throughout this blog series, but today, I want to introduce another package that helps you customize scales on your ggplots - the scales package. I use this package most frequently to format scales as percent. There aren't a lot of g...

This will be a quick post on another tidyverse function, order_by. I'll admit, I don't use this one as often as arrange. It can be useful, though, if you don't want to permanently change the order of your dataset but want to use functions that require ...

Today, we'll start digging into some of the functions used to summarise data. The full summarise function will be covered for the letter S. For now, let's look at one function from the tidyverse that can give some overall information about a dataset: n...

Today, we finally talk about the mutate function! I've used it a lot throughout the series so far, so it's nice to get to discuss what it is and how it works.The mutate function is used anytime you want create or modify a variable. It works with pretty much ...

When visualizing data, outliers and skewed data can have a huge impact, potentially making your visualization difficult to understand. We can use many of the tricks covered so far to deal with those issues, such as using filters to remove extreme value...