Tag Archives: R
Placing Text Within an R Plot
I often add text in plots. This text can be a legend or labeling certain points, in which case assigning it x and y coordinates are easy. Often times, the text is descriptive, e.g. the slope of a line or the number of observations in a sample. Customizing (x,y) coordinates in that case is simple […]
ggstance for Two Treatment Effects
I was making a plot comparing how five outcomes varied by whether they occurred during Period 1 or Period 2. I wanted to plot the standard error of each point, which would often cause points to become hidden by the error bars. The obvious answer is to shift the 10 points (5 outcomes, 2 treatments) […]
Add Interaction Variables as Needed
In today’s edition of Becoming a Functional Data Analyst, I am writing to remind myself not to create interaction variables during data munging. That is, when acquiring, cleaning, and aggregating data, I find it easier to not interact variables I will later need. Instead, it is easier to keep variables as they are and only […]
Making HTML Tables in R
TL;DR: htmlTable and tableHTML are better than xtable for creating HTML tables in R. Today, I had to make tables for a Word document, meaning I could not convert my R table to Latex code. (I know I know, pandoc. Just another crusty old thing to learn.) In the past, I had used xtable, but […]
Reason #1 Why I Don’t like ggplot
[UPDATE: My best use of academic Twitter yet. I tweeted a link to this post and quickly got pwnd by the internet. What I learned: there is a function, ggsave(), that does this that I did not know about. So use that instead of the hacky workaround I came up with. Never would’ve learned if […]
The Lazy Way Around Updating my gcc Compiler
Today, I need to launch a new AWS EC2 instance to collect some more tweets. Since I have done this several times, I used my AWS console to replicate the most recent instance I created that collects tweets. Everything ran smoothly until I tried to install streamR, my go to library for collecting tweets in […]
A Slightly Less Simple Function for Forest Plots
This post is a sequel to my wildly popular – ok, not wildly popular, but very useful for me – post documenting my function to create a forest plot. Recently, I made models using cross-validation via R’s caret package. The train() function does the heavy lifting, but the problem is that its output is a […]
In R, use openxlsx instead of xlsx
I recently had to read an Excel spreadsheet into R. Why Excel? The original data were in a Google Sheet, and it appears that Google downloads everything to a .xlsx. (There HAS to be a way to download to .csv, but I did not feel like searching.) Opening the file – it was only 12 […]
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