Ridgeline plots is a great way to visualize changes in multiple distributions/histogram either over time or space. It was initially called as joyplots, for a brief time. ggridges package from UT Austin professor Claus Wilke lets you make ridgeline plots in combinaton with ggplot. Here is how Claus describes the ridgeline plot with a brief […]
R Tips
Skimr: A R Package to Skim Summary Data Effortlessly
Exploring your data while dong analysis is extremely important. skimr, an R package, from rOpenSci is a great package that helps you get the summary statistics in a nice way, so you can quickly skim your data summary and understand it better. If you have not heard of rOpenSci, it is a non-profit initiative founded […]
5 Big Ideas Behind Tidy Evaluation
Ever wondered, how easy it is to write dataframe manipulation code without repeating yourself while using dplyr ? For example, if you are filtering a dataframe, you simply write instead of writing like this where you need to refer the dataframe multiple times and use “$” to access variables in the dataframe. The reason why […]
Why can’t ggplot2 use %>% instead of “+”?
Have you ever mixed up dplyr’s pipe operator or magittr %>% with ggplot’s “+” while piping dplyr commands with ggplot2, you are not alone. Depending on where you misused “%>%” for “+”, you might get confusing errors like Error: Mapping must be created by `aes()` or `aes_()` Error in as.vector(x, “character”) : cannot coerce type […]
6 Most Useful dplyr Commands to Manipulate a Data Frame in R
dplyr is one of the R packages developed by Hadley Wickham to manipulate data stored in data frames. Data frame is a two-dimensional data structure, where each column can contain a different type of data, like numerical, character and factors. In case you wondered the meaning of the word “dplyr”, it is like “pliers” for […]