In CreRecombinase/condoR: Helper function for reading really wide tables

How to use pajRo

Let's say we have a really big csvfile, and it has a LOT of columns. Too many columns!

really_big_csvfile <- "../data-raw/lilteenyData.csv"

In this example file, we have bird sample data. Each row has a SAMPLING_EVENT_ID. For every SAMPLING_EVENT_ID we have a bunch of metadata, and then we have a column for like every kind of bird found anywhere in the dataset. A 0 indicates that that bird was not found, and otherwise the number of birds found is indicated with something other than a 0 (it's usually a number, but sometimes it's an X). What we'd rather have is a row for every non-zero bird sighting.

library(pajRo)

regular_sized_data <- read_big_data(really_big_csvfile)
head(regular_sized_data)

So this is still a lot of columns. Let's use dplyr (included in this package), and get some more info on which birds are found in which months

library(dplyr)
month_data <- select(regular_sized_data,MONTH,Bird)
head(month_data)

Do we find more kinds of birds in certain months?

group_by(month_data,MONTH) %>% summarise(n_birds=n_distinct(Bird))

Not really.

CreRecombinase/condoR documentation built on May 6, 2019, 12:52 p.m.