I have data from a logger that inserts timestamps as rows within the comma separated data. I've sorted out a way to wrangle those timestamps into a tidy data frame (thanks to the responses to this question).
The issue I'm having now is that the timestamp lines don't have the same number of comma-separated values as the data rows (3 vs 6), and readr is defaulting to reading only in only 3 columns, despite me manually specifying column types and names for 6. Last summer (when I last used the logger) readr read the data in correctly, but to my dismay the current version (2.1.1) throws a warning and lumps columns 3:6 all together. I'm hoping that there's some option for "correcting" back to the old behaviour, or some work-around solution I haven't thought of (editing the logger files is not an option).
Example code:
library(tidyverse)
# example data
txt1 <- "
,,Logger Start 12:34
-112,53,N=1,9,15,.25
-112,53,N=2,12,17,.17
"
# example without timestamp header
txt2 <- "
-112,53,N=1,9,15,.25
-112,53,N=2,12,17,.17
"
# throws warning and reads 3 columns
read_csv(
txt1,
col_names = c("lon", "lat", "n", "red", "nir", "NDVI"),
col_types = "ddcddc"
)
# works correctly
read_csv(
txt2,
col_names = c("lon", "lat", "n", "red", "nir", "NDVI"),
col_types = "ddcddc"
)
# this is the table that older readr versions would create
# and that I'm hoping to get back to
tribble(
~lon, ~lat, ~n, ~red, ~nir, ~NDVI,
NA, NA, "Logger Start 12:34", NA, NA, NA,
-112, 53, "N=1", 9, 15, ".25",
-112, 53, "N=2",12, 17, ".17"
)
Use the base read.csv then convert to typle if need be:
read.csv(text=txt1, header = FALSE,
col.names = c("lon", "lat", "n", "red", "nir", "NDVI"))
lon lat n red nir NDVI
1 NA NA Logger Start 12:34 NA NA NA
2 -112 53 N=1 9 15 0.25
3 -112 53 N=2 12 17 0.17