How can I aggregate the dates column per month and date?
library(data.table)
df <- data.table(dates = c('2017-01-01', '2017-01-05'))
chosen_col <- 'dates'
Tried the following which does not work:
df[, .(n = .N), by = str_sub(chosen_col, 1, 7)]
df[, .(n = .N), by = eval(str_sub(chosen_col, 1, 7))]
EDIT:
So the question is how do I pass a character vector to a function inside the by argument. Fully aware of workarounds for the date problem.
You can use get():
df[, .(n = .N), by = substring(get(chosen_col), 6)]
substring n
1: 01-01 1
2: 01-05 1
We can use get to use chosen_col as a column name.
library(data.table)
#Convert to actual date
df[, (chosen_col) := as.Date(get(chosen_col))]
#Separate into month and date
df[, c('month', 'date') := list(format(get(chosen_col), "%m"),
format(get(chosen_col), "%d"))]
#Count number of rows for each month and date
df[, .(n = .N), .(month, date)]
