I have this very basic question that could not find elsewhere, i have a data with a couple of millions of people who were followed over time. I would like to check using the View function the person who has the id number 505233. Or for instance i would like to check people that are in the 2nd and 3rd country specifically excluding the other countries.
I know that this code: View(df[, c("id", "country", "health")]) gives me back the variables that i am interested in, but what about more details inside the variable itself, could someone please guide me?
id country health
12442 1 8
366453 2 9
366453 2 8
505233 3 8
505233 3 10
structure(list(id = structure(c(12442, 366453, 366453, 505233,
505233), format.stata = "%9.0g"), country = structure(c(1, 2,
2, 3, 3), format.stata = "%9.0g"), health = structure(c(8, 9,
8, 8, 10), format.stata = "%9.0g")), row.names = c(NA, -5L), class = c("tbl_df",
"tbl", "data.frame"))
You can use the following:
View(df[df$id == 505233, c("id", "country", "health")])
By adding a statement prior to the comma within the square brackets, you can filter the data frame prior to Viewing it
An alternative using the tidyverse would be the following
library(dplyr)
df %>%
select(id, country, health) %>%
filter(id == 505233) %>%
View()
Some might prefer this if they find it more readable