Dplyr select_ and starts_with on multiple values in a variable list part 2

This is a continuation from my question earlier: Dplyr select_ and starts_with on multiple values in a variable list

I am collecting data from differnt sensors in various locations, data output is something like:

df<-data.frame(date=c(2011,2012,2013,2014,2015),"Sensor1 Temp"=c(15,18,15,14,19),"Sensor1 Pressure"=c(1001, 1000, 1002, 1004, 1000),"Sensor1a Temp"=c(15,18,15,14,19),"Sensor1a Pressure"=c(1001, 1000, 1002, 1004, 1000), "Sensor2 Temp"=c(15,18,15,14,19),"Sensor2 Pressure"=c(1001, 1000, 1002, 1004, 1000), "Sensor2 DewPoint"=c(10,11,10,9,12),"Sensor2 Humidity"=c(90, 100, 90, 100, 80))

The problem is (I think) similar to: Using select_ and starts_with R or select columns based on multiple strings with dplyr

I want to search for sensors for example by location so I have a list to search through the dataframe and also include the timestamp. But searching falls apart when I search for more than one sensor (or type of sensor etc). Is there a way of using dplyr (NSE or SE) to achieve this?

FindLocation = c("date", "Sensor1", "Sensor2")
df %>% select(matches(paste(FindLocation, collapse="|"))) # works but picks up "Sensor1a" and "DewPoint" and "Humidity" data from Sensor2

Also I want to add mixed searches such as:

 FindLocation = c("Sensor1", "Sensor2") # without selecting "Sensor1a"
 FindSensor = c("Temp", "Pressure") # without selecting "DewPoint" or "Humidity"

I am hoping the select combines FindSensor with FindLocation and selects Temp and Pressure data for Sensor1 and Sensor2 (without selecting Sensor1a). Returning the dataframe with the data and the columns headings:

date, Sensor1 Temp, Sensor1 Pressure, Sensor2 Temp, Sensor2 Pressure

Many thanks again!

Solution

Some functions from purrr are going to be useful. First, you use cross2 to compute the cartesian product of FindLocation and FindSensor. You'll get a list of pairs. Then you use map_chr to apply paste to them, joining the location and sensor strings with a dot (.). Then you use the one_of helper to select the colums.

library(purrr)

FindLocation = c("Sensor1", "Sensor2")
FindSensor = c("Temp", "Pressure")

columns = cross2(FindLocation, FindSensor) %>%
  map_chr(paste, collapse = ".")

df %>% select(one_of(columns))