Suppose you inquire the following:
gtrends("google", geo="US")$interest_by_city
This returns how many searches for the term "google" occurred across cities in the US. However, it does not provide any information regarding which state each city belongs to.
I have tried merging this data set with several others including city and state names. Given that the same city name can be present in many states, it is unclear to me how to identify which city was the one Google Trends provided data for.
I provide below a more detailed MWE.
library(gtrendsR)
library(USAboundariesData)
data1 <- gtrends("google", geo= "US")$interest_by_city
data1$city <- data1$location
data2 <- us_cities(map_date = NULL)
data3 <- merge(data1, data2, by="city")
And this yields the following problem:
city state
Alexandria Louisiana
Alexandria Indiana
Alexandria Kentucky
Alexandria Virginia
Alexandria Minnesota
making it difficult to know which "Alexandria" Google Trends provided the data for.
Any hints in how to identify the state of each city would be much appreciated.
One way around this is to collect the cities per state and then just rbind
the respective data frames. You could first make a vector of state codes like so
states <- paste0("US-",state.abb)
I then just used purrr
for its map and reduce functionality to create a single frame
data <- purrr::reduce(purrr::map(states, function(x){
cities = gtrends("google", geo = x)$interest_by_city
}),
rbind)