I have 8 datasets (for 8 different years) with data on different countries. I want to extract the data for a given country in all the years. The proposed function filters for that country in every database, and then concatenates. (The reason I don't create a metadabase with every country, is that the databases are huge, and it's very expensive computationally). Is there a simpler way of doing this function? Also, I wanted to add a variable number of countries to filter. Is there a way of allowing the user of the function to filter for 2, 3 or 4 different countries?
Extract_Data <- function(data2014, data2015, data2016, data2017, data2018, data2019, data2020, data2021, var1) {
data14 <- data2014 %>% dplyr::filter(Country == var1)
data2015 <- data2015 %>% dplyr::filter(Country == var1)
data2016 <- data2016 %>% dplyr::filter(Country == var1)
data2017 <- data2017 %>% dplyr::filter(Country == var1)
data2018 <- data2018 %>% dplyr::filter(Country == var1)
data2019 <- data2019 %>% dplyr::filter(Country == var1)
data2020 <- data2020 %>% dplyr::filter(Country == var1)
data2021 <- data2021 %>% dplyr::filter(Country == var1)
data <- bind_rows(data2014,
data2015,
data2016,
data2017,
data2018,
data2019,
data2020,
data2021)
return(data)
}