Loop filter data frame and export resulting subsets-CodePudding

I have the following dataset:

df <- data.frame(CountryCode = c("AT", "AT", "DE", "DE", "UK", "UK", "NZ", "NZ"),
  GDP = c("120", "125", "300", "320", "250", "265", "50", "60"),
  Year = c("2009", "2010","2009", "2010","2009", "2010","2009", "2010")
)

I want to filter using a loop based on each unique value in column CountryCode and assign each subset to an own unique dataframe. What is the most concise way to do so?

CodePudding user response：

You can use split for that:

split(df, df$CountryCode)
$AT
#   CountryCode GDP Year
# 1          AT 120 2009
# 2          AT 125 2010

# $DE
#   CountryCode GDP Year
# 3          DE 300 2009
# 4          DE 320 2010

# $NZ
#   CountryCode GDP Year
# 7          NZ  50 2009
# 8          NZ  60 2010

# $UK
#   CountryCode GDP Year
# 5          UK 250 2009
# 6          UK 265 2010

CodePudding user response：

Another possible solution, based on dplyr:

library(dplyr)

df %>% group_by(CountryCode) %>% group_split()

#> <list_of<
#>   tbl_df<
#>     CountryCode: character
#>     GDP        : character
#>     Year       : character
#>   >
#> >[4]>
#> [[1]]
#> # A tibble: 2 × 3
#>   CountryCode GDP   Year 
#>   <chr>       <chr> <chr>
#> 1 AT          120   2009 
#> 2 AT          125   2010 
#> 
#> [[2]]
#> # A tibble: 2 × 3
#>   CountryCode GDP   Year 
#>   <chr>       <chr> <chr>
#> 1 DE          300   2009 
#> 2 DE          320   2010 
#> 
#> [[3]]
#> # A tibble: 2 × 3
#>   CountryCode GDP   Year 
#>   <chr>       <chr> <chr>
#> 1 NZ          50    2009 
#> 2 NZ          60    2010 
#> 
#> [[4]]
#> # A tibble: 2 × 3
#>   CountryCode GDP   Year 
#>   <chr>       <chr> <chr>
#> 1 UK          250   2009 
#> 2 UK          265   2010