Filter loop to create multiple data frames [duplicate]

Answer 1

df <- data.frame(topic = c("xxx", "xxx", "yyy", "yyy", "yyy", "zzz", "zzz"), 
                  high = c(52L, 27L, 89L, 99L, 43L, 21L, 90L), 
                  low = c(56L, 98L, 101L, 21L, 98L, 40L, 43L), 
                 stringsAsFactors = FALSE)

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

for (variable in unique(df$topic)) {
  assign(variable, df %>% filter (topic == variable), envir = .GlobalEnv)
}

xxx
#>   topic high low
#> 1   xxx   52  56
#> 2   xxx   27  98

yyy
#>   topic high low
#> 1   yyy   89 101
#> 2   yyy   99  21
#> 3   yyy   43  98

zzz
#>   topic high low
#> 1   zzz   21  40
#> 2   zzz   90  43

^{Created on 2019-02-13 by the reprex package (v0.2.1)}

Answer 2

you can try this:

topics <- unique(df$topic)  
y <- lapply(1:length(topics), function(x) {dt %>% filter(topic==topics[x])})
names(y) <- topics
list2env(y , envir = .GlobalEnv)

Best!