How to create new dataframes for each iteration in R for loop?-CodePudding

I am attempting to create new data frames for each iteration in R for loop. First, I am calculating percentiles for my data and store them as a data frame.

comparison_data = fread("data.txt",
                            stringsAsFactors=FALSE,
                            col.names=c("c2",
                                         "m1_area", "m1_distance", "m1_tags",
                                         "m2_area", "m2_distance", "m2_tags"
                                         )
                             )

m1_list <- quantile(comparison_data$m1_area, probs = c(.1, .2, .3, .4, .5, .6, .7))
m2_list <- quantile(comparison_data$m2_area, probs = c(.1, .2, .3, .4, .5, .6, .7))
m1_m2_list = as.data.frame(cbind(m1_list, m2_list))

I would like to filter my comparison_data file according to specific percentiles values and save generated data tables.

filter_data_table <- function(a, b) {
  m1_m2_filtered <- dplyr::filter(comparison_data, m1_area > a & m2_area > b)
}

for (i in m1_m2_list) {
  data_frames_list <- sapply(comparison_data, filter_data_table(m1_m2_list$m1_list[i], m1_m2_list$m2_list[i]))
  }

And I get an error:

Error in match.fun(FUN) : 
  'filter_data_table(m1_m2_list$m1_list[i], m1_m2_list$m2_list[i])' is not a function, character or symbol
In addition: Warning messages:
1: In m1_area > a :
  longer object length is not a multiple of shorter object length
2: In m2_area > b :
  longer object length is not a multiple of shorter object length

How can I solve it?

CodePudding user response：

You can try Map -

m1_m2_list = data.frame(m1_list, m2_list)
result <- Map(filter_data_table, m1_m2_list$m1_list, m1_m2_list$m2_list)

result would have list of dataframes with length same as nrow(m1_m2_list). Each dataframe would be output from one pair of m1_list and m2_list.

CodePudding user response：

It looks like it's within your sapply function.

Without reproducible data so I can understand what's going on this is my best effort.

Try:

filter_data_table <- function(x =comparison_data, a, b) {
  m1_m2_filtered <- dplyr::filter(x, m1_area > a & m2_area > b)
}

for (i in m1_m2_list) {
  data_frames_list <- sapply(comparison_data, filter_data_table, a = m1_m2_list$m1_list[i], b = m1_m2_list$m2_list[i])
}