Creating new dataframes and applying a function in R, for loops

Question

I have a dataset called "weights" and I was wondering what is the most efficient way to write the following code:

library(d3treeR)
library(treemap)
library(dplyr)

myfun <- function(x){
 x <- weights %>% filter(Region %in% x) 
}

CAN<-myfun("Canada")
ON<-myfun("Ontario")
NL<-myfun("Newfoundland and Labrador")
PE<-myfun("Prince Edward Island")
NS<-myfun("Nova Scotia")
NB<-myfun("New Brunswick")
QC<-myfun("Quebec")

CAN=treemap(CAN, index=c("Level.0","Level.1"), vSize="X2015", type="index")
ON=treemap(ON, index=c("Level.0","Level.1"), vSize="X2015", type="index")
NL=treemap(NL, index=c("Level.0","Level.1"), vSize="X2015", type="index")
PE=treemap(PE, index=c("Level.0","Level.1"), vSize="X2015", type="index")
NS=treemap(NS, index=c("Level.0","Level.1"), vSize="X2015", type="index")
NB=treemap(NB, index=c("Level.0","Level.1"), vSize="X2015", type="index")
QC=treemap(QC, index=c("Level.0","Level.1"), vSize="X2015", type="index")

Thank you. I have been trying to use a for loop with unique(weights$Region) to populate these 7 dataframes.

If those 7 regions are are all of the regions, you can use split() to cut your dataframe into smaller dataframes (each smaller dataframe is stored as a list element). Then you can lapply() your treemap variable to each: — DanY
– DanY, Commented Aug 11, 2018 at 23:52

DanY · Accepted Answer · 2018-08-12 15:56:05Z

2

Succinctly, split your data into subsets by region and lapply the treemap function to each:

mylist <- split(weights, weights$Region)
result <- lapply(mylist, treemap::treemap, index=c("Level.0","Level.1"), vSize="X2015", type="index")

Update: Yikes! The question asked for "efficient" way to write code and my 2-liner with lapply lost out to an answer with 2 for loops, a cbind, and an assign. Well, what can you do... :)

edited Aug 12, 2018 at 15:56

answered Aug 11, 2018 at 23:55

DanY

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3 Comments

Esben Eickhardt Over a year ago

You probably have to add as.factor to ensure a proper split :)

DanY Over a year ago

split will do the as.factor() for you, but I agree that it's often best to be explicit.

Esben Eickhardt Over a year ago

Ok, I ran into the problem of the type being character at some point, but I guess the newest R handles it fine then.

Nar · Accepted Answer · 2018-08-12 00:12:08Z

1

something like this:

    x <- c("CAN",  "ON",  "NL", "PE", "NS", "NB", "QC")
    weights <- as.data.frame(cbind(weights=rep(c(1,2,3), 7), Region=x))

    for(i in x){
      y <- weights[weights$Region == i, ]
      assign(i, y) 
    }

in you case it would be

x <- c("CAN",  "ON",  "NL", "PE", "NS", "NB", "QC")     
for(i in x){
          y <- treemap(weights[weights$Region == i, ], index=c("Level.0","Level.1"), vSize="X2015", type="index")
          assign(i, y) 
        }

answered Aug 12, 2018 at 0:12

Nar

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Comments

Phil · Accepted Answer · 2018-08-12 15:25:53Z

1

As others stated, hard to figure out, also the d3treeR package is not available on CRAN, so I'm not sure if this would work. Using purrr::map()

library(tidyverse)
library(d3treeR)

myfun <- function(weights, Region, x){
  weights %>% 
    filter(Region %in% x) %>%
    treemap(index=c("Level.0","Level.1"), vSize="X2015", type="index")
}

Regions <- c("Canada", "Ontario", "Newfoundland and Labrador", "Prince Edward Island", "Nova Scotia", "New Brunswick", "Quebec")

results <- map(Regions, myfun, weights = weights, Region = Region)

edited Aug 12, 2018 at 15:25

answered Aug 12, 2018 at 0:07

Phil

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