CODEWITHSUNDEEP
rloopsggplot2generate
Suusie
Suusie

Reputation: 149

Create loop to generate multiple plots from multiple dataframes for several designated factor names in r

best wishes for the new year.

I have a question...I would like to create a loop to generate multiple plots from multiple dataframes for several designated factor names in r.

I have different dataset with the same fish species. There are more than 50 species (plaice, flounder etc.) For each of these species I have different datasets with different data for each set, but the species used are the same. For each of these species I want to create the same ggplots and other files. Now I made the scipt so that when I fill in a species name in:

###########################
USEDSPECIES <- "Plaice"
###########################

I can run the scripts all at once to generate the plots etc. I want. The only down side is that I have to write down each species and run the whole thing like 50 times... Is there a way for me to make a kind of loop?

In the past I created several loop constructions like:

MaxValue <- rep(FALSE, length(data$Column))
tags <- unique(data $FishID)

for(i in 1:length(tags)){
  t.ss <- which(data $FishID == tags[i])
  MaxValue[t.ss][which(data$Column[t.ss] == max(data $Column[t.ss], na.rm=T))] <- TRUE
}

Only this way only one dataframe is used, in stead of multiple without indicating a factor name (as species) used.

Thank you in advance!

Upvotes: 1

Views: 47

Answers (1)

I_O
I_O

Reputation: 6911

An example of the advantages of combining the scattered dataframes and working on from there:

library(dplyr)

## example data frames for Plaice and Flounder:
df_plaice <- data.frame(FishID = rep('Plaice', 8), Weight = sample(500:800, 8))
df_flounder <- data.frame(FishID = rep('Flounder', 8), Weight = sample(500:800, 8))

## row-bind single data frames:
all_the_fish <- 
  list(df_plaice, df_flounder) |> Reduce(f = rbind)

> all_the_fish
     FishID Weight
1    Plaice    553
2    Plaice    776
## ...
15 Flounder    580
16 Flounder    794

## species-wise aggregates:
all_the_fish |>
  group_by(FishID) |>
  summarize(MaxWeight = max(Weight, na.rm = TRUE),
            AverageWeight = mean(Weight, na.rm = TRUE)
  )

# A tibble: 2 x 3
  FishID   MaxWeight AverageWeight
  <chr>        <int>         <dbl>
1 Flounder       794          674.
2 Plaice         776          620.

plotting:

all_the_fish |>
  ggplot() +
  geom_boxplot(aes(Weight)) +
  coord_flip() +
  facet_wrap(~ FishID)

enter image description here

Upvotes: 1

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