2

I need to write a function involving subsetting a df by a variable n bins. Like, if n is 2, then subsample the df some number of times in two bins (from the first half, then from the second half). If n is 3, subsample in 3 bins (first 1/3, second 1/3, third 1/3). I've been doing this for different lengths of n manually so far, and I know there must be a better way to do it. I want to write it into a function with n as an input, but I can't make it work so far. Code below.

# create df
df <- data.frame(year = c(1:46), 
                 sample = seq(from=10,to=30,length.out = 46) + rnorm(46,mean=0,sd=2) )
# real df has some NAs, so we'll add some here
df[c(20,32),2] <- NA

this df is 46 years of sampling. I want to pretend instead of 46 samples, I only took 2, but at one random year in the first half (1:23), and one random year in the second half (24:46).

# to subset in 2 groups, say, 200 times
# I'll make a df of elements to sample
samplelist <- data.frame(firstsample = sample(1:(nrow(df)/2),200,replace = T), # first sample in first half of vector
                         secondsample = sample((nrow(df)/2):nrow(df),200, replace = T) )# second sample in second half of vector
samplelist <- as.matrix(samplelist)


# start a df to add to
plot_df <- df %>% mutate(first='all',
                               second = 'all',
                               group='full')

# fill the df using coords from expand.grid
for(i in 1:nrow(samplelist)){

  plot_df <<- rbind(plot_df,
                          df[samplelist[i,] , ]   %>% 
                            mutate(
                              first = samplelist[i,1],
                              second = samplelist[i,2],
                              group = i
                            )) 
  print(i)
}

(If we can make it skip samples on "NA" sample years, that would be extra good).

So, if I wanted to do this for three points instead of two, I'd repeat the process like this:

# to subset in 3 groups 200 times
# I'll make a df of elements to sample
samplelist <- data.frame(firstsample = sample(1:(nrow(df)/3),200,replace = T), # first sample in first 1/3
                         secondsample = sample(round(nrow(df)/3):round(nrow(df)*(2/3)),200, replace = T),  # second sample in second 1/3
                         thirdsample = sample(round(nrow(df)*(2/3)):nrow(df), 200, replace=T) # third sample in last 1/3
                         )
samplelist <- as.matrix(samplelist)

# start a df to add to
plot_df <- df %>% mutate(first='all',
                         second = 'all',
                         third = 'all',
                         group='full')

# fill the df using coords from expand.grid
for(i in 1:nrow(samplelist)){

  plot_df <<- rbind(plot_df,
                    df[samplelist[i,] , ]   %>% 
                      mutate(
                        first = samplelist[i,1],
                        second = samplelist[i,2],
                        third = samplelist[i,3],
                        group = i
                      )) 
  print(i)
}

but, I want to do this many times, sampling up to ~20 times (so in 20 bins), so this manual method is not sustainable. Can you help me write a function to say "pick one sample from n bins x times"?

btw, this is the plot I am making with the complete df:

plot_df %>%
  ggplot(aes(x=year,y=sample)) +

  geom_point(color="grey40") +

  stat_smooth(geom="line",
              method = "lm",
              alpha=.3,
              aes(color=group,
                  group=group),
              se=F,
              show.legend = F) +
  geom_line(color="grey40") +


  geom_smooth(data = plot_df %>% filter(group %in% c("full")),
              method = "lm",
              alpha=.7,
              color="black",
              size=2,
              #se=F,
              # fill="grey40
              show.legend = F
  ) +
  theme_classic()
Jake L
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2 Answers2

1

If I got you right, the following function splits your df in n bins, draws x samples from each and puts the results back into cols of a df:

library(tidyverse)

set.seed(42)

df <- data.frame(year = c(1:46), 
                 sample = seq(from=10,to=30,length.out = 46) + rnorm(46,mean=0,sd=2) )

get_df_sample <- function(df, n, x) {
  df %>% 
    # bin df in n bins of (approx.) equal length
    mutate(bin = ggplot2::cut_number(seq_len(nrow(.)), n, labels = seq_len(n))) %>% 
    # split by bin
    split(.$bin) %>%
    # sample x times from each bin
    map(~ .x[sample(seq_len(nrow(.x)), x, replace = TRUE),]) %>% 
    # keep only column "sample"
    map(~ select(.x, sample)) %>% 
    # Rename: Add number of df-bin from which sample is drawn
    imap(~ rename(.x, !!sym(paste0("sample_", .y)) := sample)) %>%
    # bind
    bind_cols() %>% 
    # Add group = rownames
    rownames_to_column(var = "group")
}
get_df_sample(df, 3, 200) %>% 
  head()
#>   sample_1 sample_2 sample_3 group
#> 1 12.58631 18.27561 24.74263     1
#> 2 19.46218 24.24423 23.44881     2
#> 3 12.92179 18.47367 27.40558     3
#> 4 15.22020 18.47367 26.29243     4
#> 5 12.58631 24.24423 24.43108     5
#> 6 19.46218 23.36464 27.40558     6

Created on 2020-03-24 by the reprex package (v0.3.0)

stefan
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1

Here's a function using loops, closer to what you started doing:

df <- data.frame(year = c(1:46), 
                 sample = seq(from=10, to=30, length.out = 46) +
rnorm(46,mean=0,sd=2))

df[c(20,32), 2] <- NA

my_function <- function(n, sample_size, data = df) {

  plot_df <- data %>% mutate(group = 'full')

  sample_matrix <- matrix(data = NA, nrow = sample_size, ncol = n)

  first_row <- 1 # First subset has 1 as first row, no matter how many subsets

  for (i in 1:n) {

    last_row <- round(first_row + nrow(df)/n - 1) # Determine last row of i-th subset
    sample_matrix[, i] <- sample(first_row:last_row, sample_size, replace = T) # Store sample directly in matrix
    first_row <- i + last_row # Determine first row for next i

    group_name <- paste("group", i, sep = "_") # Column name for i-th group
    plot_df[[group_name]] <- "all" # Column for i-th group

  }

  for (j in 1:sample_size) {

    # Creating a new data frame for new observations
    new_obs <- df[sample_matrix[j,], ]
    new_obs[["group"]] <- j
    for (group_n in 1:n) {
      new_obs[[paste0("group_", group_n)]] <- sample_matrix[j, group_n]
    }
    plot_df <- rbind(plot_df, new_obs) 
    plot_df <<- plot_df

  }
}

my_function(2, 200, data = df)
broti
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