CODEWITHSUNDEEP
rdataframetidyverse
adkane
adkane

Reputation: 1441

Grouping and nesting data produces an error in R with tidyverse

I'm trying to calculate some home range estimates for some animal tracking data. To do so the authors of the amt package recommend grouping by ID and then nesting.

But when I do so I get the following error:

Error: The groups attribute is not a data frame with its last column called .rows.

Here's an example that reproduces the error:

library(amt)
library(tidyverse)

    data(deer)
    mini_deer <- deer[1:100, ]
    nesttrk <- mini_deer %>% group_by(burst_) %>% 
      nest() 
    nesttrk

The overall aim is to get a home range size estimate per ID (or burst_ in this case)

mini_deer %>% group_by(burst_) %>%  nest(-burst_) %>%
  mutate(mcparea = map(data, ~ hr_mcp(., levels = c(0.95)) %>% hr_area)) %>%
  dplyr::select(burst_, mcparea) %>% unnest()

Upvotes: 1

Views: 893

Answers (2)

akrun
akrun

Reputation: 887128

We could use nest_by with mutate itself and then unnest the list column

library(amt)
library(dplyr)
library(tidyr)
mini_deer %>% 
    nest_by(burst_) %>%
    transmute(mcparea = list(hr_mcp(data, levels = 0.95) %>% 
                  hr_area))  %>% 
    ungroup %>%
    unnest(mcparea)
# A tibble: 5 x 4
  burst_ level what         area
   <dbl> <dbl> <chr>       <dbl>
1      1  0.95 estimate  180927.
2      2  0.95 estimate 1886603.
3      3  0.95 estimate       0 
4      4  0.95 estimate       0 
5      5  0.95 estimate   14476.

Upvotes: 3

Ronak Shah
Ronak Shah

Reputation: 388982

I have not used amt package but from the error message using nest it seems that it requires data in some specific format as nesting with dataframe works without any problem. (mini_deer %>% as.data.frame() %>% group_by(burst_) %>% nest()) but we loose the class as we are converting to dataframe.

Split and combine approach works -

library(amt)
library(tidyverse)

mini_deer %>% 
  group_split(burst_, .keep = TRUE) %>%
  map_df(~ hr_mcp(., levels = c(0.95)) %>% hr_area) %>%
  mutate(burst_ = unique(mini_deer$burst_), .before = 1)

#  burst_ level what         area
#   <dbl> <dbl> <chr>       <dbl>
#1      1  0.95 estimate  180927.
#2      2  0.95 estimate 1886603.
#3      3  0.95 estimate       0 
#4      4  0.95 estimate       0 
#5      5  0.95 estimate   14476.

Upvotes: 3

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