R-Project No Applicable Method For 'Meta' Applied to an Object of Class "Character"

When using TermDocumentMatrix, no applicable method for 'meta' applied to an object of class character

You need to pass a proper content transformer to tm_map, not an arbitrary character manipulating function

doc <- tm_map(doc, content_transformer(function(x) 
    gsub(x, pattern = "buy", replacement = "bought")))

No applicable method for 'extract_' applied to an object of class character

The problem is in this case was, as was pointed out in the comments, that the wrong library was used to execute the code. The solution therefore is to specify the library in the code:

lut <- data.table(value = names(DT))[
  , variable := value %>% 
    shift() %>% 
    like("c\\d{1,2}") %>% 
    cumsum() %>% 
    magrittr::add(1L) %>% 
    magrittr::extract(c("id", "sex", "age", "race", "ethn"),. )][]

no applicable method for 'extract_parameter_set_dials' applied to an object of class workflow

The tidymodels packages recently had releases of dials and other packages (like workflows) that added this new generic:

library(tidymodels)
tidymodels_prefer()
data(cells, package = "modeldata")
cells <- cells[, -1] # minus case

svm_rec <- recipe(class ~ ., data = cells) |> 
    step_YeoJohnson(all_numeric_predictors()) |> 
    step_normalize(all_numeric_predictors())

svm_spec <- svm_rbf(cost = tune(), rbf_sigma = tune()) |> 
    set_engine("kernlab") |> 
    set_mode("classification")

svm_wflow <- workflow() |> 
    add_model(svm_spec) |> 
    add_recipe(svm_rec)

svm_wflow |> 
    extract_parameter_set_dials() |>
    update(rbf_sigma = rbf_sigma(c(-7, -1)))
#> Collection of 2 parameters for tuning
#> 
#>  identifier      type    object
#>        cost      cost nparam[+]
#>   rbf_sigma rbf_sigma nparam[+]

^{Created on 2022-04-02 by the reprex package (v2.0.1)}

You can read more here, and we recommend updating your packages from CRAN.

no applicable method for 'prep' applied to an object of class

@importFrom recipes prep bake had to be added to the .R file

Error in UseMethod(select) : no applicable method for 'select' applied to an object of class character

Two problems:

• The first argument for your return_coef function is a data.frame named df1, yet you are calling it with df1$date2 (a string). I think you should instead start with

  mapply(return_coef, list(df1), df1$date2, df1$Category)
  

  (though this does error currently, see the next bullet).

  The list(df1) in this case means that the whole df1 will be passed as the first argument for each of the pairs from df1$date2 and df1$Category.

• It now fails with argument "var1" is missing, with no default, but I suspect you were working towards that. I'll choose a couple of random names and ... something happens.

Ultimately, the function is fine as-is, just change your mapply use as:

mapply(return_coef, list(df1), df1$date2, df1$Category, var1 = "a1", var2 = "a2")
# [1] 6.539702 4.000000 1.000000 3.000000

Because both var1 and var2 are length-1, they are recycled for all calls to return_coef (as their named arguments).

Since you're using dplyr, this can be neatly put into a pipe a little more directly than using cbind(...):

library(dplyr)
  df1 %>%
    transmute(
      date2, Category,
      coef = mapply(return_coef, list(cur_data()), date2, Category, var1 = "a1", var2 = "a2")
    )
#        date2 Category     coef
# 1 2021-06-27      ABC 6.539702
# 2 2021-07-01      ABC 4.000000
# 3 2021-07-02      ABC 1.000000
# 4 2021-07-03      ABC 3.000000

I use transmute instead of a preceding select(date2, Category) because the function needs variables present in the whole frame. I could easily have done mutate(coef=..) %>% select(date2, Category, coef) as well.

No applicable method for 'lookup_defaults' applied to an object of class character

I'm not sure if I understand correctly, but maybe it will help

with data.table package filtering is really easy

library(data.table)
library(dplyr)

Observation_clean <- Observation_clean %>% as.data.table()

Observation_clean_night <- Observation_clean[between(hour(date_recorded ), 6, 19) & # hours 
                                               between(as.Date(date_recorded ), as.Date("2020-11-04"), as.Date("2021-02-05")) # dates
]

Observation_clean_day <- Observation_clean[!between(hour(date_recorded ), 6, 19) & # hours 
                                             between(as.Date(date_recorded ), as.Date("2020-11-04"), as.Date("2021-02-05")) # dates
]

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