Merge the datasets on the keys

Combines/merges multiple datasets with specified keys attribute.

Usage

merge_datasets(
  selector_list,
  datasets,
  join_keys,
  merge_function = "dplyr::full_join",
  anl_name = "ANL"
)

Arguments

selector_list

(reactive) output from data_extract_multiple_srv() or a reactive named list of outputs from data_extract_srv(). When using a reactive named list, the names must be identical to the shiny ids of the respective data_extract_ui().

datasets

(named list of reactive or non-reactive data.frame) object containing data as a list of data.frame. When passing a list of non-reactive data.frame objects, they are converted to reactive data.frame objects internally.

join_keys

(join_keys) of variables used as join keys for each of the datasets in datasets. This will be used to extract the keys of every dataset.

merge_function

(character(1) or reactive) A character string of a function that accepts the arguments x, y and by to perform the merging of datasets.

anl_name

(character(1)) Name of the analysis dataset.

Value

merged_dataset list containing:

• expr (list of call) code needed to replicate merged dataset;

• columns_source (list) of column names selected for particular selector; Each list element contains named character vector where:

  • Values are the names of the columns in the ANL. In case if the same column name is selected in more than one selector it gets prefixed by the id of the selector. For example if two data_extract have id x, y, then their duplicated selected variable (for example AGE) is prefixed to be x.AGE and y.AGE;

  • Names of the vector denote names of the variables in the input dataset;

  • attr(,"dataname") to indicate which dataset variable is merged from;

  • attr(, "always selected") to denote the names of the variables which need to be always selected;

• keys (list) the keys of the merged dataset;

• filter_info (list) The information given by the user. This information defines the filters that are applied on the data. Additionally it defines the variables that are selected from the data sets.

Details

Internally this function uses calls to allow reproducibility.

This function is often used inside a teal module server function with the selectors being the output of data_extract_srv or data_extract_multiple_srv.

# inside teal module server function

response <- data_extract_srv(
  id = "reponse",
  data_extract_spec = response_spec,
  datasets = datasets
)
regressor <- data_extract_srv(
  id = "regressor",
  data_extract_spec = regressor_spec,
  datasets = datasets
)
merged_data <- merge_datasets(list(regressor(), response()))

Examples

library(shiny)
library(teal.data)

X <- data.frame(A = c(1, 1:3), B = 2:5, D = 1:4, E = letters[1:4], G = letters[6:9])
Y <- data.frame(A = c(1, 1, 2), B = 2:4, C = c(4, 4:5), E = letters[4:6], G = letters[1:3])
join_keys <- join_keys(join_key("X", "Y", c("A", "B")))

selector_list <- list(
  list(
    dataname = "X",
    filters = NULL,
    select = "E",
    keys = c("A", "B"),
    reshape = FALSE,
    internal_id = "x"
  ),
  list(
    dataname = "Y",
    filters = NULL,
    select = "G",
    keys = c("A", "C"),
    reshape = FALSE,
    internal_id = "y"
  )
)

data_list <- list(X = reactive(X), Y = reactive(Y))

merged_datasets <- isolate(
  merge_datasets(
    selector_list = selector_list,
    datasets = data_list,
    join_keys = join_keys
  )
)

paste(merged_datasets$expr)
#> [1] "ANL_1 <- X %>% dplyr::select(A, B, E)"                    
#> [2] "ANL_2 <- Y %>% dplyr::select(A, B, G)"                    
#> [3] "ANL <- ANL_1"                                             
#> [4] "ANL <- dplyr::full_join(ANL, ANL_2, by = c(\"A\", \"B\"))"