Compute all the elementary indicators

ind_all computes all the elementary indicators, by returning them in a list (useful for calling the other functions of coresoi for computing the composite indicator).

Usage

ind_all(data, data_ind8, emergency_name, target_unit, id_location = NULL)

Arguments

data: a dataframe containing the data to use for computing the indicators.
data_ind8: the same dataframe containing the data to use to calculate indicator 8. See Details.
emergency_name: string specifying the name of the emergency to consider. Examples could include "Coronavirus" or "Terremoto Centro Italia 2016-2017".
target_unit: the target unit for which the indicators have to be computed. It can be: "companies", "contracting_authorities" or "territory".
id_location: name of the variable in data and data_ind8 containing the geographic location of interest (e.g., provinces, regions).

Value

a list of outputs of each indicator computable for the selected target unit.

Details

This functions is a wrapper of the single functions for computing the elementary indicators. Given the data on which we want to compute them and the emergency, together with the target unit, the function calls each "elementary" function for computing the single red flags, according to the specified target. In particular:

data and data_ind8 are two versions of the same dataframe, containing the information about single contracts, to be used for computing the elementary indicators. As indicator 8 works on the contract variants, given the potential "1-n" relationship (i.e., "one contract - more variants"), data_ind8 must be a longer (unnested) version of data, which includes the information about the variants (hence, some rows have duplicated columns, except for those related to the variants). In data, we suggest to include a column with a "nested" data frame related to the variants, to be unnested and placed in data_ind8 (see the example).
Argument target_unit specifies the target for computing the indicators. On this basis, specific functions are called for computing the suitable set of indicators. In particular, if target_unit = "companies", then elementary indicators 1, 2, 3, 4, 7, 8 and 9 are computed (by calling the related functions). On the other hand, if target_unit = "contracting_authorities" or target_unit = "territory", then elementary indicators 3, 4, 5, 6, 8 and 9 are obtained. In the latter case, the user has to specify (through id_location) the name of the variable in data (and data_ind8) that relates to the territorial location of interest (e.g., it could be province code/name).

NOTE: for the moment, it works only on Italian data (BDNCP).

Examples

if (FALSE) {
if (interactive()) {
  # sample of 100k contracts
  set.seed(12345)
  i <- sample(1:nrow(mock_data_core), size = 1e5)
  mock_sample0 <- mock_data_core[sort(i), ]

  # indicators for companies
  mock_sample <- tidyr::unnest(mock_sample0, aggiudicatari, keep_empty = TRUE)
  mock_sample_variants <- tidyr::unnest(mock_sample, varianti, keep_empty = TRUE)

  out_companies <- ind_all(
    data = mock_sample,
    data_ind8 = mock_sample_variants,
    emergency_name = "coronavirus",
    target_unit = "companies"
  )

  # indicators for contracting authorities
  mock_sample_ca <- mock_sample0
  mock_sample_ca_variants <- tidyr::unnest(mock_sample_ca, varianti, keep_empty = TRUE)
  out_contrauth <- ind_all(
    data = mock_sample_ca,
    data_ind8 = mock_sample_ca_variants,
    emergency_name = "coronavirus",
    target_unit = "contracting_authorities"
  )
}
}