Description Usage Arguments Value Remplacement des valeurs manquantes par défaut
import_data
permet de requêter des données mongoDB pour en
faire un dataframe ou un Spark dataframe.
factor_query
permet de fabriquer la requête d'aggrégation
correspondante.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | import_data(
database,
collection,
mongodb_uri,
batch,
min_effectif,
date_inf = NULL,
date_sup = NULL,
fields = NULL,
sirets = NULL,
code_ape = NULL,
subsample = NULL,
replace_missing = NULL,
database_query_fun = query_mongodb
)
|
database |
|
collection |
|
mongodb_uri |
|
batch |
|
min_effectif |
|
date_inf |
|
date_sup |
|
fields |
|
sirets |
|
code_ape |
|
subsample |
|
replace_missing |
|
database_query_fun |
|
data.frame()
replace_missing <- list( montant_part_patronale = 0, montant_part_ouvriere = 0, montant_echeancier = 0, ratio_dette = 0, ratio_dette_moy12m = 0, montant_part_patronale_past_1 = 0, montant_part_ouvriere_past_1 = 0, montant_part_patronale_past_2 = 0, montant_part_ouvriere_past_2 = 0, montant_part_patronale_past_3 = 0, montant_part_ouvriere_past_3 = 0, montant_part_patronale_past_6 = 0, montant_part_ouvriere_past_6 = 0, montant_part_patronale_past_12 = 0, montant_part_ouvriere_past_12 = 0, apart_heures_consommees = 0, apart_heures_autorisees = 0, apart_entreprise = 0, tag_default = FALSE, tag_failure = FALSE, tag_outcome = FALSE )
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