Add metadata to the raw data

Description

Add metadata to the raw data

Usage

add_insee_metadata(df)

Arguments

Details

Add metadata to the raw data obtained from get_insee_idbank or get_insee_dataset

Value

a tibble with the data given as parameter plus the corresponding metadata

Examples

library(magrittr)

data =
 get_insee_idbank("001694061") %>%
 add_insee_metadata()

Add a title column to the idbank list dataset

Description

Add a title column to the idbank list dataset

Usage

add_insee_title(df, n_split, lang = "en", split = TRUE, clean = TRUE)

Arguments

Details

this function uses extensively the get_insee_title function. Then, it should be used on an already filtered dataset, not on the full idbank dataset (cf. get_insee_title). The number of separators in the official INSEE title can vary and is not normalized. Beware all title columns created may not be a cleaned dimension label.

Value

the same dataframe but with one or several title columns

Examples

library(magrittr)
library(dplyr)

idbank_empl =
 get_idbank_list("EMPLOI-SALARIE-TRIM-NATIONAL") %>% #employment
 slice(1:15) %>%
 add_insee_title()

Get the title of dataset's columns

Description

Get the title of dataset's columns

Usage

get_column_title(dataset = NULL)

Arguments

Value

a dataframe

Examples

column_titles_all_dataset = get_column_title()

column_titles = get_column_title("CNA-2014-CONSO-MEN")

Download a full INSEE's dataset list

Description

Download a full INSEE's dataset list

Usage

get_dataset_list()

Details

the datasets returned are the ones available through a SDMX query

Value

a tibble with 5 columns : id, Name.fr, Name.en, url, n_series

Examples

insee_dataset = get_dataset_list()

Download a full INSEE's series key list

Description

Download a full INSEE's series key list

Usage

get_idbank_list(..., dataset = NULL, update = FALSE)

Arguments

Details

Download a mapping dataset between INSEE series keys (idbank) and SDMX series names. Under the hood the get_idbank_list uses download.file function from utils, the user can change the mode argument with the following command : Sys.getenv(INSEE_download_option_idbank_list = "wb") If INSEE makes an update, the user can also change the zip file downloaded, the data file contained in the zip and data the separator : Sys.setenv(INSEE_idbank_dataset_path = "new_zip_file_link") Sys.setenv(INSEE_idbank_sep = ",") Sys.setenv(INSEE_idbank_dataset_file = "new_data_file_name")

Value

a tibble the idbank dataset

Examples

# download datasets list
dt = get_dataset_list()
# use a dataset name to retrieve the series key list related to the dataset
idbank_list = get_idbank_list('CNT-2014-PIB-EQB-RF')

Get data from INSEE BDM database with a SDMX query link

Description

Get data from INSEE BDM database with a SDMX query link

Usage

get_insee(link, step = "1/1")

Arguments

Details

Get data from INSEE BDM database with a SDMX query link. This function is mainly for package internal use. It is used by the functions get_insee_dataset, get_insee_idbank and get_dataset_list. The data is cached, hence all queries are only run once per R session. The user can disable the download display in the console with the following command : Sys.setenv(INSEE_download_verbose = "FALSE"). The use of cached data can be disabled with : Sys.setenv(INSEE_no_cache_use = "TRUE"). All queries are printed in the console with this command: Sys.setenv(INSEE_print_query = "TRUE").

Value

a tibble containing the data

Examples

insee_link = "http://www.bdm.insee.fr/series/sdmx/data/SERIES_BDM"
insee_query = file.path(insee_link, paste0("010539365","?", "firstNObservations=1"))
data = get_insee(insee_query)

Get dataset from INSEE BDM database

Description

Get dataset from INSEE BDM database

Usage

get_insee_dataset(
  dataset,
  startPeriod = NULL,
  endPeriod = NULL,
  firstNObservations = NULL,
  lastNObservations = NULL,
  includeHistory = NULL,
  updatedAfter = NULL,
  filter = NULL
)

Arguments

Details

Get dataset from INSEE BDM database

Value

a tibble with the data

Examples

insee_dataset = get_dataset_list()
idbank_ipc = get_idbank_list("IPC-2015")

#example 1
data = get_insee_dataset("IPC-2015", filter = "M+A.........CVS..", startPeriod = "2015-03")

#example 2
data = get_insee_dataset("IPC-2015", filter = "A..SO...VARIATIONS_A....BRUT..SO",
 includeHistory = TRUE, updatedAfter = "2017-07-11T08:45:00")

Get data from INSEE series idbank

Description

Get data from INSEE series idbank

Usage

get_insee_idbank(
  ...,
  limit = TRUE,
  startPeriod = NULL,
  endPeriod = NULL,
  firstNObservations = NULL,
  lastNObservations = NULL,
  includeHistory = NULL,
  updatedAfter = NULL
)

Arguments

Details

Get data from INSEE series idbanks. The user can disable the download display in the console with the following command : Sys.setenv(INSEE_download_verbose = "FALSE")

Value

a tibble with the data

Examples

#example 1 : import price index of industrial products and turnover index : manufacture of wood
data = get_insee_idbank("001558315", "010540726")

#example 2 : unemployment data

library(magrittr)
library(dplyr)
library(ggplot2)

df_idbank_list_selected =
  get_idbank_list("CHOMAGE-TRIM-NATIONAL") %>%  #unemployment dataset
  filter(SEXE == 0) %>% #men and women
  add_insee_title()

idbank_list_selected = df_idbank_list_selected %>% pull(idbank)

unem = get_insee_idbank(idbank_list_selected)

#example 3 : French GDP growth rate

df_idbank_list_selected =
  get_idbank_list("CNT-2014-PIB-EQB-RF") %>%  # Gross domestic product balance
  filter(FREQ == "T") %>% #quarter
  filter(OPERATION == "PIB") %>% #GDP
  filter(NATURE == "TAUX") %>% #rate
  filter(CORRECTION == "CVS-CJO") #SA-WDA, seasonally adjusted, working day adjusted

idbank = df_idbank_list_selected %>% pull(idbank)

data = get_insee_idbank(idbank) %>%
  add_insee_metadata()

#plot
ggplot(data, aes(x = DATE, y = OBS_VALUE)) +
geom_col() +
ggtitle("French GDP growth rate, quarter-on-quarter, sa-wda") +
labs(subtitle = sprintf("Last updated : %s", data$TIME_PERIOD[1]))

Get title from INSEE series idbank

Description

Get title from INSEE series idbank

Usage

get_insee_title(..., lang = "en")

Arguments

Details

Query INSEE website to get series title from series key (idbank). Any query to INSEE database can handle around 400 idbanks at maximum, if necessary the idbank list will then be splitted in several lists of 400 idbanks each. Consequently, it is not advised to use it on the whole idbank dataset, the user should filter the idbank dataset first.

Value

a character vector with the titles

Examples

#example 1 : industrial production index on manufacturing and industrial activities
title = get_insee_title("010537900")

#example 2 : automotive industry and overall industrial production
library(magrittr)
library(dplyr)
library(stringr)

idbank_list_selected =
  get_idbank_list("IPI-2015") %>% #industrial production index dataset
  filter(FREQ == "M") %>% #monthly
  filter(NATURE == "INDICE") %>% #index
  filter(CORRECTION  == "CVS-CJO") %>% #Working day and seasonally adjusted SA-WDA
  filter(str_detect(NAF2,"^29$|A10-BE")) %>% #automotive industry and overall industrial production
  mutate(title = get_insee_title(idbank))

Search a pattern among insee datasets and idbanks

Description

Search a pattern among insee datasets and idbanks

Usage

search_insee(pattern = ".*")

Arguments

Details

The data related to idbanks is stored internally in the package and might the most up to date. The function ignores accents and cases.

Value

the dataset and idbank table filtered with the pattern

Examples

# example 1 : search one pattern, the accents do not matter
writeLines("the word 'enqu\U00EAte' (meaning survey in French) will match with 'enquete'")
dataset_enquete = search_insee("enquete")

# example 2 : search multiple patterns
dataset_survey_gdp = search_insee("Survey|gdp")

# example 3 : data about paris
data_paris = search_insee('paris')

# example 4 : all data
data_all = search_insee()

Split the title column in several columns

Description

Split the title column in several columns

Usage

split_title(df, title_col_name, pattern, n_split = "max", lang = NULL)

Arguments

Details

The number of separators in the official INSEE title can vary and is not normalized. Beware all title columns created may not be a cleaned dimension label.

Value

the same dataframe with the title column splitted

Examples

library(magrittr)

# quarterly payroll enrollment in the construction sector
data_raw = get_insee_idbank("001577236")

data = data_raw %>%
  split_title()