Get data from INSEE series idbank
get_insee_idbank(
...,
limit = TRUE,
startPeriod = NULL,
endPeriod = NULL,
firstNObservations = NULL,
lastNObservations = NULL,
includeHistory = NULL,
updatedAfter = NULL
)Arguments
- ...
one or several series key (idbank)
- limit
by default, the function get_insee_idbank has a 1200-idbank limit. Set limit argument to FALSE to ignore the limit or modify the limit with the following command : Sys.setenv(INSEE_idbank_limit = 1200)
- startPeriod
start date of data
- endPeriod
end date of data
- firstNObservations
get the first N observations for each key series (idbank)
- lastNObservations
get the last N observations for each key series (idbank)
- includeHistory
boolean to access the previous releases (not available on all series)
- updatedAfter
starting point for querying the previous releases (format yyyy-mm-ddThh:mm:ss)
Value
a tibble with the data
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")
Examples
# \donttest{
#example 1 : import price index of industrial products and turnover index : manufacture of wood
data = get_insee_idbank("001558315", "010540726")
#> 1/1 - Data download & Dataframe build :
#>
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#>
#> Data cached : /var/folders/4d/0gnh84wj53j7wyk695q0tc_80000gn/T//RtmpLADV6b/0340378351af7c9c4993852409c6853b.rds
#>
#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()
#> Cached data has been used
#> 1/1 - Data download & Dataframe build :
#>
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#>
#> Data cached : /var/folders/4d/0gnh84wj53j7wyk695q0tc_80000gn/T//RtmpLADV6b/10502180b18dc30e6fcae0bc2c77ea4a.rds
#>
idbank_list_selected = df_idbank_list_selected %>% pull(idbank)
unem = get_insee_idbank(idbank_list_selected)
#> 1/1 - Data download & Dataframe build :
#>
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#>
#> Data cached : /var/folders/4d/0gnh84wj53j7wyk695q0tc_80000gn/T//RtmpLADV6b/953a34af53bf40111fc6d044b5adc8f0.rds
#>
#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
#> Cached data has been used
idbank = df_idbank_list_selected %>% pull(idbank)
data = get_insee_idbank(idbank) %>%
add_insee_metadata()
#> 1/1 - Data download & Dataframe build :
#>
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#>
#> Data cached : /var/folders/4d/0gnh84wj53j7wyk695q0tc_80000gn/T//RtmpLADV6b/75180c15d5ecfe6ca41459680972f91d.rds
#>
#> Cached data has been used
#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]))
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
# }