Nothing
## ----setup,echo=FALSE, include=FALSE------------------------------------------
# setup chunk
NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")),"true")
knitr::opts_chunk$set(purl = NOT_CRAN)
library(insee)
library(tidyverse)
embed_png <- function(path, dpi = NULL) {
meta <- attr(png::readPNG(path, native = TRUE, info = TRUE), "info")
if (!is.null(dpi)) meta$dpi <- rep(dpi, 2)
knitr::asis_output(paste0(
"<img src='", path, "'",
" width=", round(meta$dim[1] / (meta$dpi[1] / 96)),
" height=", round(meta$dim[2] / (meta$dpi[2] / 96)),
" />"
))}
## ---- echo = FALSE------------------------------------------------------------
embed_png("inflation.png")
## ----message=FALSE, warning=FALSE, include=FALSE------------------------------
library(kableExtra)
library(magrittr)
library(htmltools)
library(prettydoc)
## ----message = FALSE, warning=FALSE, eval = FALSE-----------------------------
# # please download the Github version
# # devtools::install_github("InseeFr/R-Insee-Data")
# library(tidyverse)
# library(lubridate)
# library(insee)
#
#
# df_idbank_list_selected =
# get_idbank_list("IPC-2015") %>% #Inflation dataset
# filter(FREQ == "M") %>% # monthly
# filter(str_detect(COICOP2016, "^[0-9]{2}$")) %>% # coicop aggregation level
# filter(NATURE == "INDICE") %>% # index
# filter(MENAGES_IPC == "ENSEMBLE") %>% # all kinds of household
# filter(REF_AREA == "FE") %>% # all France including overseas departements
# add_insee_title()
#
# list_idbank = df_idbank_list_selected %>% pull(idbank)
#
# data =
# get_insee_idbank(list_idbank, startPeriod = "2015-01") %>%
# add_insee_metadata()
#
# data_plot = data %>%
# mutate(month = month(DATE)) %>%
# arrange(DATE) %>%
# filter(COICOP2016 != "12") %>%
# group_by(COICOP2016_label_en, month) %>%
# mutate(growth = 100 * (OBS_VALUE / dplyr::lag(OBS_VALUE) - 1))
#
# ggplot(data_plot, aes(x = DATE, y = growth)) +
# geom_col() +
# facet_wrap(~COICOP2016_label_en, scales = "free", labeller = label_wrap_gen(22)) +
# ggtitle("French inflation, by product category, year-on-year") +
# labs(subtitle = sprintf("Last updated : %s", data_plot$TIME_PERIOD[nrow(data_plot)]))
#
#
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