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library(lissyrtools)
library(magrittr)

files_h <- read_lissy_files(c("ca14h", "ca15h", "ca16h", "ca17h", "ca18h", "ca19h"),
                            col_select = "dhi")
files_p <- read_lissy_files(c("ca14p", "ca15p", "ca16p", "ca17p", "ca18p", "ca19p"),
                            col_select = c("pi11", "age"))

lissy_datasets <- merge_dataset_levels(files_h, files_p)

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# This is an example of how to read multiple files at once in LISSY

# To read multiple years of one country:

library(tidyverse)


years <- c("08", "10", "14", "16")

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library(tidyverse)

# Exercise 1
years <- c("08", "10", "14", "16")

# append all IT datasets from 2008 to 2016
it_df <- purrr::map_dfr(.x = years,
                        .f = ~read.LIS(glue::glue("it{.x}p"), vars = c("year", "educlev", "educ_c", "enroll", "sex", "age" )))

table(it_df$educlev, it_df$educ_c) 

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# Summer workshop - Data preparation in R --------


# COPY TO LISSY: ----------------------------------------------------------

library(tidyverse)
library(magrittr)
# install.packages("Hmisc")

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library(tidyverse)
library(haven)

#' Download the OECD detailed National Accounts
#'
#' @description
#' Uses the API to the OECD tables to download the National Accounts.
#'
#' Downloads all variables for all years for the selected countries.
#'

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library(tidyverse)

national_accounts_df <-  tibble::tibble(country = c("ITA", "ITA", "ITA", "ITA", "ITA"), 
                                        variable = c("NFD41R", "NFD11P", "NFB3GR", "NFD42R", "NFD45R"), 
                                        sector = c("S14", "S14", "S14", "S14", "S14"), 
                                        year = c("2016", "2016", "2016", "2016", "2016"), 
                                        value = c(27593.2, 84325810, 227852.9, 119509.5, 1034.7))

estimates_from_microdata_df <- tibble::tibble(indicator = c("D11P", "B3GR+D41R+D42R+D45R"), 
                                              value = c(84328052, 894699.3))

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library(rlang)
library(dplyr)

it14ih <- data.frame(hid = 1:6,
                     hi11 = c(3601, 13190, 0,  11479, 0, 4713),
                     hi13 = c(973, 0, 0, 478, 815, 399),
                     hi12 = c(0, 0, 0,  0, 0, 842),
                     hicapital = c(40, 41, 0, 100, 0, 83),
                     hpopwgt = c(567.1, 5308.3, 666.7, 
                                 692.2, 254.2, 632.6)

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#' Download the OECD detailed National Accounts
#'
#' @description
#' Uses the API to the OECD tables to download the National Accounts.
#'
#' Downloads all variables for all years for the selected countries.
#'
#' @details
#' The OECD API takes countries with ISO3. The function uses the METIS 'country'
#'   table to convert ISO2 to ISO3.

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import cppyy
import numpy as np

# 'translation' of the Python function below done by ChatGPT
cppyy.cppdef("""
#include <iostream>
#include <vector>
#include <algorithm>
#include <numeric>

JosepER

v <- c(8,5,1,3,5,6,7,6,3) # income
w <- seq(0.1, 0.9, 0.1) # weights


w <- w[order(v)]
v <- sort(v)


# compute πₖ