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ITLP-4Q19.R
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ITLP-4Q19.R
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### Descarga bases
rm(list=ls())
tiempo <- Sys.time()
ult.anio <- 19
ult.trim <- 1
todas.bases <- TRUE
if (!require(pacman)) install.packages("pacman")
library(pacman)
p_load("data.table", "haven", "foreign",
"tidyverse", "srvyr", "lubridate", "here",
"gdata", "grid", "gtable", "gridExtra", "httr", "jsonlite", "rmarkdown")
destino <- here::here("bases", "ENOE_desc")
dest.dir <- here::here("bases", "ENOE_util")
url2 <- "https://www.inegi.org.mx/contenidos/programas/enoe/15ymas/microdatos/20"
descargas2 <- function(i, j){
download.file(paste0(url2, i,"trim",j,"_csv.zip", sep=""),
paste0(destino, "/enoe_15ymas_20", i, j, "_csv.zip"), mode="wb")
inicio <- paste0(destino, "/enoe_15ymas_20", i, sep="")
unzip(paste0(destino, "/enoe_15ymas_20", i, j, "_csv.zip"), exdir = dest.dir)
}
url3 <- "https://www.inegi.org.mx/contenidos/programas/enoe/15ymas/microdatos/20"
descargas3 <- function(i, j){
download.file(paste0(url3, i,"trim",j,"_csv.zip", sep=""),
paste0(destino, "/enoe_15ymas_20", i, j, "_csv.zip"), mode="wb")
inicio <- paste0(destino, "/enoe_15ymas_20", i, sep="")
unzip(paste0(destino, "/enoe_15ymas_20", i, j, "_csv.zip"), exdir = dest.dir)
}
if(T){
n.periodo <- head(paste(rep(c("I", "II", "III", "IV"), (ult.anio - 05)),
sort(rep(2005:(2000+ult.anio), 4)), sep = " "),
((ult.anio-4)*4)-(4-ult.trim))
tx <- head(paste("t", rep(1:4, (ult.anio - 05)),
str_sub(sort(rep(2005:(2000+ult.anio), 4)), -2), sep = ""),
((ult.anio-4)*4)-(4-ult.trim))
n.itlp <-{ c("periodo",
"Nacional",
"Urbano",
"Rural",
"Aguascalientes",
"Baja California",
"Baja California Sur",
"Campeche",
"Coahuila",
"Colima",
"Chiapas",
"Chihuahua",
"Ciudad de México",
"Durango",
"Guanajuato",
"Guerrero",
"Hidalgo",
"Jalisco",
"Estado de México",
"Michoacán",
"Morelos",
"Nayarit",
"Nuevo León",
"Oaxaca",
"Puebla",
"Querétaro",
"Quintana Roo",
"San Luis Potosí",
"Sinaloa",
"Sonora",
"Tabasco",
"Tamaulipas",
"Tlaxcala",
"Veracruz",
"Yucatán",
"Zacatecas")}
}
if(!todas.bases){
descargas3(str_pad(ult.anio, width = 2, pad = "0"), ult.trim)
} else {
anios2 <- str_pad(5:18,2,pad="0")
perm <- 4 - 2
walk2(head(sort(rep(anios2, times=4)),
n=length(rep(anios2, times=4))-perm),
head(rep(1:4, times=(ult.anio-4)),
n=length(rep(1:4, times=(ult.anio-4)))-perm),
descargas2)
### Dos bases se descargan con mayusculas
anios3 <- str_pad(18:ult.anio,2,pad="0")
perm3 <- 4 - ult.trim
walk2(head(sort(rep(anios3, times=4)),
n=length(rep(anios3, times=4))-perm3)[-c(1,2)],
head(rep(1:4, times=(ult.anio-17)),
n=length(rep(1:4, times=(ult.anio-17)))-perm3)[-c(1,2)],
descargas3)
}
ultim.mes <- paste(case_when(ult.trim==1 ~ "mar", ult.trim==2 ~ "jun" ,
ult.trim==3 ~ "sep", ult.trim==4 ~ "dic"),
paste("20", ult.anio, sep = ""), sep = "")
url <- paste("https://www.coneval.org.mx/Informes/Pobreza/Datos_abiertos/",
"lineas_de_pobreza_por_ingresos/lineas_pobreza_ingresos_ene1992_",
ultim.mes,".csv", sep = "")
download.file(url, destfile = here::here("bases", "lineas.csv"))
lineas <- fread(here::here("bases", "lineas.csv"))
lineas <- dcast(lineas, anio + mes ~ desagregacion, value.var=c("lpei", "lpi"))
lineas <- lineas[, mes := case_when(mes=="Ene" ~ 1 ,mes=="Feb" ~ 2,
mes=="Mar" ~ 3, mes=="Abr" ~ 4,
mes=="May" ~ 5, mes=="Jun" ~ 6,
mes=="Jul" ~ 7, mes=="Ago" ~ 8,
mes=="Sep" ~ 9, mes=="Oct" ~ 10,
mes=="Nov" ~ 11, mes=="Dic" ~ 12)
][anio>=2005
][, trim := case_when(mes==1 |mes==2 | mes==3 ~ 1,
mes==4 |mes==5 | mes==6 ~ 2,
mes==7 |mes==8 | mes==9 ~ 3,
mes==10 |mes==11 | mes==12 ~ 4)
][, c("lpei_r",
"lpei_u") :=
.(round(mean(lpei_Rural), 2),
round(mean(lpei_Urbano), 2)), by=.(anio, trim)
][, .(anio, trim, lpei_r, lpei_u)
][, "periodo" :=
paste("t",trim, str_sub(anio, -2,-1), sep="")]
lineas <-subset(unique(lineas))
df.ca <- lineas[, .(periodo, lpei_r , lpei_u) ]
names(df.ca) <- c("periodo","Rural","Urbano")
df.ca.u <- df.ca$Urbano
df.ca.r <- df.ca$Rural
df.ca <- data.frame(cbind(df.ca.r, df.ca.u))
df.ca$df.ca.r <- df.ca$df.ca.r / df.ca$df.ca.r[21]
df.ca$df.ca.u <- df.ca$df.ca.u / df.ca$df.ca.u[21]
df.ca <- dplyr::filter(df.ca, !is.na(df.ca.r))
df.ca$periodo <- as.numeric(substr(tx,2,4))
url <- "http://www3.inegi.org.mx/sistemas/api/indicadores/v1/Indicador/"
url1 <- "/01/es/false/json/"
auth <- "9e0b148e-428f-0ffa-4508-6cf5f04c5854"
raw <- httr::GET(paste0(url,583766, url1,auth, sep=""))
txt.c <- content(raw, as = "text", encoding = "UTF-8") %>% fromJSON
df.inpc <- data.table(serie=583766, txt.c$Data$Serie$TimePeriod ,
txt.c$Data$Serie$CurrentValue)
colnames(df.inpc) <- c("serie", "periodo", "inpc")
df.inpc <- df.inpc[, c("periodo", "inpc") :=
.(as.character(periodo),
as.numeric(as.character(inpc)))
][, c("anio", "mes") :=
.(str_sub(periodo, 1, 4),
str_sub(periodo, -2, -1))
][anio>=2005
][, trim := case_when(mes=="01" |mes=="02" |
mes=="03" ~ 1, mes=="04" |
mes=="05" | mes=="06" ~ 2,
mes=="07" |mes=="08" |
mes=="09" ~ 3, mes=="10" |
mes=="11" | mes=="12" ~ 4)
][, .(anio, trim, inpc)
][, inpc_trim :=
.(mean(inpc)), by=.(anio, trim)
][, .(anio, trim, inpc_trim)]
df.inpc <-subset(unique(df.inpc))
v_inpc <- head(df.inpc$inpc_trim, length(tx))
df_ind <- fread(here::here("bases", "base_mun_ind.csv"))
df_ind <- df_ind[pobi >= 0.4][, c("ent", "mun") :=
.(str_pad(ent, 2, "left", "0"),
str_pad(mun, 3, "left", "0"))]
mun_ind <- paste(df_ind$ent, df_ind$mun, sep="")
df.inpc <- data.frame(inpc_t = v_inpc, tx)
df.inpc$def <- df.inpc$inpc_t / df.inpc$inpc_t[df.inpc$tx=="t110"]
options(survey.lonely.psu="adjust")
fx.ingreso <- function(x) {
num <- as.numeric(substr(x,2,5))
df <- fread(here::here("bases", "ENOE_util", paste0("coe2", x, ".csv", sep="")))
colnames(df) <- tolower(colnames(df))
df <- df[, c("cd_a", "ent", "con", "v_sel", "n_ren") :=
.(str_pad(cd_a, 2, "left", "0"),
str_pad(ent, 2, "left", "0"),
str_pad(con, 5, "left", "0"),
str_pad(v_sel, 2, "left", "0"),
str_pad(n_ren, 2, "left", "0"))]
df <- df[,foliop := paste0(cd_a, ent, con, v_sel,n_hog, h_mud, n_ren, sep="")
][, .(foliop, p6c, p6b2, p6_9, p6a3)]
df2 <- fread(here::here("bases", "ENOE_util", paste0("sdem", x, ".csv", sep="")))
colnames(df2) <- tolower(colnames(df2))
df2 <- df2[, c("cd_a", "ent", "con", "v_sel", "n_ren") :=
.(str_pad(cd_a, 2, "left", "0"),
str_pad(ent, 2, "left", "0"),
str_pad(con, 5, "left", "0"),
str_pad(v_sel, 2, "left", "0"),
str_pad(n_ren, 2, "left", "0"))]
df2 <- df2[r_def==0 & (c_res==1 | c_res==3)
][,
c("folioh",
"foliop") :=
.(paste0(cd_a, ent, con, v_sel, n_hog, h_mud, sep=""),
paste0(cd_a, ent, con, v_sel, n_hog, h_mud, n_ren, sep=""))][
, .(folioh, foliop, salario, t_loc, fac, clase1,
clase2, ent, ingocup, mun, sex, dur_est, rama,
est_d, upm)]
df <- df[df2, on = .(foliop)
][, c("ocupado","p6b2","p6c") :=
.(ifelse(clase1 == 1 & clase2 == 1, 1, 0),
as.numeric(p6b2),
as.numeric(p6c))
][p6b2==999998 | p6b2==999999, p6b2 := NA
][, ingreso := if_else(ocupado == 0 |
(is.na(p6b2) & (p6_9==9 | p6a3==3)),
0, p6b2)
][is.na(p6b2) & (p6c==1), ingreso := salario * 0.5
][is.na(p6b2) & p6c==2, ingreso := salario * 1
][is.na(p6b2) & p6c==3, ingreso := salario * 1.5
][is.na(p6b2) & p6c==4, ingreso := salario * 2.5
][is.na(p6b2) & p6c==5, ingreso := salario * 4
][is.na(p6b2) & p6c==6, ingreso := salario * 7.5
][is.na(p6b2) & p6c==7, ingreso := salario * 10
][,
c("factor", "tamh", "rururb", "ent", "mv") :=
.(fac,
1,
if_else((as.numeric(t_loc)>=1 &
as.numeric(t_loc)<=3), 0, 1),
as.numeric(ent),
if_else(is.na(ingreso) &
ocupado == 1, 1, 0))
][
, .(folioh, foliop, tamh, ingreso, rururb,
factor, ent, mun, mv, ocupado,
sex, dur_est, rama, est_d, upm)
]
df_ocupados <- df[, .(tamh = sum(tamh),
ingreso = sum(ingreso),
mv = sum(mv),
sex=sex[1],
ocupado = sum(ocupado),
rururb = rururb[1],
factor = factor[1],
ent = ent[1],
mun = mun[1],
horas = dur_est[1],
rama = rama[1],
est_d = est_d[1],
upm = upm[1]), by=.(foliop)
][, .(foliop, tamh, ingreso, mv, sex,ocupado, rururb, factor, ent, mun, horas, rama, est_d, upm)
][, mv := if_else(!is.na(mv) & mv > 0, 1, 0)
][mv != 1
][, mun_i := str_c(str_pad(ent, 2, "left", "0"),str_pad(mun, 3, "left", "0"), sep="")
][,indigena := case_when(mun_i == "23011" ~ NA_real_,
mun_i %in% mun_ind ~ 1,
TRUE ~ 0)
][ocupado==1
][, c("factorp", "pob", "ingpc") :=
.(factor * tamh,
case_when(rururb == 0 & (ingreso / tamh) < lineas$lpei_u[lineas$periodo== x] ~ 1,
rururb == 1 & (ingreso / tamh) < lineas$lpei_r[lineas$periodo== x] ~ 1,
TRUE ~ 0),
ingpc = ingreso / tamh)]
df <- df[, .(tamh = sum(tamh),
ingreso = sum(ingreso),
mv = sum(mv),
ocupado = sum(ocupado),
rururb = rururb[1],
factor = factor[1],
ent = ent[1],
mun = mun[1]), by=.(folioh)
][, .(folioh, tamh, ingreso, mv,
ocupado, rururb, factor, ent, mun)
][, mv := if_else(!is.na(mv) &
mv > 0, 1, 0)
][mv != 1][, c("factorp", "pob", "ingpc", "ingpcdef") :=
.(factor * tamh,
case_when(rururb == 0 & (ingreso / tamh) < lineas$lpei_u[lineas$periodo== x] ~ 1,
rururb == 1 & (ingreso / tamh) < lineas$lpei_r[lineas$periodo== x] ~ 1,
TRUE ~ 0),
ingreso / tamh,
NA_real_)]
num <- as.numeric(substr(x,2,5))
df <- as.data.frame(df)
df$ingpcdef[df$rururb==0] <- df$ingpc[df$rururb==0] / df.ca$df.ca.u[df.ca$periodo==num]
df$ingpcdef[df$rururb==1] <- df$ingpc[df$rururb==1] / df.ca$df.ca.r[df.ca$periodo==num]
df_ocupados <- df_ocupados[, "region" := case_when(ent %in% c(2,8,5,19,26,28) ~ "norte",
ent %in% c(3,1,6,10,14,16,18,24,25,32) ~ "centro norte",
ent %in% c(9,15,11,13,17,21,22,29) ~ "centro",
TRUE ~ "sur")]
#Antes del disenio
sd <- as_survey_design(df, weights = factorp)
df.rururb <- sd %>% group_by(rururb) %>%
summarise(pob_mean = survey_mean(pob, na.rm=TRUE))
df.def_n <- summarise(sd, ingpcdef = survey_mean(ingpcdef, na.rm=TRUE))
df.def_e <- sd %>% group_by(ent) %>%
summarise(ingpcdef_mean = survey_mean(ingpcdef, na.rm=TRUE))
#sd_i <- as_survey_design(df_ocupados, weights = factorp, id=upm, strata = est_d, nest=TRUE)
sd_i <- as_survey_design(df_ocupados, weights = factorp)
df_i_tlp <- sd_i %>% group_by(indigena) %>%
summarise(pob_mean = survey_mean(pob, na.rm=TRUE, vartype = "cv"))
df_i_ingpc <- sd_i %>% group_by(indigena) %>%
summarise(ingpc = survey_mean(ingpc, na.rm=TRUE, vartype = "cv"))
df_s_tlp <- sd_i %>% group_by(sex) %>%
summarise(pob_mean = survey_mean(pob, na.rm=TRUE, vartype = "cv"))
df_s_ingpc <- sd_i %>% group_by(sex) %>%
summarise(ingpc = survey_mean(ingpc, na.rm=TRUE, vartype = "cv"))
#df_sex_hrs <- sd_i %>% group_by(sex, horas) %>%
# summarise(ingpc = survey_mean(ingpc, na.rm=TRUE, vartype = "cv"), pob_mean = survey_mean(pob, na.rm=TRUE, vartype = "cv"))
#df_ind_act <- sd_i %>% group_by(indigena, rama) %>%
# summarise(ingpc = survey_mean(ingpc, na.rm=TRUE, vartype = "cv"), pob_mean = survey_mean(pob, na.rm=TRUE, vartype = "cv"))
#df_sex_reg <- sd_i %>% group_by(sex, region) %>%
# summarise(ingpc = survey_mean(ingpc, na.rm=TRUE, vartype = "cv"), pob_mean = survey_mean(pob, na.rm=TRUE, vartype = "cv"))
#df_ind_reg <- sd_i %>% group_by(indigena, region) %>%
# summarise(ingpc = survey_mean(ingpc, na.rm=TRUE, vartype = "cv"), pob_mean = survey_mean(pob, na.rm=TRUE, vartype = "cv"))
df_r_i <- data.table(x = 1)
df_r_i$TLP_i <- df_i_tlp$pob_mean[df_i_tlp$indigena==T] *100
df_r_i$TLP_ni <- df_i_tlp$pob_mean[df_i_tlp$indigena==F] *100
df_r_i$ingreso_i <- df_i_ingpc$ingpc[df_i_ingpc$indigena==T]
df_r_i$ingreso_ni <- df_i_ingpc$ingpc[df_i_ingpc$indigena==F]
df_r_i$TLP_h <- df_s_tlp$pob_mean[as.numeric(df_s_tlp$sex)==1] *100
df_r_i$TLP_m <- df_s_tlp$pob_mean[as.numeric(df_s_tlp$sex)==2] *100
df_r_i$ingreso_h <- df_s_ingpc$ingpc[as.numeric(df_s_ingpc$sex)==1]
df_r_i$ingreso_m <- df_s_ingpc$ingpc[as.numeric(df_s_ingpc$sex)==2]
#df_sex_hrs$id <- paste("S", df_sex_hrs$sex, "H", df_sex_hrs$horas, sep="")
#sex_hrs <- as.data.frame(cbind(t(df_sex_hrs$ingpc), t(df_sex_hrs$ingpc_cv),
# t(df_sex_hrs$pob_mean), t(df_sex_hrs$pob_mean_cv)))
#colnames(sex_hrs) <- c(paste(df_sex_hrs$id, "_i", sep=""), paste(df_sex_hrs$id, "_i_cv", sep=""),
# paste(df_sex_hrs$id, "_p", sep=""), paste(df_sex_hrs$id, "_p_cv", sep=""))
#df_ind_act$id <- paste("I", as.numeric(df_ind_act$indigena), "A", df_ind_act$rama, sep="")
#ind_act <- as.data.frame(cbind(t(df_ind_act$pob_mean), t(df_ind_act$pob_mean_cv),
# t(df_ind_act$ingpc), t(df_ind_act$ingpc_cv)))
#colnames(ind_act) <- c(paste(df_ind_act$id, "_p", sep=""), paste(df_ind_act$id, "_p_cv", sep=""),
# paste(df_ind_act$id, "_i", sep=""), paste(df_ind_act$id, "_i_cv", sep=""))
#df_sex_reg$id <- paste("S", as.numeric(df_sex_reg$sex), "R",
# str_remove(df_sex_reg$region, " "), sep="")
#sex_reg <- as.data.frame(cbind(t(df_sex_reg$ingpc), t(df_sex_reg$ingpc_cv),
# t(df_sex_reg$pob_mean), t(df_sex_reg$pob_mean_cv)))
#colnames(sex_reg) <- c(paste(df_sex_reg$id, "_i", sep=""), paste(df_sex_reg$id, "_i_cv", sep=""),
# paste(df_sex_reg$id, "_p", sep=""), paste(df_sex_reg$id, "_p_cv", sep=""))
#df_ind_reg$id <- paste("I", as.numeric(df_ind_reg$indigena), "R",
# str_remove(df_ind_reg$region, " "), sep="")
#ind_reg <- as.data.frame(cbind(t(df_ind_reg$ingpc), t(df_ind_reg$ingpc_cv),
# t(df_ind_reg$pob_mean), t(df_ind_reg$pob_mean_cv)))
#colnames(ind_reg) <- c(paste(df_ind_reg$id, "_i", sep=""), paste(df_ind_reg$id, "_i_cv", sep=""),
# paste(df_ind_reg$id, "_p", sep=""), paste(df_ind_reg$id, "_p_cv", sep=""))
df_r <- data.table(x = 1)
df_r$TLP <- summarise(sd, pob_mean = survey_mean(pob))$pob_mean[1] * 100
df_r$defN <- df.def_n$ingpcdef[1]
df_r$TLPu <- df.rururb$pob_mean[1] * 100
df_r$TLPr <- df.rururb$pob_mean[2] * 100
df.ent <- group_by(sd, ent) %>%
summarise(pob_mean = survey_mean(pob))
df.ingpc <- group_by(sd, ent) %>%
summarise(ingpc_mean = survey_mean(ingpc))
for(y in 1:32) {
nombre <- paste0("TLP", y, sep ="")
df_r[[nombre]] <- df.ent$pob_mean[y] * 100
nombre2 <- paste0("ingpcx", y, sep ="")
df_r[[nombre2]] <- df.ingpc$ingpc_mean[y]
nombre4 <- paste0("ingpcdef", y, sep ="")
df_r[[nombre4]] <- df.def_e$ingpcdef_mean[y]
}
df_r <- dplyr::select(df_r, starts_with("TLP"), starts_with("ingpcx"), starts_with("ingpcdef"))
df_r$periodo <- x
df_r$ingpcx0 <- summarise(sd, ingpc_mean = survey_mean(ingpc))$ingpc_mean[1]
df_r$ingpcdef0 <- summarise(sd, ingpcdef_mean = survey_mean(ingpcdef))$ingpcdef_mean[1]
df_r <- dplyr::select(df_r, periodo, starts_with("TLP"), starts_with("ingpcx"), starts_with("ingpcdef"))
df_r$ingpc <- df_r$ingpcx0
df_r$ingpcdef <- df_r$ingpcdef0
#df_r <- bind_cols(df_r, df_r_i, sex_hrs, ind_act, sex_reg, ind_reg)
df_r <- bind_cols(df_r, df_r_i)
print(paste("Fin del calculo para el periodo ", x, sep =""))
return(df_r)
}
if(todas.bases){
f <- map(tx, fx.ingreso)
df <- f[[1]]
for (i in 2:length(f)) {
df <- bind_rows(df, f[[i]])
}
fwrite(df, here::here("temp", "temporal.csv"))
} else {
df <- fread(here::here("temp", "temporal.csv"))
df <- filter(df, periodo != tx[length(tx)])
f <- fx.ingreso(tx[length(tx)])
df <- bind_rows(df, f)
fwrite(df, here::here("temp", "temporal.csv"))
}
### df <- fread(here::here("temp", "temporal.csv"))
df$def <- df.inpc$def[1:length(df$ingreso_i)]
df <- data.table(df)
df <- df[,c("ingreso_i", "ingreso_ni",
"ingreso_h", "ingreso_m") := .(ingreso_i/def, ingreso_ni/def,
ingreso_h/def, ingreso_m/def)]
df <- as.data.frame(df)
df_indigenas <- dplyr::select(df, periodo, ends_with("_i"), ends_with("_ni"),
ends_with("_h"), ends_with("_m"),
ends_with("_p"), ends_with("_cv"))
fwrite(df_indigenas, here::here("temp", "cuadro_indigenas.csv"))
df4 <- dplyr::select(df, periodo, starts_with("ingpcdef")) %>%
mutate(periodo = substr(periodo, 2, 5))
df2 <- dplyr::select(df, periodo, starts_with("ingpcx")) %>%
mutate(periodo = substr(periodo, 2, 5))
df <- dplyr::select(df, periodo, starts_with("TLP"), -ends_with("_i"),
-ends_with("_ni"), -ends_with("_m"), -ends_with("_h"))
df7 <- df
df <- filter(df, !is.na(TLP)) %>%
mutate(periodo = substr(periodo, 2, 5))
df$periodo <- as.numeric(df$periodo)
df2$periodo <- df$periodo
df$base <- df$TLP[df$periodo==110]
df$ITLP <- NA
df$ITLP <- df$TLP / df$base
df$baseu <- df$TLPu[df$periodo==110]
df$ITLPu <- NA
df$ITLPu <- df$TLPu / df$baseu
df$baser <- df$TLPr[df$periodo==110]
df$ITLPr <- NA
df$ITLPr <- df$TLPr / df$baser
for(y in 1:32) {
nombre <- paste0("base", y, sep ="")
nombre2 <- paste0("TLP", y, sep ="")
df[[nombre]] <- NA
df[[nombre]] <- mean(df[[nombre2]][df$periodo==110])
nombre3 <- paste0("ITLP", y, sep ="")
df[[nombre3]] <- NA
df[[nombre3]] <- df[[nombre2]] / df[[nombre]]
}
df <- dplyr::select(df, periodo, starts_with("ITLP"))
rownames(df) <- n.periodo
rownames(df2) <- n.periodo
names(df) <- n.itlp
n.ingpc <- n.itlp[-c(3:4)]
names(df2) <- c(n.ingpc[-2], "Nacional")
rownames(df) <- n.periodo
rownames(df2) <- n.periodo
df3 <- df2
df3$inpc <- head(v_inpc, length(df3$periodo))
df3$base <- df3$inpc / df3$inpc[df3$periodo==110]
df3[,2:34] <- df3[,2:34] / df3$base
names(df4) <- c("periodo", n.ingpc[-c(1,2)], "Nacional", "otro" )
df4 <- df4[,-35]
rownames(df4) <- n.periodo
df <- data.frame(sapply(df, FUN=round, digits=4))
df2 <- data.frame(sapply(df2, FUN=round, digits=2))
df3 <- data.frame(sapply(df3, FUN=round, digits=2))
df4 <- data.frame(periodo = df4[,1],sapply(df4[,-1], FUN=round, digits=2))
names(df) <- c("periodo", "Nacional", "Urbano", "Rural", n.ingpc[-c(1,2)])
df7 <- dplyr::select(df7, -ends_with("_h"), -ends_with("_ni"), -ends_with("_i"),
-ends_with("_m"))
names(df7) <- c("periodo", "Nacional", "Urbano", "Rural", n.ingpc[-c(1,2)])
fwrite(df, here::here("temp", "ITLP IS.csv"))
fwrite(df2, here::here("temp", "IL-Corriente.csv"))
fwrite(df3, here::here("temp", "IL-INPC.csv"))
fwrite(df4, here::here("temp", "IL-CA.csv"))
fwrite(df7, here::here("temp", "TLP.csv"))
ult.trim.l <- if_else(ult.trim == 1, "primer",
if_else(ult.trim==2, "segundo",
if_else(ult.trim==3, "tercer", "cuarto")))
add_sublabs <- function(plot, sublabs){
gg <- ggplotGrob(plot)
axis_num <- which(gg$layout[,"name"] == "axis-b")
xbreaks <- gg[["grobs"]][[axis_num]][["children"]][[2]][["grobs"]][[2]][["children"]][[1]]$x
if(length(xbreaks) != length(sublabs)) stop("Sub-labels must be the same length as the x-axis breaks")
to_breaks <- c(as.numeric(xbreaks),1)[which(!duplicated(sublabs, fromLast = TRUE))+1]
sublabs_x <- diff(c(0,to_breaks))
sublabs_labels <- sublabs[!duplicated(sublabs, fromLast = TRUE)]
tg <- tableGrob(matrix(sublabs_labels, nrow = 1))
tg$widths = unit(sublabs_x, attr(xbreaks,"unit"))
pos <- gg$layout[axis_num,c("t","l")]
gg2 <- gtable_add_rows(gg, heights = sum(tg$heights)+unit(4,"mm"), pos = pos$t)
gg3 <- gtable_add_grob(gg2, tg, t = pos$t+1, l = pos$l)
return(gg3)
}
df.ca$inc_r <- (df.ca$df.ca.r - lag(df.ca$df.ca.r))/lag(df.ca$df.ca.r)
df.ca$inc_u <- (df.ca$df.ca.u - lag(df.ca$df.ca.u))/lag(df.ca$df.ca.u)
df.ca$per <- paste("t",df3$periodo, sep="")
gdata::keep(ult.anio, ult.trim.l, ult.trim, n.periodo, n.ingpc, df, df2, df3,
df4, df7, df.ca, add_sublabs, df_indigenas, tiempo, sure=T)
save.image(file=here::here("datos_final.RData"))
library("rmarkdown")
#rmarkdown::render(here::here("presentaciones", "Ing-laboral.Rmd"), encoding="UTF-8",
# output_options =
# list(pandoc_args =
# c(paste("--metadata=subtitle:\"",
# paste(stringr::str_to_title(ult.trim.l)," trimestre de 20", ult.anio, sep=""),
# "\"", sep=""))))
rmarkdown::render(here::here("presentaciones", "Comunicado de prensa.Rmd"), encoding="UTF-8")
Sys.time() - tiempo