Pregunta 1. Usando los datos de la pen world table, de la Universidad de Groningen. Resuelva los siguientes requerimientos (es importante mostrar todos sus resultados en formato tabular):

carga de las respectivas librerias

library(pwt9)
data("pwt9.0")
library(dplyr)
library(readxl)
library(stringr)
library(kableExtra)

carga de las bases de datos

load("C:/Users/latit/OneDrive/Escritorio/MAE 2020 GT 2/Tarea_Métodos/Comercio/data_comercio_exterior.RData")
source(file = "C:/Users/latit/Downloads/funciones_comercio_exterior.R")

1- Construya una función que le permita elegir el país y filtrar para un período(inicio, final), muestre su uso filtrando los datos para guatemala, en el periodo de 1990-2014.

# Función a utilizar:
funcion_consulta_pais<-function(iso_pais,anio_inicio,anio_final){
enquo(iso_pais)->iso_pais
pwt9.0 %>% filter(isocode==!!iso_pais,
                  year>=anio_inicio,
                  year<=anio_final)->df
return(df) 
}

funcion_consulta_pais(iso_pais = "GTM",1990,2014) %>%
  kable(caption = "Prueba de función consulta paises, guatemala 1990-2014",
        digits = 1,align = "l") %>%
  kable_styling(bootstrap_options = "striped",
                full_width = TRUE)
Prueba de función consulta paises, guatemala 1990-2014
country isocode year currency rgdpe rgdpo pop emp avh hc ccon cda cgdpe cgdpo ck ctfp cwtfp rgdpna rconna rdana rkna rtfpna rwtfpna labsh delta xr pl_con pl_da pl_gdpo i_cig i_xm i_xr i_outlier cor_exp statcap csh_c csh_i csh_g csh_x csh_m csh_r pl_c pl_i pl_g pl_x pl_m pl_k
GTM-1990 Guatemala GTM 1990 Quetzal 33234.6 34222.7 9.2 2.5 NA 1.5 32241.0 35134.4 33063.2 34293.3 45778.6 0.9 0.9 46215.4 41905.3 47471.4 126784.4 1.0 0.9 0.5 0.1 4.5 0.2 0.2 0.2 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.1 0.0 0.2 0.4 0.2 0.5 0.5 0.3
GTM-1991 Guatemala GTM 1991 Quetzal 35438.7 36470.8 9.4 2.6 NA 1.5 33555.4 37250.1 35158.6 36600.2 47208.3 0.9 0.9 47906.0 43432.1 50421.9 129355.2 1.0 0.9 0.5 0.1 5.0 0.2 0.2 0.2 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.1 0.0 0.2 0.4 0.2 0.5 0.5 0.3
GTM-1992 Guatemala GTM 1992 Quetzal 36326.2 37987.7 9.6 2.7 NA 1.5 35497.8 40458.9 35981.5 37812.5 49587.2 0.9 0.9 50223.9 45647.4 54848.9 133586.8 1.0 1.0 0.5 0.1 5.2 0.2 0.3 0.2 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.1 0.0 0.2 0.4 0.2 0.5 0.5 0.4
GTM-1993 Guatemala GTM 1993 Quetzal 38583.3 40375.7 9.9 2.8 NA 1.5 37369.7 42216.4 38180.7 40147.5 53500.3 0.9 0.9 52196.8 47680.4 56266.1 140097.1 1.0 1.0 0.5 0.1 5.6 0.2 0.3 0.3 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.1 0.0 0.3 0.4 0.2 0.5 0.5 0.3
GTM-1994 Guatemala GTM 1994 Quetzal 41145.2 42164.7 10.1 3.0 NA 1.6 39555.8 44458.9 40625.7 42118.2 57302.1 0.8 0.9 54301.9 49909.4 58601.2 144104.8 1.0 0.9 0.5 0.1 5.8 0.3 0.3 0.3 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.1 0.0 0.3 0.4 0.2 0.5 0.5 0.4
GTM-1995 Guatemala GTM 1995 Quetzal 43889.6 45114.5 10.4 3.0 NA 1.6 42208.8 47068.0 43522.3 45290.4 62316.2 0.9 0.9 56981.1 52361.3 60906.5 150601.8 1.0 0.9 0.5 0.1 5.8 0.3 0.3 0.3 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.1 0.0 0.3 0.4 0.2 0.5 0.5 0.3
GTM-1996 Guatemala GTM 1996 Quetzal 45516.4 46279.2 10.6 3.1 NA 1.6 43993.9 48135.5 45269.6 46609.7 66182.5 0.8 0.9 58669.1 53711.6 60829.8 154488.9 1.0 0.9 0.5 0.1 6.0 0.3 0.3 0.3 interpolated benchmark market no NA NA 0.9 0.1 0.1 0.1 -0.1 0.0 0.3 0.5 0.2 0.6 0.5 0.4
GTM-1997 Guatemala GTM 1997 Quetzal 48241.9 48901.3 10.9 3.2 NA 1.6 46064.6 51158.2 47688.0 49022.4 72300.2 0.8 0.8 61235.1 55940.7 64595.6 163422.1 1.0 0.9 0.5 0.1 6.1 0.3 0.3 0.3 interpolated benchmark market no NA NA 0.9 0.1 0.1 0.1 -0.2 0.0 0.3 0.5 0.3 0.5 0.5 0.3
GTM-1998 Guatemala GTM 1998 Quetzal 51417.2 51953.6 11.1 3.3 NA 1.6 48666.8 55740.6 50502.8 52091.2 79881.7 0.8 0.8 64293.3 58718.5 70643.4 172925.6 0.9 1.0 0.5 0.1 6.4 0.3 0.3 0.3 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.2 0.0 0.3 0.5 0.3 0.5 0.5 0.4
GTM-1999 Guatemala GTM 1999 Quetzal 53551.0 54882.2 11.4 3.4 NA 1.6 51127.0 58298.1 52587.8 54994.9 89127.0 0.8 0.8 66766.6 61015.4 72668.6 185427.2 0.9 0.9 0.5 0.1 7.4 0.3 0.3 0.3 interpolated benchmark market no NA 47.8 0.8 0.1 0.1 0.1 -0.2 0.0 0.3 0.4 0.3 0.5 0.5 0.3
GTM-2000 Guatemala GTM 2000 Quetzal 56102.1 57968.2 11.7 3.6 NA 1.7 53538.4 61430.3 55067.0 57636.4 96989.8 0.7 0.7 69175.8 63408.1 75548.2 192628.2 0.9 0.9 0.5 0.1 7.8 0.3 0.3 0.3 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.2 0.0 0.3 0.4 0.3 0.5 0.5 0.3
GTM-2001 Guatemala GTM 2001 Quetzal 58489.1 61418.7 12.0 3.7 NA 1.6 56344.4 65172.1 57608.4 61010.9 103967.5 0.7 0.8 70788.7 65909.3 78846.1 198709.3 0.9 0.9 0.5 0.1 7.9 0.3 0.3 0.3 interpolated benchmark market no NA NA 0.8 0.1 0.1 0.1 -0.2 0.0 0.3 0.4 0.3 0.5 0.5 0.4
GTM-2002 Guatemala GTM 2002 Quetzal 61456.7 63811.9 12.3 3.9 NA 1.6 58545.0 68691.8 60556.7 63553.1 112948.9 0.7 0.8 73525.9 67883.9 81973.3 205983.8 0.9 0.9 0.5 0.1 7.8 0.3 0.3 0.3 interpolated benchmark market no NA NA 0.8 0.2 0.1 0.1 -0.2 0.1 0.3 0.4 0.4 0.5 0.5 0.4
GTM-2003 Guatemala GTM 2003 Quetzal 63583.8 66275.4 12.6 4.0 NA 1.6 61206.7 71559.9 62545.6 66160.8 122840.9 0.7 0.7 75386.6 70127.8 84049.5 212495.2 0.9 0.9 0.5 0.1 7.9 0.3 0.4 0.3 interpolated benchmark market no NA NA 0.8 0.2 0.1 0.1 -0.2 0.0 0.3 0.4 0.4 0.5 0.5 0.4
GTM-2004 Guatemala GTM 2004 Quetzal 66131.6 69108.5 12.9 4.0 NA 1.6 63706.6 74806.2 64977.1 69019.6 136110.9 0.7 0.7 77762.9 72080.1 86489.9 218599.4 0.9 1.0 0.4 0.1 7.9 0.4 0.4 0.3 interpolated benchmark market no NA 81.1 0.8 0.2 0.1 0.1 -0.2 0.1 0.4 0.5 0.4 0.5 0.5 0.4
GTM-2005 Guatemala GTM 2005 Quetzal 68825.3 72399.2 13.2 4.2 NA 1.6 68320.2 79756.3 68791.5 72216.7 153376.9 0.7 0.7 80298.1 74991.0 89195.8 225095.9 0.9 1.0 0.4 0.1 7.6 0.4 0.4 0.4 interpolated benchmark market no NA 78.9 0.9 0.2 0.1 0.1 -0.3 0.0 0.4 0.5 0.4 0.6 0.5 0.4
GTM-2006 Guatemala GTM 2006 Quetzal 73486.2 76669.0 13.5 4.5 NA 1.6 72078.9 85189.2 72839.5 76602.5 173933.1 0.7 0.7 84617.9 78573.3 94445.4 234027.8 0.9 1.0 0.4 0.0 7.6 0.4 0.4 0.4 interpolated benchmark market no NA 80.0 0.9 0.2 0.1 0.1 -0.2 0.0 0.4 0.5 0.4 0.6 0.6 0.4
GTM-2007 Guatemala GTM 2007 Quetzal 79439.3 82025.2 13.8 4.5 NA 1.7 77205.1 91696.3 78528.7 82105.0 192681.0 0.7 0.7 89952.3 83017.8 100097.3 243391.2 1.0 1.0 0.4 0.0 7.7 0.4 0.4 0.4 interpolated benchmark market no NA 78.9 0.9 0.2 0.1 0.1 -0.3 0.0 0.4 0.5 0.4 0.6 0.6 0.4
GTM-2008 Guatemala GTM 2008 Quetzal 83265.5 85980.3 14.1 4.5 NA 1.7 82892.9 95164.7 82976.3 85649.1 209983.8 0.7 0.7 92903.7 87139.7 100861.8 251030.0 1.0 1.0 0.4 0.0 7.6 0.5 0.5 0.5 interpolated benchmark market no NA 82.2 0.9 0.1 0.1 0.1 -0.3 0.0 0.5 0.5 0.5 0.7 0.6 0.4
GTM-2009 Guatemala GTM 2009 Quetzal 87864.5 88414.6 14.4 4.5 NA 1.7 84656.9 95068.2 87094.7 88634.6 223994.4 0.7 0.7 93392.6 88072.6 99219.4 255899.8 1.0 0.9 0.4 0.0 8.2 0.4 0.4 0.4 interpolated benchmark market no NA 85.6 0.9 0.1 0.1 0.1 -0.2 0.0 0.4 0.5 0.4 0.7 0.6 0.4
GTM-2010 Guatemala GTM 2010 Quetzal 92085.6 93170.7 14.7 4.3 NA 1.8 89748.7 101272.5 91646.2 93270.4 241053.6 0.7 0.7 96072.4 91514.5 103506.6 260478.3 1.0 1.0 0.4 0.0 8.1 0.4 0.5 0.4 interpolated benchmark market no NA 85.6 0.9 0.1 0.1 0.1 -0.2 0.0 0.4 0.5 0.4 0.7 0.6 0.4
GTM-2011 Guatemala GTM 2011 Quetzal 98496.6 100070.9 15.0 4.5 NA 1.8 94919.2 109068.4 98496.6 100070.9 266095.2 0.7 0.7 100070.9 94919.2 109068.4 266095.2 1.0 1.0 0.4 0.0 7.8 0.5 0.5 0.5 benchmark benchmark market no 0.6 83.3 0.8 0.1 0.1 0.1 -0.3 0.0 0.5 0.5 0.5 0.7 0.6 0.4
GTM-2012 Guatemala GTM 2012 Quetzal 101200.2 102466.4 15.4 5.1 NA 1.8 98274.9 112493.7 101122.4 101964.9 272282.8 0.7 0.7 103043.0 98167.0 112555.0 272057.2 1.0 1.0 0.4 0.0 7.8 0.5 0.5 0.5 extrapolated benchmark market no NA 80.0 0.9 0.1 0.1 0.1 -0.3 0.0 0.5 0.5 0.5 0.7 0.6 0.4
GTM-2013 Guatemala GTM 2013 Quetzal 104637.7 105246.7 15.7 4.9 NA 1.8 102153.3 115864.6 104280.2 104663.1 281013.8 0.7 0.7 106852.9 101996.6 116153.3 277956.6 1.0 1.0 0.4 0.0 7.9 0.5 0.5 0.5 extrapolated benchmark market no NA 76.7 0.9 0.1 0.1 0.1 -0.3 0.0 0.5 0.6 0.5 0.7 0.6 0.4
GTM-2014 Guatemala GTM 2014 Quetzal 109715.6 110703.2 16.0 5.0 NA 1.8 106532.5 120539.6 109468.7 110100.0 292397.5 0.7 0.7 111393.9 106132.7 120700.0 284343.5 1.0 1.0 0.4 0.0 7.7 0.5 0.5 0.5 extrapolated benchmark market no NA 68.9 0.9 0.1 0.1 0.1 -0.3 0.0 0.5 0.6 0.5 0.7 0.6 0.4

2- construya una función que le permita elegir todas las variables de la categoría “Labor detail”,muestre su uso para los datos de Argentina

#Función a utilizar:
Funcion_variables_Labor_detail <- function(country,anio_inicio,anio_final) {
  pwt9.0 %>% filter(country==!!country,year>=anio_inicio,year<=anio_final) %>%
    select(country,year,emp, avh, hc, labsh)-> country_periodo_1
  country_periodo_1
}
# Probando la fución con el país de Argentina
Funcion_variables_Labor_detail(country = "Argentina",anio_inicio = 1990,anio_final = 2014) %>%
 kable(caption = "Prueba de función consulta Trade detail para: Argentina 1990-2014",
 digits = 1,align = "l") %>%
 kable_styling(bootstrap_options = "striped",
 full_width = TRUE)
Prueba de función consulta Trade detail para: Argentina 1990-2014
country year emp avh hc labsh
ARG-1990 Argentina 1990 11.6 1850.0 2.5 0.5
ARG-1991 Argentina 1991 12.0 1838.0 2.6 0.5
ARG-1992 Argentina 1992 12.1 1826.0 2.6 0.5
ARG-1993 Argentina 1993 12.1 1850.3 2.6 0.5
ARG-1994 Argentina 1994 12.1 1875.0 2.6 0.5
ARG-1995 Argentina 1995 11.5 1897.2 2.6 0.5
ARG-1996 Argentina 1996 11.8 1846.1 2.6 0.4
ARG-1997 Argentina 1997 12.4 1917.3 2.6 0.4
ARG-1998 Argentina 1998 12.9 1903.0 2.6 0.4
ARG-1999 Argentina 1999 13.0 1893.2 2.6 0.5
ARG-2000 Argentina 2000 13.1 1861.0 2.7 0.5
ARG-2001 Argentina 2001 13.0 1803.4 2.7 0.5
ARG-2002 Argentina 2002 13.0 1610.6 2.7 0.4
ARG-2003 Argentina 2003 13.7 1719.4 2.7 0.4
ARG-2004 Argentina 2004 14.7 1739.7 2.8 0.4
ARG-2005 Argentina 2005 15.3 1755.3 2.8 0.4
ARG-2006 Argentina 2006 15.9 1809.4 2.8 0.4
ARG-2007 Argentina 2007 16.4 1816.9 2.8 0.4
ARG-2008 Argentina 2008 16.8 1835.9 2.8 0.4
ARG-2009 Argentina 2009 17.0 1736.9 2.8 0.4
ARG-2010 Argentina 2010 17.5 1728.7 2.8 0.4
ARG-2011 Argentina 2011 17.9 1762.3 2.9 0.4
ARG-2012 Argentina 2012 18.1 1789.0 2.9 0.4
ARG-2013 Argentina 2013 18.3 1776.7 2.9 0.4
ARG-2014 Argentina 2014 18.1 1776.7 2.9 0.4

3- use las funciones creadas en 1 y en 2, para generar 2 dataframes, que muestren los datos de “EE.UU” Y “Canada” para el período 2000-2014

usando la función 1 creada en el literla número 1 para EstadosUnidos y Canada

# Probando la función 1 en USA y CANADA:
funcion_consulta_pais(iso_pais = c("USA","CAN"),anio_inicio =2000,anio_final=2014) %>%
  kable(caption = "Prueba de función consulta paises, Estados Unidos y Canada 2000-2014",
        digits = 1,align = "l") %>%
  kable_styling(bootstrap_options = "striped",
                full_width = TRUE)
Prueba de función consulta paises, Estados Unidos y Canada 2000-2014
country isocode year currency rgdpe rgdpo pop emp avh hc ccon cda cgdpe cgdpo ck ctfp cwtfp rgdpna rconna rdana rkna rtfpna rwtfpna labsh delta xr pl_con pl_da pl_gdpo i_cig i_xm i_xr i_outlier cor_exp statcap csh_c csh_i csh_g csh_x csh_m csh_r pl_c pl_i pl_g pl_x pl_m pl_k
CAN-2001 Canada CAN 2001 Canadian Dollar 1166188 1119308 31.0 15.1 1768.0 3.5 814203.9 1079932 1145022 1144414 3268334 0.9 0.8 1190649 782785.5 1041029 3905941 1.0 0.9 0.6 0.0 1.5 0.7 0.6 0.6 interpolated benchmark market no NA NA 0.6 0.2 0.2 0.4 -0.4 0 0.6 0.5 0.8 0.5 0.5 0.6
CAN-2003 Canada CAN 2003 Canadian Dollar 1211094 1184269 31.6 15.8 1732.1 3.5 858441.9 1148489 1194611 1200543 3349291 0.9 0.8 1247575 832796.8 1119539 4151862 1.0 0.9 0.6 0.0 1.4 0.8 0.7 0.7 interpolated benchmark market no NA NA 0.6 0.2 0.2 0.4 -0.3 0 0.7 0.6 1.0 0.6 0.6 0.8
CAN-2005 Canada CAN 2005 Canadian Dollar 1311424 1323181 32.3 16.4 1739.2 3.6 918976.9 1263380 1315081 1326233 3865556 0.9 0.8 1327435 882079.1 1221829 4462552 1.0 1.0 0.6 0.0 1.2 0.9 0.9 0.9 benchmark benchmark market no 0.9 NA 0.5 0.3 0.1 0.4 -0.4 0 0.9 0.8 1.1 0.6 0.6 0.9
CAN-2007 Canada CAN 2007 Canadian Dollar 1376870 1384391 33.0 17.3 1724.7 3.6 969776.7 1342214 1370408 1395106 4445640 0.9 0.8 1389595 950916.3 1319552 4812567 1.0 1.0 0.6 0.0 1.1 1.1 1.1 1.0 interpolated benchmark market no NA NA 0.5 0.3 0.2 0.4 -0.4 0 1.1 0.9 1.3 0.7 0.7 1.1
CAN-2009 Canada CAN 2009 Canadian Dollar 1310934 1304883 33.7 17.4 1678.5 3.6 1000717.9 1325223 1306457 1323073 4794360 0.8 0.8 1367808 994270.1 1323141 5106391 1.0 1.0 0.6 0.0 1.1 1.1 1.0 1.0 interpolated benchmark market no NA NA 0.6 0.2 0.2 0.3 -0.3 0 1.0 0.9 1.3 0.7 0.7 1.0
CAN-2011 Canada CAN 2011 Canadian Dollar 1423920 1455816 34.5 18.1 1683.6 3.7 1045868.8 1440603 1423920 1455816 5427466 0.8 0.8 1455816 1045868.8 1440603 5427466 1.0 1.0 0.6 0.0 1.0 1.3 1.3 1.2 benchmark benchmark market no 0.8 NA 0.5 0.3 0.2 0.4 -0.4 0 1.3 1.1 1.5 0.7 0.7 1.2
CAN-2013 Canada CAN 2013 Canadian Dollar 1478439 1493624 35.2 18.7 1682.7 3.7 1086339.8 1488701 1465085 1472069 5828469 0.8 0.8 1513537 1084256.5 1500049 5779532 1.0 1.0 0.6 0.0 1.0 1.3 1.3 1.2 extrapolated benchmark market no NA NA 0.6 0.3 0.2 0.4 -0.4 0 1.2 1.1 1.5 0.7 0.7 1.1
USA-2000 United States of America USA 2000 US Dollar 13222419 13031820 282.9 139.3 1848.1 3.6 9977582.0 13511612 13035321 12983206 35997032 1.0 1.0 12975535 10500206.0 13647352 38439588 0.9 0.9 0.6 0.1 1.0 0.8 0.8 0.8 interpolated benchmark market no NA NA 0.7 0.3 0.1 0.1 -0.2 0 0.8 0.7 1.2 0.6 0.6 0.8
USA-2002 United States of America USA 2002 US Dollar 13591523 13309916 288.5 139.1 1805.5 3.6 10524779.0 14027745 13503168 13339370 38467564 1.0 1.0 13336194 11088529.0 14123900 40679832 0.9 1.0 0.6 0.1 1.0 0.9 0.8 0.8 benchmark benchmark market no NA NA 0.7 0.3 0.1 0.1 -0.2 0 0.8 0.7 1.2 0.6 0.6 0.8
USA-2004 United States of America USA 2004 US Dollar 14499944 14204685 293.5 141.6 1783.4 3.6 11251801.0 15090846 14366189 14232334 42071616 1.0 1.0 14229557 11796878.0 15181932 43024076 1.0 1.0 0.6 0.0 1.0 0.9 0.9 0.9 interpolated benchmark market no NA NA 0.7 0.3 0.1 0.1 -0.2 0 0.8 0.7 1.3 0.6 0.7 0.9
USA-2006 United States of America USA 2006 US Dollar 15353601 15083465 298.9 146.6 1778.5 3.6 12126527.0 16170304 15318001 15099868 47891040 1.0 1.0 15097712 12476968.0 16121374 45671956 1.0 1.0 0.6 0.0 1.0 0.9 0.9 0.9 interpolated benchmark market no NA NA 0.7 0.3 0.1 0.1 -0.2 0 0.9 0.8 1.3 0.7 0.7 0.9
USA-2008 United States of America USA 2008 US Dollar 15357469 15305872 304.5 147.5 1761.3 3.7 12569281.0 16125585 15370500 15321926 50006724 1.0 1.0 15321422 12759836.0 16086510 47779436 1.0 1.0 0.6 0.0 1.0 1.0 1.0 1.0 interpolated benchmark market no NA NA 0.7 0.2 0.1 0.1 -0.2 0 0.9 0.9 1.3 0.8 0.8 1.0
USA-2010 United States of America USA 2010 US Dollar 15368666 15250698 309.9 141.3 1738.0 3.7 12764841.0 15842214 15317448 15273702 48876336 1.0 1.0 15273331 12883714.0 15924426 48728140 1.0 1.0 0.6 0.0 1.0 1.0 1.0 1.0 interpolated benchmark market no NA NA 0.7 0.2 0.1 0.1 -0.2 0 0.9 0.9 1.3 0.7 0.8 1.0
USA-2012 United States of America USA 2012 US Dollar 15976742 15899255 314.8 144.9 1753.7 3.7 13206454.0 16505245 15946878 15863845 50020716 1.0 1.0 15863049 13182059.0 16509182 49960600 1.0 1.0 0.6 0.0 1.0 1.0 1.0 1.0 extrapolated benchmark market no NA NA 0.7 0.2 0.1 0.1 -0.2 0 1.0 0.9 1.3 0.8 0.8 1.0
USA-2014 United States of America USA 2014 US Dollar 16704698 16598099 319.4 148.5 1764.6 3.7 13685949.0 17113208 16605887 16490883 52849892 1.0 1.0 16490192 13585164.0 17137356 51190644 1.0 1.0 0.6 0.0 1.0 1.1 1.0 1.1 extrapolated benchmark market no NA NA 0.7 0.2 0.1 0.1 -0.2 0 1.0 1.0 1.4 0.8 0.8 1.1

usando la funcion 2 creada en el literal número 1 para Estados Unidos y Canada

# Probando la función 2 en Estados Unidos y Canada:
Funcion_variables_Labor_detail(country = c("United States of America","Canada"),anio_inicio = 2000,anio_final = 2014)->dataframe_2_2
dataframe_2_2%>%
 kable(caption = "Prueba de función consulta paises para: EE.UU y Canada 2000-2014",
 digits = 1,align = "l") %>%
 kable_styling(bootstrap_options = "striped",
 full_width = TRUE)
Prueba de función consulta paises para: EE.UU y Canada 2000-2014
country year emp avh hc labsh
CAN-2001 Canada 2001 15.1 1768.0 3.5 0.6
CAN-2003 Canada 2003 15.8 1732.1 3.5 0.6
CAN-2005 Canada 2005 16.4 1739.2 3.6 0.6
CAN-2007 Canada 2007 17.3 1724.7 3.6 0.6
CAN-2009 Canada 2009 17.4 1678.5 3.6 0.6
CAN-2011 Canada 2011 18.1 1683.6 3.7 0.6
CAN-2013 Canada 2013 18.7 1682.7 3.7 0.6
USA-2000 United States of America 2000 139.3 1848.1 3.6 0.6
USA-2002 United States of America 2002 139.1 1805.5 3.6 0.6
USA-2004 United States of America 2004 141.6 1783.4 3.6 0.6
USA-2006 United States of America 2006 146.6 1778.5 3.6 0.6
USA-2008 United States of America 2008 147.5 1761.3 3.7 0.6
USA-2010 United States of America 2010 141.3 1738.0 3.7 0.6
USA-2012 United States of America 2012 144.9 1753.7 3.7 0.6
USA-2014 United States of America 2014 148.5 1764.6 3.7 0.6

Pregunta 2. Usando los datos de Comercio Exterior de El Salvador, disponibles en la base de datos preparada en clases, responda las siguientes preguntas:

Importante: muestre sus resultados en formato tabular, y asignando los encabezados y pies de pagina apropiados en cada caso

1-calcule las exportaciones totales de El Salvador hacia la región de África Sub-Sahariana, para el período 2019-2020 son (en millones de US$)

data_comercio_exterior %>%
  select("pais", "sac","anio","mes","valor_fob","sub_region") %>%
  filter(sub_region=="Africa Sub-Sahariana",anio %in% 2019:2020,valor_fob>0) %>%
  group_by(anio) %>%
  summarise(`Total Exportaciones El Salvador MM US$`=sum(valor_fob)/1e6) %>% 
  head() %>% kable(caption = "Exportaciones totales de El Salvador en Millones de dolares US$ hacia la region de África Sub-Sahariana") %>% kable_minimal()  %>% 
  add_footnote(label="Elaboración propia con base a datos del BCR",
               notation="symbol") %>%  kable_minimal()
Exportaciones totales de El Salvador en Millones de dolares US$ hacia la region de África Sub-Sahariana
anio Total Exportaciones El Salvador MM US$
2019 2.452792
2020 1.503626
* Elaboración propia con base a datos del BCR

2- obtenga el Saldo de la balanza comercial de El Salvador,con “Asia Sudoriental”, para el periodo 2017-2019, (en millones de US$)

data_comercio_exterior %>%
  filter(sub_region=="Asia Sudoriental",anio %in% c(2017:2019)) %>%
  group_by(anio) %>%
  summarise(`Total Exportaciones MM US$`=sum(valor_fob)/1e6,
            `Total Importaciones MM US$`=sum(valor_cif)/1e6,
            `Balanza Comercial ESA-Asia Sudoriental MM $`=`Total Exportaciones MM US$`-`Total Importaciones MM US$`) %>% 
  head() %>% kable(caption = "Saldo de la Balanza comercial de El Salvador respecto a Asia Sudoriental (2017-2019)") %>% kable_minimal()  %>%  
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_minimal()
Saldo de la Balanza comercial de El Salvador respecto a Asia Sudoriental (2017-2019)
anio Total Exportaciones MM US$ Total Importaciones MM US$ Balanza Comercial ESA-Asia Sudoriental MM $
2017 73.591111 269.4838 -195.8927
2018 16.609646 280.8837 -264.2740
2019 4.608928 262.5498 -257.9409
* Elaboración propia con base en datos del BCR

3- Por cada dólar exportado a la región Sudamericana, en el año 2019,¿Cuanto se importo?

data_comercio_exterior %>% filter(valor_cif==0, valor_fob>0, anio==2019,region_intermedia=="Sudamerica") %>% 
  summarise(`Total de exportaciones de El Salvador a Sudamérica`=sum(valor_fob))->X

data_comercio_exterior %>%
filter(region_intermedia=="Sudamerica", valor_cif>0, valor_fob==0, anio==2019) %>% 
  summarise(`Ratio Importaciones de El Salvador a Sudamerica`=sum(valor_cif))->M

Ratio_M_X<- (M/X)
print(Ratio_M_X)
##   Ratio Importaciones de El Salvador a Sudamerica
## 1                                        19.13248

Respuesta a pregunta: se Han importado la cifra de $19.13248 Millones de dólares por cada dolar de exportación hacia la región sudamericana, en el año 2019.

4- Calcule el indicador de Balassa de El Salvador, con México, Estados Unidos y Canadá, durante elperiodo 2017-2020 para el capítulo “01” SAC.

capitulo<-"01"
data.frame("anios"=2017:2020,
           "IB_Mexico"=sapply(X=2017:2020,FUN = indicadores_Balassa_capitulo,codigo_pais=484,capitulo=capitulo),
           "IB_USA"=sapply(X=2017:2020,FUN = indicadores_Balassa_capitulo,codigo_pais=840,capitulo=capitulo),
           "IB_Canada"=sapply(X=2017:2020,FUN = indicadores_Balassa_capitulo,codigo_pais=124,capitulo=capitulo))%>%
  kable(caption = "Indicador de Balassa de El Salvador con: México, Estados Unidos y Canadá, durante el periodo 2017-2020, para el capitulo “01” del SAC",
        digits = 2,align = "l")%>%
  kable_styling(bootstrap_options = "striped",
                full_width = TRUE)%>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_minimal()
Indicador de Balassa de El Salvador con: México, Estados Unidos y Canadá, durante el periodo 2017-2020, para el capitulo “01” del SAC
anios IB_Mexico IB_USA IB_Canada
2017 -0.58 0.36 0.40
2018 -0.82 0.32 0.61
2019 -0.90 0.40 0.19
2020 -0.98 0.70 0.04
* Elaboración propia con base en datos del BCR