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map_filter <- function(dataset, variable, list_values, rbind = FALSE){

  variable <- enquo(variable)
  
  for_one_dataset <- function(dataset, variable, value){
    dataset %>%
      filter((!!variable) == value)
  }

  if (rbind) {

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# modified from https://www.brodrigues.co/blog/2018-10-05-ggplot2_purrr_officer/

create_pptx <- function(plt = last_plot(), path = file.choose()){
  if(!file.exists(path)) {
    out <- read_pptx()
  } else {
    out <- read_pptx(path)
  }
  
  out %>%

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dotspacemacs-configuration-layers
   '(elm
     python
     helm
     auto-completion
     ;; better-defaults
     emacs-lisp
     ess
     themes-megapack
     version-control

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"Order","Level","Code","Parent","Description","This item includes","This item also includes","Rulings","This item excludes","Reference to ISIC Rev. 4"
"398481","1","A",,"AGRICULTURE, FORESTRY AND FISHING","This section includes the exploitation of vegetal and animal natural resources, comprising the activities of growing of crops, raising and breeding of animals, harvesting of timber and other plants, animals or animal products from a farm or their natural habitats.",,,,"A"
"398482","2","01","A","Crop and animal production, hunting and related service activities","This division includes two basic activities, namely the production of crop products and production of animal products, covering also the forms of organic agriculture, the growing of genetically modified crops and the raising of genetically modified animals. This division includes growing of crops in open fields as well in greenhouses.
 
Group 01.5 (Mixed farming) breaks with the usual principles for identifying main activity. It accepts that many ag

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unmap T
map  t scrollLeft
map  n scrollRight
map  r scrollDown
map  s scrollUp
map d removeTab
map u restoreTab
map v previousTab
map l nextTab
map J Vomnibar.activateInNewTab

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	{ MODKEY|ShiftMask,             XK_Return, spawn,          {.v = termcmd } },
    { MODKEY,                       XK_u, spawn,        {.v = rofi_run} },
/*	{ MODKEY,                       XK_b,      togglebar,      {0} },*/
	{ MODKEY,                       XK_t,      focusstack,     {.i = +1 } },
	{ MODKEY,                       XK_s,      focusstack,     {.i = -1 } },
	{ MODKEY,                       XK_i,      incnmaster,     {.i = +1 } },
	{ MODKEY,                       XK_d,      incnmaster,     {.i = -1 } },
	{ MODKEY,                       XK_c,      setmfact,       {.f = -0.05} },
	{ MODKEY,                       XK_r,      setmfact,       {.f = +0.05} },
	{ MODKEY,                       XK_comma,      zoom,           {0} },

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---
title: "Title goes here"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
runtime: shiny
---

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country_name	visual	question_statistic	response_type	result_percent
Afghanistan	Population Pyramid	Female population, 14 or younger (in thousands)		7318
Afghanistan	Population Pyramid	Female population, 15-24 years old (in thousands)		3413
Afghanistan	Population Pyramid	Female population, 25 to 34 years old (in thousands)		2210
Afghanistan	Population Pyramid	Female population, 35 to 49 years old (in thousands)		1965
Afghanistan	Population Pyramid	Female population, 50 to 64 years old (in thousands)		992
Afghanistan	Population Pyramid	Female population, 65 years old or older (in thousands)		449
Afghanistan	Population Pyramid	Male population, 14 or younger (in thousands)		7705
Afghanistan	Population Pyramid	Male population, 15-24 years old (in thousands)		3649
Afghanistan	Population Pyramid	Male population, 25 to 34 years old (in thousands)		2421

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library(tidyverse)

data("population")


head(population)

pop_wide <- population %>%
  pivot_wider(names_from = country, values_from = population)