{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# *Statistics coded*: Young people - social inclusion \n",
    "\n",
    "Prepared by [**J.Grazzini**](mailto:jacopo.grazzini@ec.europa.eu) (*Eurostat*).\n",
    "\n",
    "This notebook illustrates the principles of storytelling through literate programming by reproducing some of the figures of the _Statistics Explained_article on [**young people and social inclusion**](https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Young_people_-_social_inclusion). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(\"eurostat\") \n",
    "library(\"ggplot2\")\n",
    "library(\"tidyr\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(repr)\n",
    "options(repr.plot.width=8, repr.plot.height=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>unit</th><th scope=col>indic_il</th><th scope=col>sex</th><th scope=col>age</th><th scope=col>geo</th><th scope=col>time</th><th scope=col>values</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>PC      </td><td>LI_R_M40</td><td>F       </td><td>Y16-29  </td><td>AT      </td><td>2017    </td><td>11.2    </td></tr>\n",
       "\t<tr><td>PC      </td><td>LI_R_M40</td><td>F       </td><td>Y16-29  </td><td>BE      </td><td>2017    </td><td> 5.9    </td></tr>\n",
       "\t<tr><td>PC      </td><td>LI_R_M40</td><td>F       </td><td>Y16-29  </td><td>BG      </td><td>2017    </td><td>19.3    </td></tr>\n",
       "\t<tr><td>PC      </td><td>LI_R_M40</td><td>F       </td><td>Y16-29  </td><td>CH      </td><td>2017    </td><td>  NA    </td></tr>\n",
       "\t<tr><td>PC      </td><td>LI_R_M40</td><td>F       </td><td>Y16-29  </td><td>CY      </td><td>2017    </td><td> 6.4    </td></tr>\n",
       "\t<tr><td>PC      </td><td>LI_R_M40</td><td>F       </td><td>Y16-29  </td><td>CZ      </td><td>2017    </td><td> 3.8    </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllll}\n",
       " unit & indic\\_il & sex & age & geo & time & values\\\\\n",
       "\\hline\n",
       "\t PC           & LI\\_R\\_M40 & F            & Y16-29       & AT           & 2017         & 11.2        \\\\\n",
       "\t PC           & LI\\_R\\_M40 & F            & Y16-29       & BE           & 2017         &  5.9        \\\\\n",
       "\t PC           & LI\\_R\\_M40 & F            & Y16-29       & BG           & 2017         & 19.3        \\\\\n",
       "\t PC           & LI\\_R\\_M40 & F            & Y16-29       & CH           & 2017         &   NA        \\\\\n",
       "\t PC           & LI\\_R\\_M40 & F            & Y16-29       & CY           & 2017         &  6.4        \\\\\n",
       "\t PC           & LI\\_R\\_M40 & F            & Y16-29       & CZ           & 2017         &  3.8        \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "unit | indic_il | sex | age | geo | time | values | \n",
       "|---|---|---|---|---|---|\n",
       "| PC       | LI_R_M40 | F        | Y16-29   | AT       | 2017     | 11.2     | \n",
       "| PC       | LI_R_M40 | F        | Y16-29   | BE       | 2017     |  5.9     | \n",
       "| PC       | LI_R_M40 | F        | Y16-29   | BG       | 2017     | 19.3     | \n",
       "| PC       | LI_R_M40 | F        | Y16-29   | CH       | 2017     |   NA     | \n",
       "| PC       | LI_R_M40 | F        | Y16-29   | CY       | 2017     |  6.4     | \n",
       "| PC       | LI_R_M40 | F        | Y16-29   | CZ       | 2017     |  3.8     | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  unit indic_il sex age    geo time values\n",
       "1 PC   LI_R_M40 F   Y16-29 AT  2017 11.2  \n",
       "2 PC   LI_R_M40 F   Y16-29 BE  2017  5.9  \n",
       "3 PC   LI_R_M40 F   Y16-29 BG  2017 19.3  \n",
       "4 PC   LI_R_M40 F   Y16-29 CH  2017   NA  \n",
       "5 PC   LI_R_M40 F   Y16-29 CY  2017  6.4  \n",
       "6 PC   LI_R_M40 F   Y16-29 CZ  2017  3.8  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "id = \"ilc_li02\"\n",
    "# id <-search_eurostat(\"At-risk-of-poverty rate by poverty threshold, age and sex\")$code[1]\n",
    "dat <-get_eurostat(id, time_format = \"num\", filters = list(age=\"Y16-29\", time=\"2017\", unit=\"PC\"))\n",
    "head(dat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "ctries <- c(\"EU28\", \"DK\", \"RO\", \"ES\", \"EL\", \"IT\", \"SE\", \"BG\", \"LU\", \"PT\", \"NL\", \"DE\", \"FI\", \"IE\", \"BE\", \"FR\", \"EE\", \"AT\", \"UK\", \"PL\", \"HR\", \"CY\", \"LV\", \"HU\", \"SK\", \"MT\", \"SI\", \"CZ\", \"NO\", \"CH\", \"IS\", \"RS\", \"MK\", \"TR\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Removed 8 rows containing missing values (position_stack).”"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8AAAAFoCAIAAAAXZAVmAAAACXBIWXMAABJ0AAASdAHeZh94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\nAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p<-ggplot(data=subset(dat, indic_il == \"LI_R_MD60\" & sex == \"T\" & geo %in% ctries), \n",
    "              aes(x=reorder(geo, -values), y=values)) +\n",
    " geom_bar(stat=\"identity\", fill=\"orange\") +\n",
    " xlab(\"Share of young people (aged 16-29 years) at risk of poverty, 2017\") +\n",
    " ylab(\"(%)\") \n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>age</th><th scope=col>sex</th><th scope=col>unit</th><th scope=col>geo</th><th scope=col>time</th><th scope=col>values</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>PC    </td><td>AT    </td><td>2017  </td><td>96.1  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>PC    </td><td>BE    </td><td>2017  </td><td>95.5  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>PC    </td><td>BG    </td><td>2017  </td><td>87.8  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>PC    </td><td>CH    </td><td>2017  </td><td>  NA  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>PC    </td><td>CY    </td><td>2017  </td><td>98.6  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>PC    </td><td>CZ    </td><td>2017  </td><td>97.2  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllll}\n",
       " age & sex & unit & geo & time & values\\\\\n",
       "\\hline\n",
       "\t Y16-19 & F      & PC     & AT     & 2017   & 96.1  \\\\\n",
       "\t Y16-19 & F      & PC     & BE     & 2017   & 95.5  \\\\\n",
       "\t Y16-19 & F      & PC     & BG     & 2017   & 87.8  \\\\\n",
       "\t Y16-19 & F      & PC     & CH     & 2017   &   NA  \\\\\n",
       "\t Y16-19 & F      & PC     & CY     & 2017   & 98.6  \\\\\n",
       "\t Y16-19 & F      & PC     & CZ     & 2017   & 97.2  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "age | sex | unit | geo | time | values | \n",
       "|---|---|---|---|---|---|\n",
       "| Y16-19 | F      | PC     | AT     | 2017   | 96.1   | \n",
       "| Y16-19 | F      | PC     | BE     | 2017   | 95.5   | \n",
       "| Y16-19 | F      | PC     | BG     | 2017   | 87.8   | \n",
       "| Y16-19 | F      | PC     | CH     | 2017   |   NA   | \n",
       "| Y16-19 | F      | PC     | CY     | 2017   | 98.6   | \n",
       "| Y16-19 | F      | PC     | CZ     | 2017   | 97.2   | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  age    sex unit geo time values\n",
       "1 Y16-19 F   PC   AT  2017 96.1  \n",
       "2 Y16-19 F   PC   BE  2017 95.5  \n",
       "3 Y16-19 F   PC   BG  2017 87.8  \n",
       "4 Y16-19 F   PC   CH  2017   NA  \n",
       "5 Y16-19 F   PC   CY  2017 98.6  \n",
       "6 Y16-19 F   PC   CZ  2017 97.2  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "id = \"ilc_lvps08\"\n",
    "# id <-search_eurostat(\"Share of young adults aged 18-34 living with their parents by age and sex\", fixed = TRUE)$code[1]\n",
    "dat <-get_eurostat(id, time_format = \"num\", filters = list(time=\"2017\", unit=\"PC\"))\n",
    "head(dat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Removed 16 rows containing missing values (geom_bar).”"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8AAAAFoCAIAAAAXZAVmAAAACXBIWXMAABJ0AAASdAHeZh94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\nN/839Yx3weeAAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p<-ggplot(data=subset(dat, geo %in% ctries & sex %in% c(\"F\", \"M\") & age == \"Y16-29\"), \n",
    "              aes(x=reorder(geo, -values), y=values, fill=sex)) +\n",
    " geom_bar(stat=\"identity\", position=position_dodge()) +\n",
    " xlab(\"Share of young people (aged 16-29 years) living with their parents, 2017\") +\n",
    " ylab(\"(%)\") \n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Removed 24 rows containing missing values (geom_point).”"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8AAAAFoCAIAAAAXZAVmAAAACXBIWXMAABJ0AAASdAHeZh94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\ngAE0AAAAAAAAZvh/AW/OSemS0zUAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p<-ggplot(data=subset(dat, geo %in% ctries & sex == \"T\" & age %in% c(\"Y16-29\",\"Y20-24\",\"Y25-29\")), \n",
    "              aes(x=reorder(geo, -values), y=values, fill=sex, col=age)) +\n",
    " geom_point() +\n",
    " xlab(\"Share of young people (aged 16-29 years) living with their parents, 2017\") +\n",
    " ylab(\"(%)\") \n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>unit</th><th scope=col>age</th><th scope=col>sex</th><th scope=col>geo</th><th scope=col>time</th><th scope=col>values</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>PC    </td><td>Y16-29</td><td>F     </td><td>EU28  </td><td>2007  </td><td>  NA  </td></tr>\n",
       "\t<tr><td>PC    </td><td>Y16-29</td><td>F     </td><td>EU28  </td><td>2008  </td><td>  NA  </td></tr>\n",
       "\t<tr><td>PC    </td><td>Y16-29</td><td>F     </td><td>EU28  </td><td>2009  </td><td>  NA  </td></tr>\n",
       "\t<tr><td>PC    </td><td>Y16-29</td><td>F     </td><td>EU28  </td><td>2010  </td><td>28.0  </td></tr>\n",
       "\t<tr><td>PC    </td><td>Y16-29</td><td>F     </td><td>EU28  </td><td>2011  </td><td>29.1  </td></tr>\n",
       "\t<tr><td>PC    </td><td>Y16-29</td><td>F     </td><td>EU28  </td><td>2012  </td><td>30.2  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllll}\n",
       " unit & age & sex & geo & time & values\\\\\n",
       "\\hline\n",
       "\t PC     & Y16-29 & F      & EU28   & 2007   &   NA  \\\\\n",
       "\t PC     & Y16-29 & F      & EU28   & 2008   &   NA  \\\\\n",
       "\t PC     & Y16-29 & F      & EU28   & 2009   &   NA  \\\\\n",
       "\t PC     & Y16-29 & F      & EU28   & 2010   & 28.0  \\\\\n",
       "\t PC     & Y16-29 & F      & EU28   & 2011   & 29.1  \\\\\n",
       "\t PC     & Y16-29 & F      & EU28   & 2012   & 30.2  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "unit | age | sex | geo | time | values | \n",
       "|---|---|---|---|---|---|\n",
       "| PC     | Y16-29 | F      | EU28   | 2007   |   NA   | \n",
       "| PC     | Y16-29 | F      | EU28   | 2008   |   NA   | \n",
       "| PC     | Y16-29 | F      | EU28   | 2009   |   NA   | \n",
       "| PC     | Y16-29 | F      | EU28   | 2010   | 28.0   | \n",
       "| PC     | Y16-29 | F      | EU28   | 2011   | 29.1   | \n",
       "| PC     | Y16-29 | F      | EU28   | 2012   | 30.2   | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  unit age    sex geo  time values\n",
       "1 PC   Y16-29 F   EU28 2007   NA  \n",
       "2 PC   Y16-29 F   EU28 2008   NA  \n",
       "3 PC   Y16-29 F   EU28 2009   NA  \n",
       "4 PC   Y16-29 F   EU28 2010 28.0  \n",
       "5 PC   Y16-29 F   EU28 2011 29.1  \n",
       "6 PC   Y16-29 F   EU28 2012 30.2  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "id = \"ilc_peps01\"\n",
    "# id <-search_eurostat(\"People at risk of poverty or social exclusion by age and sex\")$code[1]\n",
    "dat <-get_eurostat(id, time_format = \"num\", filters=list(unit=\"PC\", geo=\"EU28\", age=\"Y16-29\"))\n",
    "head(dat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Removed 9 rows containing missing values (geom_point).”"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8AAAAFoCAMAAACv2GIDAAADAFBMVEUAAAABAQECAgIDAwME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\nAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p<-ggplot(data=dat, aes(x=time, y=values, group=sex)) +\n",
    " geom_point() +\n",
    " xlab(\"Share of young people (aged 16-29 years) at risk of poverty or social exclusion, EU-28, 2007-2017 - by sex\") +\n",
    " ylab(\"(%)\") \n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>unit</th><th scope=col>indic_il</th><th scope=col>sex</th><th scope=col>age</th><th scope=col>geo</th><th scope=col>time</th><th scope=col>values</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>PC       </td><td>LI_R_MD60</td><td>T        </td><td>Y16-29   </td><td>EU28     </td><td>1995     </td><td>NA       </td></tr>\n",
       "\t<tr><td>PC       </td><td>LI_R_MD60</td><td>T        </td><td>Y16-29   </td><td>EU28     </td><td>1996     </td><td>NA       </td></tr>\n",
       "\t<tr><td>PC       </td><td>LI_R_MD60</td><td>T        </td><td>Y16-29   </td><td>EU28     </td><td>1997     </td><td>NA       </td></tr>\n",
       "\t<tr><td>PC       </td><td>LI_R_MD60</td><td>T        </td><td>Y16-29   </td><td>EU28     </td><td>1998     </td><td>NA       </td></tr>\n",
       "\t<tr><td>PC       </td><td>LI_R_MD60</td><td>T        </td><td>Y16-29   </td><td>EU28     </td><td>1999     </td><td>NA       </td></tr>\n",
       "\t<tr><td>PC       </td><td>LI_R_MD60</td><td>T        </td><td>Y16-29   </td><td>EU28     </td><td>2000     </td><td>NA       </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllll}\n",
       " unit & indic\\_il & sex & age & geo & time & values\\\\\n",
       "\\hline\n",
       "\t PC            & LI\\_R\\_MD60 & T             & Y16-29        & EU28          & 1995          & NA           \\\\\n",
       "\t PC            & LI\\_R\\_MD60 & T             & Y16-29        & EU28          & 1996          & NA           \\\\\n",
       "\t PC            & LI\\_R\\_MD60 & T             & Y16-29        & EU28          & 1997          & NA           \\\\\n",
       "\t PC            & LI\\_R\\_MD60 & T             & Y16-29        & EU28          & 1998          & NA           \\\\\n",
       "\t PC            & LI\\_R\\_MD60 & T             & Y16-29        & EU28          & 1999          & NA           \\\\\n",
       "\t PC            & LI\\_R\\_MD60 & T             & Y16-29        & EU28          & 2000          & NA           \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "unit | indic_il | sex | age | geo | time | values | \n",
       "|---|---|---|---|---|---|\n",
       "| PC        | LI_R_MD60 | T         | Y16-29    | EU28      | 1995      | NA        | \n",
       "| PC        | LI_R_MD60 | T         | Y16-29    | EU28      | 1996      | NA        | \n",
       "| PC        | LI_R_MD60 | T         | Y16-29    | EU28      | 1997      | NA        | \n",
       "| PC        | LI_R_MD60 | T         | Y16-29    | EU28      | 1998      | NA        | \n",
       "| PC        | LI_R_MD60 | T         | Y16-29    | EU28      | 1999      | NA        | \n",
       "| PC        | LI_R_MD60 | T         | Y16-29    | EU28      | 2000      | NA        | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  unit indic_il  sex age    geo  time values\n",
       "1 PC   LI_R_MD60 T   Y16-29 EU28 1995 NA    \n",
       "2 PC   LI_R_MD60 T   Y16-29 EU28 1996 NA    \n",
       "3 PC   LI_R_MD60 T   Y16-29 EU28 1997 NA    \n",
       "4 PC   LI_R_MD60 T   Y16-29 EU28 1998 NA    \n",
       "5 PC   LI_R_MD60 T   Y16-29 EU28 1999 NA    \n",
       "6 PC   LI_R_MD60 T   Y16-29 EU28 2000 NA    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "id = \"ilc_li02\"\n",
    "# id <-search_eurostat(\"At-risk-of-poverty rate by poverty threshold, age and sex\", fixed = TRUE)$code[1]\n",
    "dat <-get_eurostat(id, time_format = \"num\", filters = list(unit=\"PC\", geo=\"EU28\", indic_il=\"LI_R_MD60\", sex=\"T\", age=c(\"Y16-29\",\"Y20-24\",\"Y25-29\")))\n",
    "head(dat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Removed 45 rows containing missing values (geom_point).”"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8AAAAFoCAMAAACv2GIDAAAC/VBMVEUAAAABAQECAgIDAwME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\nYAA8zP8DJVNqOR5EEQIAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p<-ggplot(data=dat, aes(x=time, y=values, group=age)) +\n",
    " geom_point() +\n",
    " xlab(\"Share of young people at risk of poverty, EU-28, 2007-2017 - by age\") +\n",
    " ylab(\"(%)\") \n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>age</th><th scope=col>sex</th><th scope=col>hhstatus</th><th scope=col>unit</th><th scope=col>geo</th><th scope=col>time</th><th scope=col>values</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>P_NPAR</td><td>PC_POP</td><td>AT    </td><td>2016  </td><td>44.8  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>P_NPAR</td><td>PC_POP</td><td>BE    </td><td>2016  </td><td>  NA  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>P_NPAR</td><td>PC_POP</td><td>BG    </td><td>2016  </td><td>74.4  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>P_NPAR</td><td>PC_POP</td><td>CH    </td><td>2016  </td><td>  NA  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>P_NPAR</td><td>PC_POP</td><td>CY    </td><td>2016  </td><td>  NA  </td></tr>\n",
       "\t<tr><td>Y16-19</td><td>F     </td><td>P_NPAR</td><td>PC_POP</td><td>CZ    </td><td>2016  </td><td>  NA  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllll}\n",
       " age & sex & hhstatus & unit & geo & time & values\\\\\n",
       "\\hline\n",
       "\t Y16-19   & F        & P\\_NPAR & PC\\_POP & AT       & 2016     & 44.8    \\\\\n",
       "\t Y16-19   & F        & P\\_NPAR & PC\\_POP & BE       & 2016     &   NA    \\\\\n",
       "\t Y16-19   & F        & P\\_NPAR & PC\\_POP & BG       & 2016     & 74.4    \\\\\n",
       "\t Y16-19   & F        & P\\_NPAR & PC\\_POP & CH       & 2016     &   NA    \\\\\n",
       "\t Y16-19   & F        & P\\_NPAR & PC\\_POP & CY       & 2016     &   NA    \\\\\n",
       "\t Y16-19   & F        & P\\_NPAR & PC\\_POP & CZ       & 2016     &   NA    \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "age | sex | hhstatus | unit | geo | time | values | \n",
       "|---|---|---|---|---|---|\n",
       "| Y16-19 | F      | P_NPAR | PC_POP | AT     | 2016   | 44.8   | \n",
       "| Y16-19 | F      | P_NPAR | PC_POP | BE     | 2016   |   NA   | \n",
       "| Y16-19 | F      | P_NPAR | PC_POP | BG     | 2016   | 74.4   | \n",
       "| Y16-19 | F      | P_NPAR | PC_POP | CH     | 2016   |   NA   | \n",
       "| Y16-19 | F      | P_NPAR | PC_POP | CY     | 2016   |   NA   | \n",
       "| Y16-19 | F      | P_NPAR | PC_POP | CZ     | 2016   |   NA   | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  age    sex hhstatus unit   geo time values\n",
       "1 Y16-19 F   P_NPAR   PC_POP AT  2016 44.8  \n",
       "2 Y16-19 F   P_NPAR   PC_POP BE  2016   NA  \n",
       "3 Y16-19 F   P_NPAR   PC_POP BG  2016 74.4  \n",
       "4 Y16-19 F   P_NPAR   PC_POP CH  2016   NA  \n",
       "5 Y16-19 F   P_NPAR   PC_POP CY  2016   NA  \n",
       "6 Y16-19 F   P_NPAR   PC_POP CZ  2016   NA  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "id = \"yth_incl_060\"\n",
    "# id <-search_eurostat(\"Young people's at-risk-of-poverty rate by sex, age and living/not living with parents\", fixed = TRUE)$code[1]\n",
    "dat <-get_eurostat(id, time_format = \"num\", filters = list(time=\"2016\"))\n",
    "head(dat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Removed 12 rows containing missing values (geom_bar).”"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8AAAAFoCAIAAAAXZAVmAAAACXBIWXMAABJ0AAASdAHeZh94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\nRhvmiTp6opQAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p<-ggplot(data=subset(dat, geo %in% ctries & age == \"Y16-29\"), \n",
    "              aes(x=reorder(geo, -values), y=values, fill=hhstatus)) +\n",
    " geom_bar(stat=\"identity\", position=position_dodge()) +\n",
    " xlab(\"Share of young people (aged 16-29 years) at risk of poverty, 2016 - by HH status\") +\n",
    " ylab(\"(%)\") \n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}