Begin

In this section we will examine Eurostat’s datasets. First, as an example we will compare goverment spending in research and development.

Load the required libraries:

library(eurostat)
library(dplyr)
library(readr)
library(tidyr)
library(lubridate)
library(DT)
library(purrr)
library(broom)
library(ggplot2)
library(ggthemes)
library(ggrepel)

RnD

Here we are going to examine the goverment pending on research and development. The table tipsst10 holds the corresponding data.

We can read the dataset by calling the get_eurostat function and we can store the results to a variable (here named rnd):

rnd <- get_eurostat("tipsst10")

We can examine the column names of the table (data frame) rnd:

names(rnd)

## [1] "sectperf" "unit"     "geo"      "time"     "values"

Or we examine the domain values of its columns:

rnd %>% select(sectperf) %>% distinct()

## # A tibble: 1 x 1
##   sectperf
##   <fct>   
## 1 TOTAL

rnd %>% select(unit) %>% distinct()

## # A tibble: 2 x 1
##   unit   
##   <fct>  
## 1 MIO_NAC
## 2 PC_GDP

We can filter the dataset, thus we can restrict it to specific rows:

rnd %>% 
    filter(unit == 'PC_GDP' & geo == 'EL')

## # A tibble: 18 x 5
##    sectperf unit   geo   time       values
##    <fct>    <fct>  <fct> <date>      <dbl>
##  1 TOTAL    PC_GDP EL    1995-01-01  0.42 
##  2 TOTAL    PC_GDP EL    1997-01-01  0.43 
##  3 TOTAL    PC_GDP EL    1999-01-01  0.570
##  4 TOTAL    PC_GDP EL    2001-01-01  0.56 
##  5 TOTAL    PC_GDP EL    2003-01-01  0.55 
##  6 TOTAL    PC_GDP EL    2004-01-01  0.53 
##  7 TOTAL    PC_GDP EL    2005-01-01  0.580
##  8 TOTAL    PC_GDP EL    2006-01-01  0.56 
##  9 TOTAL    PC_GDP EL    2007-01-01  0.580
## 10 TOTAL    PC_GDP EL    2008-01-01  0.66 
## 11 TOTAL    PC_GDP EL    2009-01-01  0.63 
## 12 TOTAL    PC_GDP EL    2010-01-01  0.6  
## 13 TOTAL    PC_GDP EL    2011-01-01  0.67 
## 14 TOTAL    PC_GDP EL    2012-01-01  0.7  
## 15 TOTAL    PC_GDP EL    2013-01-01  0.81 
## 16 TOTAL    PC_GDP EL    2014-01-01  0.83 
## 17 TOTAL    PC_GDP EL    2015-01-01  0.97 
## 18 TOTAL    PC_GDP EL    2016-01-01  1.01

rnd %>% 
    filter(unit == 'PC_GDP' & geo == 'EL') %>% 
    ggplot(aes(x = time, y = values)) +
    geom_line()

rnd %>% 
    filter(unit == 'PC_GDP' & geo %in% c('EL', 'PT')) %>% 
    ggplot(aes(x = time, y = values, colour = geo)) +
        geom_line(size = 1.2) + 
        theme_economist()

Plot the time series data:

rnd %>% 
    filter(unit == 'PC_GDP' & geo %in% c('EL', 'PT', 'CZ', 'BE')) %>% 
    mutate(label = if_else(time == max(time), as.character(geo), NA_character_)) %>%
    ggplot(aes(x = time, y = values, colour = geo)) +
    geom_line(size = 1.2) + 
    geom_label_repel(aes(label = label), nudge_x = 1, na.rm = TRUE) +
    scale_color_discrete(guide = FALSE) +
    theme_economist() +
    xlab("Time") + ylab("% GDP in RnD") +
    theme(text = element_text(size = 18))