13 Solutions || Adv. Data Manipulation

suppressPackageStartupMessages(library(gapminder))
suppressPackageStartupMessages(library(dplyr))

Write one command ( can span multiple lines) using pipes that will output a data frame that has only the columns lifeExp, country and year for the records before the year 2000 from African countries, but not for other Continents.

tidy_africa <- gapminder %>%
                dplyr::filter(continent == "Africa") %>%
                dplyr::select(year, country, lifeExp)
head(tidy_africa)

## # A tibble: 6 × 3
##    year country lifeExp
##   <int> <fct>     <dbl>
## 1  1952 Algeria    43.1
## 2  1957 Algeria    45.7
## 3  1962 Algeria    48.3
## 4  1967 Algeria    51.4
## 5  1972 Algeria    54.5
## 6  1977 Algeria    58.0

Calculate the average life expectancy per country. Which country has the longest average life expectancy and which one the shortest average life expectancy?

gapminder %>%
   dplyr::group_by(country) %>%
   dplyr::summarize(mean_lifeExp = mean(lifeExp)) %>%
   dplyr::filter(mean_lifeExp == min(mean_lifeExp) | mean_lifeExp == max(mean_lifeExp))

## # A tibble: 2 × 2
##   country      mean_lifeExp
##   <fct>               <dbl>
## 1 Iceland              76.5
## 2 Sierra Leone         36.8

In the previous hands-on you discovered that all the entries from 2007 are actually from 2008. Write a command to edit the data accordingly using pipes. In the same command filter only the entries from 2008 to verify the change.

gapminder %>%
  dplyr::mutate(year = ifelse(year==2007,2008,year)) %>%
  dplyr::filter(year==2008) %>%
  head()

## # A tibble: 6 × 6
##   country     continent  year lifeExp      pop gdpPercap
##   <fct>       <fct>     <dbl>   <dbl>    <int>     <dbl>
## 1 Afghanistan Asia       2008    43.8 31889923      975.
## 2 Albania     Europe     2008    76.4  3600523     5937.
## 3 Algeria     Africa     2008    72.3 33333216     6223.
## 4 Angola      Africa     2008    42.7 12420476     4797.
## 5 Argentina   Americas   2008    75.3 40301927    12779.
## 6 Australia   Oceania    2008    81.2 20434176    34435.