The group_by verb

Introduction to the Tidyverse

David Robinson

Chief Data Scientist, DataCamp

The summarize verb

gapminder %>%
  filter(year == 2007) %>%
  summarize(meanLifeExp = mean(lifeExp),
            totalPop = sum(pop))

# A tibble: 1 x 2
  meanLifeExp   totalPop
        <dbl>      <dbl>
1    67.00742 6251013179

Summarizing by year

gapminder %>%
  group_by(year) %>%
  summarize(meanLifeExp = mean(lifeExp),
            totalPop = sum(pop))

# A tibble: 12 x 3
    year meanLifeExp   totalPop
   <int>       <dbl>      <dbl>
 1  1952    49.05762 2406957150
 2  1957    51.50740 2664404580
 3  1962    53.60925 2899782974
 4  1967    55.67829 3217478384
 5  1972    57.64739 3576977158
 6  1977    59.57016 3930045807
 7  1982    61.53320 4289436840
 8  1987    63.21261 4691477418
 9  1992    64.16034 5110710260
10  1997    65.01468 5515204472
11  2002    65.69492 5886977579
12  2007    67.00742 6251013179

Summarizing by continent

gapminder %>%
  filter(year == 2007) %>%
  group_by(continent) %>%
  summarize(meanLifeExp = mean(lifeExp),
            totalPop = sum(pop))

# A tibble: 5 x 3
  continent meanLifeExp    totalPop
      <fct>       <dbl>       <dbl>
1    Africa    48.86533  6187585961
2  Americas    64.65874  7351438499
3      Asia    60.06490 30507333901
4    Europe    71.90369  6181115304
5   Oceania    74.32621   212992136

Summarizing by continent and year

gapminder %>%
  group_by(year, continent) %>%
  summarize(totalPop = sum(pop),
            meanLifeExp = mean(lifeExp))

# A tibble: 60 x 4
# Groups:   year [?]
    year continent   totalPop meanLifeExp
   <int>     <fct>      <dbl>       <dbl>
 1  1952    Africa  237640501    39.13550
 2  1952  Americas  345152446    53.27984
 3  1952      Asia 1395357351    46.31439
 4  1952    Europe  418120846    64.40850
 5  1952   Oceania   10686006    69.25500
 6  1957    Africa  264837738    41.26635
 7  1957  Americas  386953916    55.96028
 8  1957      Asia 1562780599    49.31854
 9  1957    Europe  437890351    66.70307
10  1957   Oceania   11941976    70.29500
# ... with 50 more rows

Let's practice!

Introduction to the Tidyverse