Data Manipulation with dplyr
James Chapman
Curriculum Manager, DataCamp
babynames %>% group_by(year) %>% summarize(year_total = sum(number))
# A tibble: 28 x 2 year year_total <dbl> <int> 1 1880 201478 2 1885 240822 3 1890 301352 4 1895 350934 5 1900 450148 6 1905 423875 7 1910 590607 8 1915 1830351 9 1920 2259494 10 1925 2330750 # … with 18 more rows
babynames %>% group_by(year) %>% mutate(year_total = sum(number))
# A tibble: 332,595 x 4 # Groups: year [28] year name number year_total <dbl> <chr> <int> <int> 1 1880 Aaron 102 201478 2 1880 Ab 5 201478 3 1880 Abbie 71 201478 4 1880 Abbott 5 201478 5 1880 Abby 6 201478 6 1880 Abe 50 201478 7 1880 Abel 9 201478 8 1880 Abigail 12 201478 9 1880 Abner 27 201478 10 1880 Abraham 81 201478 # … with 332,585 more rows
babynames %>% group_by(year) %>% mutate(year_total = sum(number)) %>% ungroup()
# A tibble: 332,595 x 4 year name number year_total <dbl> <chr> <int> <int> 1 1880 Aaron 102 201478 2 1880 Ab 5 201478 3 1880 Abbie 71 201478 4 1880 Abbott 5 201478 5 1880 Abby 6 201478 6 1880 Abe 50 201478 7 1880 Abel 9 201478 8 1880 Abigail 12 201478 9 1880 Abner 27 201478 10 1880 Abraham 81 201478 # … with 332,585 more rows
babynames %>% group_by(year) %>% mutate(year_total = sum(number)) %>% ungroup() %>% mutate(fraction = number / year_total)
# A tibble: 332,595 x 5 year name number year_total fraction <dbl> <chr> <int> <int> <dbl> 1 1880 Aaron 102 201478 0.000506 2 1880 Ab 5 201478 0.0000248 3 1880 Abbie 71 201478 0.000352 4 1880 Abbott 5 201478 0.0000248 5 1880 Abby 6 201478 0.0000298 6 1880 Abe 50 201478 0.000248 7 1880 Abel 9 201478 0.0000447 8 1880 Abigail 12 201478 0.0000596 9 1880 Abner 27 201478 0.000134 10 1880 Abraham 81 201478 0.000402 # … with 332,585 more rows
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