A.11 Summaries by team using group_by

A.11 Summaries by team using `group_by`

Now we can find average points scored by each team. When we use group_by, whatever operations come next will be done separately for each group.

Code

dd %>% 
  group_by(team) %>%
  summarise(    score = mean(    score), 
            opp.score = mean(opp.score))

# A tibble: 30 × 3
   team  score opp.score
   <chr> <dbl>     <dbl>
 1 ATL    114.      112.
 2 BKN    113.      112.
 3 BOS    112.      104.
 4 CHA    115.      115.
 5 CHI    112.      112 
 6 CLE    108.      106.
 7 DAL    108.      105.
 8 DEN    113.      110.
 9 DET    105.      113.
10 GSW    111       105.
# ℹ 20 more rows

Here the summarise operations that we saw before is performed separately on each team instead of for the entire data frame.

Sometimes it can help to visualize this in our minds by pretending that group_by(team) gives you separate data frames for each team. Then whatever operation comes next is performed on each of those data frame.