function summarise

Question

I am using a database with information about the Olympics(https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results) and I want to analyze the data on the Olympic sports in which Brazil was medalist. I used the Summarize() function to get a column with number of medals per sport.

but when I go to sum up this column I get the error "Error: object 'sum(total2)' not found".

teste <- na.omit(subset(df1, select = c(Medal, Team, Sport, Event)))
teste <- teste %>% rename(pf = Sport)
teste <- teste %>% rename(pv = Medal)
data ＜- teste %＞% filter(Team=='Brazil') %>% 
        group_by(pv, pf) %＞% distinct(Event) %>% 
        summarize(total2 = n())
        sum(total2)

I’ve tried the function colSum but returns the same error. Taking advantage of the post, would it be possible to create a pie Chart with the medalist sports? I tried to do using the ggplot2 but I couldn’t.

Answer 1

The following code counts the medals that Brazil had at the Olympic Games.

library(dplyr)
library(readr)
library(ggplot2)

fl <- list.files(pattern = 'athlete.*\\.csv$')
fl

cols_spec <- cols(
  ID = col_double(),
  Name = col_character(),
  Sex = col_character(),
  Age = col_double(),
  Height = col_double(),
  Weight = col_double(),
  Team = col_character(),
  NOC = col_character(),
  Games = col_character(),
  Year = col_double(),
  Season = col_character(),
  City = col_character(),
  Sport = col_character(),
  Event = col_character(),
  Medal = col_character()
)

df1 <- read_csv(fl, col_types = cols_spec)

After reading the file, filter by country and group the data with summarise. The result, with only 2 columns, is saved in the date.frame cont_medalhas.

df1 %>%
  filter(Team == 'Brazil') %>%
  select(Medal, Sport) %>%
  na.omit() %>%
  group_by(Sport, Medal) %>%
  summarize(Total = n(), .groups = 'drop') -> cont_medalhas

Now the totals. Brazil had in all 449 medals in 14 sports (or, considering that I am Portuguese, sports).

cont_medalhas %>% pull(Total) %>% sum()
#[1] 449

cont_medalhas %>% distinct(Sport) %>% nrow()
#[1] 14

Finally, the bar graph. Colors come of this post.

cont_medalhas %>%
  mutate(Sport = factor(Sport),
         Medal = factor(Medal, levels = c('Gold', 'Silver', 'Bronze'))) %>%
  ggplot(aes(Sport, Total, fill = Medal)) +
  geom_col(position = position_dodge2(width = 0.9, preserve = 'single')) +
  scale_fill_manual(values = c('#FEE101', '#A7A7AD', '#A77044')) +
  theme_bw() +
  theme(axis.text.x = element_text(angle = 60, vjust = 1, hjust = 1))