Module 5: Apply 4

Import data

# excel file
data <- read_excel("data/myData.xlsx")
data

## # A tibble: 271,116 × 15
##       id name     sex   age   height weight team  noc   games  year season city 
##    <dbl> <chr>    <chr> <chr> <chr>  <chr>  <chr> <chr> <chr> <dbl> <chr>  <chr>
##  1     1 A Dijia… M     24    180    80     China CHN   1992…  1992 Summer Barc…
##  2     2 A Lamusi M     23    170    60     China CHN   2012…  2012 Summer Lond…
##  3     3 Gunnar … M     24    NA     NA     Denm… DEN   1920…  1920 Summer Antw…
##  4     4 Edgar L… M     34    NA     NA     Denm… DEN   1900…  1900 Summer Paris
##  5     5 Christi… F     21    185    82     Neth… NED   1988…  1988 Winter Calg…
##  6     5 Christi… F     21    185    82     Neth… NED   1988…  1988 Winter Calg…
##  7     5 Christi… F     25    185    82     Neth… NED   1992…  1992 Winter Albe…
##  8     5 Christi… F     25    185    82     Neth… NED   1992…  1992 Winter Albe…
##  9     5 Christi… F     27    185    82     Neth… NED   1994…  1994 Winter Lill…
## 10     5 Christi… F     27    185    82     Neth… NED   1994…  1994 Winter Lill…
## # ℹ 271,106 more rows
## # ℹ 3 more variables: sport <chr>, event <chr>, medal <chr>

State one question

Which medal type (Gold, Silver, Bronze) was won most frequently across all Olympic Games?

Plot data

data %>%
  filter(medal %in% c("Gold", "Silver", "Bronze")) %>%
  ggplot(aes(x = medal, fill = medal)) +
  geom_bar() +
  scale_fill_manual(values = c("Gold" = "gold", "Silver" = "gray", "Bronze" = "#cd7f32")) +
  labs(
    title = "Olympic Medal Counts Across All Games",
    x = "Medal Type",
    y = "Count"
  ) +
  theme_minimal()

Interpret

Gold medals were won the most frequently across all Olympic Games.