Do not change anything in the following chunk

You will be working on olympic_gymnasts dataset. Do not change the code below:

olympics <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-07-27/olympics.csv')

olympic_gymnasts <- olympics %>% 
  filter(!is.na(age)) %>%             # only keep athletes with known age
  filter(sport == "Gymnastics") %>%   # keep only gymnasts
  mutate(
    medalist = case_when(             # add column for success in medaling
      is.na(medal) ~ FALSE,           # NA values go to FALSE
      !is.na(medal) ~ TRUE            # non-NA values (Gold, Silver, Bronze) go to TRUE
    )
  )

More information about the dataset can be found at

https://github.com/rfordatascience/tidytuesday/blob/master/data/2021/2021-07-27/readme.md

Question 1: Create a subset dataset with the following columns only: name, sex, age, team, year and medalist. Call it df.

df<- olympic_gymnasts|>
  select(name, sex, age, team, year, medalist)

Question 2: From df create df2 that only have year of 2008 2012, and 2016

df2<- df|> 
  filter(year%in%c(2008,2012,2016))

Question 3 Group by these three years (2008,2012, and 2016) and summarize the mean of the age in each group.

group_by(df2)|>
summarize(mean(age))
## # A tibble: 1 × 1
##   `mean(age)`
##         <dbl>
## 1        21.9

Question 4 Use olympic_gymnasts dataset, group by year, and find the mean of the age for each year, call this dataset oly_year. (optional after creating the dataset, find the minimum average age)

oly_year<-olympic_gymnasts|> 
  group_by(year)%>%
summarise(mean_age = mean(age, na.rm=T))

Question 5 This question is open ended. Create a question that requires you to use at least two verbs. Create a code that answers your question. Then below the chunk, reflect on your question choice and coding procedure

# Your R code here
#Which gender took home more medals and what was year they won in?
olympic_gymnasts|>
group_by(sex,medalist,year)
## # A tibble: 25,528 × 16
## # Groups:   sex, medalist, year [98]
##       id name     sex     age height weight team  noc   games  year season city 
##    <dbl> <chr>    <chr> <dbl>  <dbl>  <dbl> <chr> <chr> <chr> <dbl> <chr>  <chr>
##  1    17 Paavo J… M        28    175     64 Finl… FIN   1948…  1948 Summer Lond…
##  2    17 Paavo J… M        28    175     64 Finl… FIN   1948…  1948 Summer Lond…
##  3    17 Paavo J… M        28    175     64 Finl… FIN   1948…  1948 Summer Lond…
##  4    17 Paavo J… M        28    175     64 Finl… FIN   1948…  1948 Summer Lond…
##  5    17 Paavo J… M        28    175     64 Finl… FIN   1948…  1948 Summer Lond…
##  6    17 Paavo J… M        28    175     64 Finl… FIN   1948…  1948 Summer Lond…
##  7    17 Paavo J… M        28    175     64 Finl… FIN   1948…  1948 Summer Lond…
##  8    17 Paavo J… M        28    175     64 Finl… FIN   1948…  1948 Summer Lond…
##  9    17 Paavo J… M        32    175     64 Finl… FIN   1952…  1952 Summer Hels…
## 10    17 Paavo J… M        32    175     64 Finl… FIN   1952…  1952 Summer Hels…
## # ℹ 25,518 more rows
## # ℹ 4 more variables: sport <chr>, event <chr>, medal <chr>, medalist <lgl>

Discussion: Enter your discussion of results here.