Homework 3

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)
df

## # A tibble: 25,528 × 6
##    name                    sex     age team     year medalist
##    <chr>                   <chr> <dbl> <chr>   <dbl> <lgl>   
##  1 Paavo Johannes Aaltonen M        28 Finland  1948 TRUE    
##  2 Paavo Johannes Aaltonen M        28 Finland  1948 TRUE    
##  3 Paavo Johannes Aaltonen M        28 Finland  1948 FALSE   
##  4 Paavo Johannes Aaltonen M        28 Finland  1948 TRUE    
##  5 Paavo Johannes Aaltonen M        28 Finland  1948 FALSE   
##  6 Paavo Johannes Aaltonen M        28 Finland  1948 FALSE   
##  7 Paavo Johannes Aaltonen M        28 Finland  1948 FALSE   
##  8 Paavo Johannes Aaltonen M        28 Finland  1948 TRUE    
##  9 Paavo Johannes Aaltonen M        32 Finland  1952 FALSE   
## 10 Paavo Johannes Aaltonen M        32 Finland  1952 TRUE    
## # ℹ 25,518 more rows

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

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

## # A tibble: 2,703 × 6
##    name              sex     age team     year medalist
##    <chr>             <chr> <dbl> <chr>   <dbl> <lgl>   
##  1 Nstor Abad Sanjun M        23 Spain    2016 FALSE   
##  2 Nstor Abad Sanjun M        23 Spain    2016 FALSE   
##  3 Nstor Abad Sanjun M        23 Spain    2016 FALSE   
##  4 Nstor Abad Sanjun M        23 Spain    2016 FALSE   
##  5 Nstor Abad Sanjun M        23 Spain    2016 FALSE   
##  6 Nstor Abad Sanjun M        23 Spain    2016 FALSE   
##  7 Katja Abel        F        25 Germany  2008 FALSE   
##  8 Katja Abel        F        25 Germany  2008 FALSE   
##  9 Katja Abel        F        25 Germany  2008 FALSE   
## 10 Katja Abel        F        25 Germany  2008 FALSE   
## # ℹ 2,693 more rows

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

df2 |>
  group_by(year) |>
  summarize(
  n = n()
)

## # A tibble: 3 × 2
##    year     n
##   <dbl> <int>
## 1  2008   994
## 2  2012   848
## 3  2016   861

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

only_year <- olympic_gymnasts |>
  group_by(year) |>
  summarize(
  n = n()
)
only_year

## # A tibble: 29 × 2
##     year     n
##    <dbl> <int>
##  1  1896    73
##  2  1900    33
##  3  1904   317
##  4  1906    70
##  5  1908   240
##  6  1912   310
##  7  1920   206
##  8  1924   499
##  9  1928   561
## 10  1932   140
## # ℹ 19 more rows

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
q5 <- df |>
  head(100) |>
  select(name, year) |> 
  arrange(year)
q5

## # A tibble: 100 × 2
##    name              year
##    <chr>            <dbl>
##  1 Isak Abrahamsen   1912
##  2 Alf Lied Aanning  1920
##  3 Karl Jan Aas      1920
##  4 Andrei Abraham    1936
##  5 Andrei Abraham    1936
##  6 Andrei Abraham    1936
##  7 Andrei Abraham    1936
##  8 Andrei Abraham    1936
##  9 Andrei Abraham    1936
## 10 Andrei Abraham    1936
## # ℹ 90 more rows

Discussion: Enter your discussion of results here. Create a new data with the top 100 names then sort them by year. I created a new data set named q5 from df , then i used head to get the top 100 then i used select to get the name and the year .Finally, I used the arrange to sort the year.