Week 5: Apply 4

Import data

TidyTuesday NHL

# excel file
NHL <- read_csv("../00_data/NHL_attendance.csv")

## Rows: 10846 Columns: 8
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): team, team_name
## dbl (6): year, total, home, away, week, weekly_attendance
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

NHL

State one question

Who had the best atteadnce this season

Plot data

NHL %>%
    
    # Select a year
    filter(year == 2019) %>%
    
    # Filter for yearly total attendance by team
    distinct(team_name, total) %>%
    
    # Plot
    ggplot(aes(total, fct_reorder(team_name, total))) +
    geom_col(fill = "midnightblue") +
    scale_x_continuous(labels = scales::number_format(scale = 0.000001)) +
    labs(title = "NFL Teams by Attendance in 2019",
         x = "Number of People in Millions", y = NULL)

NHL %>%
    
    # Filter for yearly total attendance by team
    distinct(team_name, year, total) %>%
    
    group_by(year) %>%
    slice_max(total, n = 5) %>%
    ungroup() %>%
    
    ggplot(aes(total, tidytext::reorder_within(team_name, total, year))) +
    geom_col(show.legend = FALSE) +
    facet_wrap(~year, scales = "free") +
    scale_x_continuous(labels = scales::number_format(scale = 0.000001)) +
    tidytext::scale_y_reordered() +
    labs(title = "Top Five NFL Teams in Attendance",
         x = "Number of People in Millions", y = NULL)

Interpret

The Cowboys are clearly the most popular NFL team of the last decade. What happened to the Redskins?