diving {ohenery}

Olympic Diving Data

Description

One hundred years of Men's Olympic Platform Diving records.

Usage

data(diving)

Format

A data.frame object with 695 observations and 13 columns.

The columns are defined as follows:

Name

The participant's name.

Age

The age of the participant at the time of the Olympics. Some values missing.

Height

The height of the participant at the time of the Olympics, in centimeters. Many values missing.

Weight

The height of the participant at the time of the Olympics, in kilograms. Many values missing.

Team

The string name of the team (country) which the participant represented.

NOC

The string name of the National Olympic Committee which the participant represented. This is a three character code.

Games

The string name of the Olympic games, including a year.

Year

The integer year of the Olympics. These range from 1906 through 2016.

City

The string name of the host city.

Medal

A string of “Gold”, “Silver”, “Bronze” or NA.

EventId

A unique integer ID for each Olympics.

AthleteId

A unique integer ID for each participant.

HOST_NOC

The string name of the National Olympic Committee of the nation hosting the Olympics. This is a three character code.

Note

The author makes no guarantees regarding correctness of this data.

Please attribute this data to the upstream harvester.

Author(s)

Steven E. Pav [e-mail]

Source

Data were collected by Randi Griffin from the website “sports-reference.com”, and staged on Kaggle at https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results.

Examples

library(dplyr)
library(forcats)
data(diving)

fitdat <- diving %>%
  mutate(Finish=case_when(grepl('Gold',Medal)   ~ 1,
                          grepl('Silver',Medal) ~ 2,
                          grepl('Bronze',Medal) ~ 3,
                          TRUE ~ 4)) %>%
  mutate(weight=ifelse(Finish <= 3,1,0)) %>%
  mutate(cut_age=cut(coalesce(Age,22.0),c(12,19.5,21.5,22.5,25.5,99),include.lowest=TRUE)) %>%
  mutate(country=forcats::fct_relevel(forcats::fct_lump(factor(NOC),n=5),'Other')) %>%
  mutate(home_advantage=NOC==HOST_NOC)

hensm(Finish ~ cut_age + country + home_advantage,data=fitdat,weights=weight,group=EventId,ngamma=3)