w2w2015: Wharf to Wharf race data - 2015

In aaronferrucci/WharfToWharfR: Wharf to Wharf

Description

Data from the 2015 Wharf to Wharf race in Santa Cruz. This dataset is filtered and cleaned. The code for scraping, filtering and cleaning is here: https://github.com/aaronferrucci/wharf2wharf

Usage

w2w2015

Format

A data frame with fifteen variables: firstname, lastname, bib, city, state, country, age, sex, overall, oversex, overdiv, elapsed, elapsedTime, start, startTime

Source

https://github.com/aaronferrucci/wharf2wharf

Examples

# Look at the geneder balance...
table(w2w2015$sex)
# Most entrants are from the USA.
table(w2w2015$country)
#
Show the distribution of ages
library(ggplot2)
qplot(w2w2015$age, ylab = "", xlab = "age")
#
# Plot run time vs. age.
elapsed_ticks <- seq(0, max(w2w2015$elapsed), 900000)
ggplot(w2w2015, aes(x = age, y = elapsed, color=sex)) +
  scale_x_continuous(breaks = seq(0, 100, 10)) +
  scale_y_continuous(breaks = elapsed_ticks, name = "elapsed time (ms)") +
  geom_point() +
  expand_limits(y = 0.375 * 3600 * 1000) +
  stat_smooth(method = "gam", formula = y ~ s(x, bs="cs"))
#
# Plot start time vs. elapsed time
start_ticks <- seq(8.5 * 3600 * 1000, max(w2w2015$start), 0.0625 * 3600 * 1000)
ggplot(w2w2015, aes(x = elapsed, y = start, color = sex)) +
  scale_y_continuous(breaks = start_ticks) +
  scale_x_continuous(breaks = elapsed_ticks) +
  expand_limits(x = 0.25 * 3600 * 1000, y = 8.5 * 3600 * 1000) +
  geom_point()

aaronferrucci/WharfToWharfR documentation built on May 10, 2019, 3:20 a.m.