The full set of runners for all races during 2010.

Data details

There are 821,303 rows and 20 columns. The data source¹ is used to create our data that is stored in our pins table. You can access this pin from a connection to posit.byui.edu using hathawayj/marathon_2010.

This data is available to all.

Variable description

• age The age of the runner
• gender The gender of the runner (M/F)
• chiptime The time in minutes for the runner
• year The year of the marathon
• marathon The name of the marathon
• country The country where the marathon was held
• finishers The number of finishers at the marathon

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
age	356927	0.57	39.40	10.92	6.00	31.00	39.00	47.00	91.00	▁▇▆▁▁
split_half	456187	0.44	127.48	26.67	59.25	109.77	123.12	140.60	681.93	▇▁▁▁▁
clocktime	375659	0.54	273.81	60.33	0.00	231.45	264.72	306.33	896.07	▁▇▁▁▁
chiptime	0	1.00	267.78	58.01	122.27	228.02	259.07	297.23	874.23	▇▅▁▁▁
year	0	1.00	2010.00	0.00	2010.00	2010.00	2010.00	2010.00	2010.00	▁▁▇▁▁
split_10k	574912	0.30	61.01	12.83	27.33	52.52	59.08	67.07	196.75	▇▆▁▁▁
split_30k	623570	0.24	194.56	44.96	82.90	163.15	186.90	217.93	511.85	▅▇▁▁▁
split_40k	657161	0.20	273.52	63.82	115.88	227.02	263.68	309.80	599.22	▂▇▃▁▁
finishers	0	1.00	13898.64	14144.96	2.00	2208.00	7880.00	22449.00	45109.00	▇▂▂▁▂
meantime	0	1.00	267.76	28.07	168.56	250.25	266.10	276.10	443.81	▁▇▂▁▁
female	141761	0.83	0.35	0.48	0.00	0.00	0.00	1.00	1.00	▇▁▁▁▅
us	0	1.00	0.62	0.49	0.00	0.00	1.00	1.00	1.00	▅▁▁▁▇
canada	0	1.00	0.03	0.18	0.00	0.00	0.00	0.00	1.00	▇▁▁▁▁
europe	0	1.00	0.31	0.46	0.00	0.00	0.00	1.00	1.00	▇▁▁▁▃
other	0	1.00	0.04	0.20	0.00	0.00	0.00	0.00	1.00	▇▁▁▁▁
age_gender	0	1.00	0.47	0.50	0.00	0.00	0.00	1.00	1.00	▇▁▁▁▇

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
gender	141761	0.83	1	1	0	2	0
marathon	0	1.00	7	62	0	641	0
country	0	1.00	2	14	0	33	0
marathon2	0	1.00	12	67	0	641	0

pacman::p_load(pins, tidyverse, downloader, fs, glue, rvest, googledrive, connectapi)


# Data is from master_marathon. 
sdrive <- shared_drive_find("byuids_data") # This will ask for authentication.
google_file <- drive_ls(sdrive)  |>
  filter(stringr::str_detect(name, "master_marathon"))
tempf <- tempfile()
drive_download(google_file, tempf)
dat <- read_csv(tempf)


# Wrangle (filter to 2010)
marathon_2010 <- dat %>%
  filter(year == 2010)



board <- board_connect()
pin_write(board, marathon_2010, type = "parquet")

pin_name <- "marathon_2010"
meta <- pin_meta(board, paste0("hathawayj/", pin_name))
client <- connect()
my_app <- content_item(client, meta$local$content_id)
set_vanity_url(my_app, paste0("data/", pin_name))

Access data

This data is available to all.

Direct Download: marathon_2010.parquet

R and Python Download:

URL Connections:

For public data, any user can connect and read the data using pins::board_connect_url() in R.

library(pins)
url_data <- "https://posit.byui.edu/data/marathon_2010/"
board_url <- board_connect_url(c("dat" = url_data))
dat <- pin_read(board_url, "dat")

Use this custom function in Python to have the data in a Pandas DataFrame.

import pandas as pd
import requests
from io import BytesIO

def read_url_pin(name):
  url = "https://posit.byui.edu/data/" + name + "/" + name + ".parquet"
  response = requests.get(url)
  if response.status_code == 200:
    parquet_content = BytesIO(response.content)
    pandas_dataframe = pd.read_parquet(parquet_content)
    return pandas_dataframe
  else:
    print(f"Failed to retrieve data. Status code: {response.status_code}")
    return None

# Example usage:
pandas_df = read_url_pin("marathon_2010")

Authenticated Connection:

Our connect server is https://posit.byui.edu which you assign to your CONNECT_SERVER environment variable. You must create an API key and store it in your environment under CONNECT_API_KEY.

Read more about environment variables and the pins package to understand how these environment variables are stored and accessed in R and Python with pins.

library(pins)
board <- board_connect(auth = "auto")
dat <- pin_read(board, "hathawayj/marathon_2010")

import os
from pins import board_rsconnect
from dotenv import load_dotenv
load_dotenv()
API_KEY = os.getenv('CONNECT_API_KEY')
SERVER = os.getenv('CONNECT_SERVER')

board = board_rsconnect(server_url=SERVER, api_key=API_KEY)
dat = board.pin_read("hathawayj/marathon_2010")

Footnotes

1. http://faculty.chicagobooth.edu/george.wu/research/marathon/data.htm