Body Temperature

Data details

There are 148 rows and 2 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/body_temp.

This data is available to all.

Variable description

• Gender: Gender of subject.
  
• BodyTemp: Body temperature (Fahrenheit)

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
BodyTemp	0	1	98.23	0.74	96.2	97.8	98.3	98.7	100.8	▂▅▇▂▁

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
Gender	0	1	4	6	0	2	0

library(tidyverse)
library(pins)
library(connectapi)

body_temp <- read_csv('https://github.com/byuistats/data/raw/master/BodyTemp/BodyTemp.csv')


# Publish the data to the server with Bro. Hathaway as the owner.
board <- board_connect()
pin_write(board, body_temp, type = "parquet", access_type = "all")

pin_name <- "body_temp"
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: body_temp.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/body_temp/"
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("body_temp")

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/body_temp")

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/body_temp")

Footnotes

1. [Representative data from: Mackowiak, P. A., Wasserman, S. S., and Levine, M. M. “A Critical Appraisal of 98.6 Degrees F, the Upper Limit of the Normal Body Temperature, and Other Legacies of Carl Reinhold August Wunderlich.” Journal of the American Medical Association. 268, 12 (23-30 September 1992): 1578-80. (Data were extracted from Figure 1 of the article. Relative frequencies were multiplied by n=148 to get representative counts at each body temperature.)](Representative data from: Mackowiak, P. A., Wasserman, S. S., and Levine, M. M. “A Critical Appraisal of 98.6 Degrees F, the Upper Limit of the Normal Body Temperature, and Other Legacies of Carl Reinhold August Wunderlich.” Journal of the American Medical Association. 268, 12 (23-30 September 1992): 1578-80. (Data were extracted from Figure 1 of the article. Relative frequencies were multiplied by n=148 to get representative counts at each body temperature.))