Forced Expiratory Volume

Data details

There are 654 rows and 5 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/forced_expiratory_volume.

This data is available to all.

Variable description

• Age: Person age (years)
• FEV: Forced expiratory volume (liters)
• Height: Person height (inches)
• Gender: Gender (Female, Male)
• SmokingStatus: Smoking status (Smoker, Nonsmoker)

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
Age	0	1	9.93	2.95	3.00	8.00	10.00	12.00	19.00	▂▇▇▃▁
FEV	0	1	2.64	0.87	0.79	1.98	2.54	3.12	5.79	▃▇▆▂▁
Height	0	1	61.14	5.70	46.00	57.00	61.50	65.50	74.00	▂▅▇▇▂

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
Gender	0	1	4	6	0	2	0
SmokingStatus	0	1	6	9	0	2	0

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

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


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

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

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/forced_expiratory_volume")

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/forced_expiratory_volume")

Footnotes

1. M. Kahn. An exhalent problem for teaching statistics. Journal of Statistics Education, 13(2), 2003. Bernard Rosner. Fundamentals of Biostatistics. Duxbury, Belmont, CA, USA, sixth edition, 2006.