BYU-I Course Project Data - Dutch child height and weight measurements

Data details

There are 2,000 rows and 8 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/childhealth_dutch.

Variable description

subjid: unique identifyer of each child
sex: Male or Female
agedays: Age in days
gagebrth: Gestational age at birth (days)
htcm: Length/height in cm (34-102)
wtkg: Weight measurement in kg (0.8-20.5)
haz: Height in SDS relative to WHO child growth standard
waz: Weight in SDS relative to WHO child growth standard

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
subjid	0	1.00	10637.52	500.27	10001.00	10064.00	11018.00	11072.00	11127.00	▆▁▁▁▇
agedays	3	1.00	274.38	238.33	0.00	58.00	196.00	456.00	978.00	▇▃▃▂▁
gagebrth	0	1.00	281.35	12.52	227.00	276.00	283.00	290.00	304.00	▁▁▂▇▆
htcm	40	0.98	69.08	12.42	38.00	57.50	69.50	79.00	97.00	▁▇▆▇▂
wtkg	19	0.99	8.10	3.30	1.18	5.08	8.22	10.70	16.50	▅▇▇▆▂
haz	40	0.98	0.30	1.10	-6.60	-0.38	0.37	1.02	3.71	▁▁▃▇▁
waz	19	0.99	0.29	0.99	-5.98	-0.30	0.33	0.96	3.11	▁▁▂▇▂

Variable type: character

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

Explore generating code using R

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

tdat <- tempfile()
download("https://github.com/stefvanbuuren/brokenstick/raw/71dc99e62ce57b58d5c1d2a1074fbd4bf394e559/data/smocc_hgtwgt.rda",tdat, mode = "wb")

load(tdat)

childhealth_dutch <- smocc_hgtwgt |>
  select(subjid, sex, agedays, gagebrth, htcm, wtkg, haz, waz)

board <- board_connect()

pin_write(board, childhealth_dutch, "childhealth_dutch", type = "parquet", access_type = "all")

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

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/childhealth_dutch")

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/childhealth_dutch")

Footnotes

https://github.com/stefvanbuuren/brokenstick ↩︎