Lead Exposure and Behavior

Data details

There are 72 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/lead_exposure_and_behavior.

This data is available to all.

Variable description

• Group: Subject group based on lead exposure (Nonexposed, Exposed)
• Gender: Gender (M, F)
• Age: Age (months)
• Lead: Concentration of lead in blood (micromoles per liter)
• BRS: Score from Behavior Rating Scale (BRS), in percentiles: higher numbers indicate less problematic behavior

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
Age	0	1	23.25	6.69	12.2	17.75	22.70	27.60	35.80	▆▇▇▅▅
Lead	0	1	0.50	0.29	0.0	0.27	0.52	0.63	1.18	▆▅▇▃▂
BRS	0	1	53.72	28.99	1.0	32.25	55.50	76.00	99.00	▆▆▆▇▇

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
Group	0	1	7	10	0	2	0
Gender	0	1	1	1	0	2	0

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

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


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

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

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/lead_exposure_and_behavior")

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/lead_exposure_and_behavior")

Footnotes

1. Alan L. Mendelsohn, Benard P. Dreyer, Arthur H. Fierman, Carolyn M. Rosen, Lori A. Legano, Hillary A. Kruger, Sylvia W. Lim, and Cheryl D. Courtlandt. Low-level lead exposure and behavior in early childhood. Pediatrics, 101(3):10, 1998.