Baby Boom

Data details

There are 44 rows and 4 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/baby_boom.

This data is available to all.

Variable description

• Time Time of birth, 24-hour clock (2010 = 8:10 PM)
• Gender Gender of baby (1 - female, 2 = male)
• Weight Weight of baby (grams)
• Minutes Number of minutes past midnight the baby was born
• WaitTimes Number of minutes between the current and previous births

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
Gender	0	1.00	1.59	0.50	1	1.00	2.0	2.00	2	▆▁▁▁▇
Weight	0	1.00	3275.95	528.03	1745	3141.50	3404.0	3571.75	4162	▂▁▂▇▃
Minutes	0	1.00	788.73	416.07	5	482.75	846.5	1158.50	1435	▆▃▆▇▇
WaitTimes	1	0.98	33.26	29.56	1	14.00	27.0	46.00	157	▇▃▁▁▁

NULL

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

baby_boom <- read_csv('https://github.com/byuistats/data/raw/master/BabyBoom-JSE/BabyBoom-JSE.csv')

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

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

Authenticated Connection:

Our connect server is https://posit.byui.edu which you assign to your CONNECT_SERVER environment variable. You must create and 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/baby_boom")

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/baby_boom")

Footnotes

1. S Steele. Babies by the dozen for Christmas: 24-hour baby boom. The Sunday Mail (Brisbane), page 7, December 21, 1997. Peter K. Dunn. A simple dataset for demonstrating common distributions. Journal of Statistics Education, 7(3), 1999.