LED example bulbs of lumen output

Data details

There are 8,888 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/led_study.

This data is available to all.

Variable description

• id: An id for each LED light measured
• hours: The number of hours since the first measurement
• intensity: The lumen output of the bulb. 800 lumens maps to a 60 watt incandescent bulb (https://www.lumens.com/how-tos-and-advice/light-bulb-facts.html)
• normalized_intensity: The normalized light output based on the first measured intensity of the bulb
• percent_intensity: The normalized_intensity multiplied by 100

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
id	0	1	101.50	58.31	1.00	51.00	101.50	152.00	202.00	▇▇▇▇▇
hours	0	1	2262.32	1534.33	0.00	978.25	2050.00	3546.25	5010.00	▇▇▆▃▆
intensity	0	1	803.80	11.01	753.64	796.78	803.93	811.05	840.29	▁▁▇▆▁
normalized_intensity	0	1	1.01	0.01	0.99	1.01	1.01	1.02	1.04	▁▃▇▅▁
percent_intensity	0	1	101.25	0.68	98.96	100.79	101.28	101.72	103.52	▁▃▇▅▁

NULL

pacman::p_load(tidyverse, googledrive, connectapi)

sdrive <- shared_drive_find("byuids_data") # This will ask for authentication.
google_file <- drive_ls(sdrive)  |>
  filter(stringr::str_detect(name, "led_study.csv"))
tempf <- tempfile()
drive_download(google_file, tempf)
led_study <- read_csv(tempf)

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

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

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/led_study")

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/led_study")

Footnotes

1. J. Hathaway