Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| subjid | 0 | 1 | 10632.60 | 502.06 | 10001 | 10064.25 | 11017.5 | 11071.75 | 11127 | ▆▁▁▁▇ |
| birthwt | 0 | 1 | 3484.73 | 571.14 | 1180 | 3135.00 | 3500.0 | 3897.50 | 5100 | ▁▂▇▇▁ |
DS 150
November 5, 2023
There are 206 rows and 3 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/birth_dutch.
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| subjid | 0 | 1 | 10632.60 | 502.06 | 10001 | 10064.25 | 11017.5 | 11071.75 | 11127 | ▆▁▁▁▇ |
| birthwt | 0 | 1 | 3484.73 | 571.14 | 1180 | 3135.00 | 3500.0 | 3897.50 | 5100 | ▁▂▇▇▁ |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| sex | 0 | 1 | 4 | 6 | 0 | 2 | 0 |
pacman::p_load(tidyverse, fs, sf, arrow, googledrive, downloader, fs, glue, rvest, pins, connectapi)
t.dat <- tempfile()
download("https://github.com/stefvanbuuren/brokenstick/raw/71dc99e62ce57b58d5c1d2a1074fbd4bf394e559/data/smocc_hgtwgt.rda",t.dat, mode = "wb")
load(t.dat)
birth_dutch <- smocc_hgtwgt %>%
group_by(subjid) %>%
summarise(sex = sex[1], birthwt = birthwt[1]) %>%
ungroup()
board <- board_connect()
pin_write(board, birth_dutch, type = "parquet", access_type = "all")
pin_name <- "birth_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))This data is available to all.
Direct Download: birth_dutch.parquet
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/birth_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("birth_dutch")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.