NULL
Data details
There are 640 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/tb_dictionary.
This data is available to all.
Variable summary
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| variable_name | 0 | 1.00 | 2 | 32 | 0 | 640 | 0 |
| dataset | 0 | 1.00 | 6 | 29 | 0 | 19 | 0 |
| code_list | 566 | 0.12 | 11 | 235 | 0 | 27 | 0 |
| definition | 0 | 1.00 | 3 | 339 | 0 | 639 | 0 |
Explore generating code using R
library(tidyverse)
library(pins)
library(connectapi)
tb_dictionary <- read_csv("https://extranet.who.int/tme/generateCSV.asp?ds=dictionary")
# Publish the data to the server with Bro. Hathaway as the owner.
board <- board_connect()
pin_write(board, tb_dictionary, type = "parquet")
pin_name <- "tb_dictionary"
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: tb_dictionary.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/tb_dictionary/"
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("tb_dictionary")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/tb_dictionary")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/tb_dictionary")