Access to Drinking Water

Data details

There are 5,622 rows and 8 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/access_drinking_water_stacked.

This data is available to all.

Variable description

• entity: Country name
• code: 3-letter code for each country
• year: Year
• Share of the population using safely managed drinking water services: (Percent)
• Share of the population using only basic drinking water services: (Percent)
• Share of the population using limited drinking water services: (Percent)
• Share of the population using unimproved drinking water services: (Percent)
• Share of the population using surface water as a primary source of drinking water: (Percent)

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
year	0	1.00	2010.99	6.56	2000.00	2005.00	2011.00	2017.00	2022.00	▇▆▇▆▇
Share of the population using safely managed drinking water services	1838	0.67	68.67	30.19	1.43	45.53	77.85	96.43	100.00	▂▂▂▂▇
Share of the population using only basic drinking water services	1838	0.67	20.10	18.75	0.00	2.95	16.90	32.77	91.14	▇▃▃▁▁
Share of the population using limited drinking water services	0	1.00	3.53	5.77	0.00	0.00	0.72	4.78	37.50	▇▁▁▁▁
Share of the population using unimproved drinking water services	0	1.00	6.61	9.12	0.00	0.44	2.55	9.14	54.74	▇▂▁▁▁
Share of the population using surface water as a primary source of drinking water	94	0.98	3.32	6.15	0.00	0.00	0.22	3.77	49.42	▇▁▁▁▁

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
entity	0	1.00	4	38	0	254	0
code	506	0.91	3	8	0	232	0

pacman::p_load(tidyverse, pins, connectapi, owidR)

# owid() function downloads current data directly from Our World in Data.
# Use owid_search() to search for other OWID datasets.
# For more information, see the package documentation here: https://github.com/piersyork/owidR/blob/main/README.md
access_drinking_water_stacked <- owid('access-drinking-water-stacked')

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

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

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/access_drinking_water_stacked")

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/access_drinking_water_stacked")

Footnotes

1. https://ourworldindata.org/grapher/access-drinking-water-stacked?country=OWID_WRL_Low+incomeUpper-middle+income_High+incomeLower-middle+income_{Sub-Saharan+Africa}Central+and+Southern+Asia_{North+America+and+Europe}Latin+America+and+the+Caribbean~Western+Asia+and+Northern+Africa