Climate Change: Antarctica

Data details

There are 40 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/climate_change_antarctica.

This data is available to all.

Variable description

• Entity: Country name
• Code: 3-letter code for each country
• Year: Year
• antarctic_sea_ice_september: Amount of sea ice in Antarctica in September (millions of square kilometers)
• antarctic_sea_ice_february: Amount of sea ice in Antarctica in February (millions of square kilometers)

Variable summary

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
Year	0	1	1998.5	11.69	1979	1988.75	1998.5	2008.25	2018	▇▇▇▇▇
antarctic_sea_ice_september	0	1	18527513.5	436200.40	17680013	18185013.29	18565013.6	18805013.74	19760014	▂▇▇▂▁
antarctic_sea_ice_february	0	1	3072252.2	424448.59	2290002	2840002.08	2985002.2	3212502.35	3890003	▂▅▇▁▃

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
Entity	0	1	10	10	0	1	0
Code	0	1	3	3	0	1	0

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

# owid() doesn't work for this dataset right now because the source site is down 5/8/2024

# 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
# climate_change_antarctica <- owid('climate-change-antarctica')


# Until that issue is resolved, the data can be found in the google drive
# Download the file from google drive
sdrive <- shared_drive_find("byuids_data") # This will ask for authentication.
google_file <- drive_ls(sdrive) |>
  filter(stringr::str_detect(name, "climate-change-antarctica"))
tempf <- tempfile()
drive_download(google_file, tempf)
climate_change_antarctica <- read_csv(tempf)

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

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

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/climate_change_antarctica")

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/climate_change_antarctica")

Footnotes

1. https://ourworldindata.org/explorers/climate-change?facet=none&country=OWID_WRL~ATA&Metric=Antarctic+sea+ice+extent&Long-run+series%3F=false