To pull data from the Aviation Weather Center METAR page (https://aviationweather.gov/cgi-bin/data/metar.php) into a list, you would need to use web scraping techniques. This involves making an HTTP request to the page, parsing the HTML content, and extracting the relevant data.

To accomplish this with Python, you can use libraries such as requests for making the HTTP request, and BeautifulSoup for parsing the HTML content.

Here is a sample code snippet to get you started:

import requests
from bs4 import BeautifulSoup

# Make a GET request to the METAR page
url = 'https://aviationweather.gov/cgi-bin/data/metar.php'
response = requests.get(url)

# Parse the HTML content
soup = BeautifulSoup(response.content, 'html.parser')

# Find the specific elements containing the METAR data
# Use the developer tools in your browser to find the HTML structure

# Example: If the METAR data is stored in a <div> with class 'metar-data'
# metar_data_div = soup.find('div', class_='metar-data')
# metar_list = metar_data_div.text.split('\n')

# Process the text to extract the METAR data into a list

# Print or further process the METAR data
# for metar in metar_list:
#     print(metar)

In this example, requests is used to perform the HTTP request, and BeautifulSoup for parsing the HTML content. You will need to inspect the HTML structure of the METAR page to identify the specific elements containing the METAR data.

Please note that web scraping should be done in accordance with the website's terms of use and with respect to any applicable legal regulations.