• Go to the Food Bank information page from https://data.virginia.gov/api/views/xvir-sctz/rows.xml?accessType=DOWNLOAD
• Use that page to obtain the data using requests.
• Examine the structure of the data.
• Generate the code in Python to obtain the names of the localities where the greatest distribution of food in pounds was made, the greatest number of individuals served, and the greatest number of households served in the month of April 2019.
• Print your name and the labels for the data requested.
• Markdown or comment on your code and submit a  Jupyter Notebook file named ScrapeXML.ipynb.
•  

Transcribed Image Text:

import requests from 1xml import objectify URL = 'https://data.virginia.gov/api/views/xvir-sctz/rows.xml? accessType=DOWNLOAD' response = requests.get(URL).content import requests from 1xml import objectify #parse xml file root = objectify.fromstring(response) #print data print (response) import requests from 1xml import objectify URL = 'https://data.virginia.gov/api/views/xvir-sctz/rows.xml? accessType=DOWNLOAD' response = requests.get(URL).content import requests from 1xml import objectify #parse xml file root = objectify.fromstring(response) #print data print (response)

Answer rating: 100% (QA)

To obtain data from a URL examine its structure and generate Python code to retrieve specific information you can use libraries like requests and Beau... View the full answer