Tools in Data Science

BBC Weather location ID with Python#

You’ll learn how to get the location ID of any city from the BBC Weather API – as a precursor to scraping weather data – covering:

Understanding API Calls: Learn how backend API calls work when searching for a city on the BBC weather website.
Inspecting Web Interactions: Use the browser’s inspect element feature to track API calls and understand the network activity.
Extracting Location IDs: Identify and extract the location ID from the API response using Python.
Using Python Libraries: Import and use requests, json, and urlencode libraries to make API calls and process responses.
Constructing API URLs: Create structured API URLs dynamically with constant prefixes and query parameters using urlencode.
Building Functions: Develop a Python function that accepts a city name, constructs the API call, and returns the location ID.

To open the browser Developer Tools on Chrome, Edge, or Firefox, you can:

Here are links and references:

You’ll learn how to scrape the live weather data of a city from the BBC Weather API, covering:

Introduction to Web Scraping: Understand the basics of web scraping and its legality.
Libraries Overview: Learn the importance of requests and BeautifulSoup.
Fetching HTML: Use requests to fetch HTML content from a web page.
Parsing HTML: Utilize BeautifulSoup to parse and navigate the HTML content.
Identifying Data: Inspect HTML elements to locate specific data (e.g., high and low temperatures).
Extracting Data: Extract relevant data using BeautifulSoup’s find_all() function.
Data Cleanup: Clean extracted data to remove unwanted elements.
Post-Processing: Use regular expressions to split large strings into meaningful parts.
Data Structuring: Combine extracted data into a structured pandas DataFrame.
Handling Special Characters: Replace unwanted characters for better data manipulation.
Saving Data: Save the cleaned data into CSV and Excel formats.

Here are links and references: