Course Content
Automating Data Collection from Web Sources
Store Scraped Data Into a Pandas DataFrame
Storing scraped data in a pandas DataFrame is a convenient way to manipulate and work with the data. pandas is a powerful library in Python that provides easy-to-use data structures and data analysis tools.
A DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it as a spreadsheet, SQL table, or a dictionary of Series objects. It is generally the most commonly used pandas object.
Task
- Import
pandasand initialize an empty DF; - Scrape the country name (find all instances on the web page);
- Scrape the capital city (find all instances on the web page);
- Append the scraped values (
country_name,item) in thedf.
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Storing scraped data in a pandas DataFrame is a convenient way to manipulate and work with the data. pandas is a powerful library in Python that provides easy-to-use data structures and data analysis tools.
A DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it as a spreadsheet, SQL table, or a dictionary of Series objects. It is generally the most commonly used pandas object.
Task
- Import
pandasand initialize an empty DF; - Scrape the country name (find all instances on the web page);
- Scrape the capital city (find all instances on the web page);
- Append the scraped values (
country_name,item) in thedf.
Switch to desktop for real-world practiceContinue from where you are using one of the options below