Extract, Transform, and Load (ETL) tasks help in collecting and manipulating data from diverse sources to fit the user's requirements. In this course, you'll explore different interfaces available in the petl library and perform basic ETL tasks using petl. You will begin by examining how to import data from various data sources, including delimited text files, Microsoft Excel, and structured JSON data. You'll also recognize how to load and save data in these formats. Next, you'll outline how to integrate petl with a relational database using SQLAlchemy and SQLite3. Finally, you'll perform transform operations on data using different petl features to filter specific data needed by you. Once you have completed this course, you'll have a clear understanding of the role played by petl in simplifying ETL tasks.

Software development often requires manipulation of data that has been extracted from different data sources to make it compatible with the user's specifications and requirements. petl's data transformation features can help achieve this. In this course, you'll investigate fundamental data transformations that can be performed using the petl library. You'll demonstrate how to load data into a petl table, filter columns, and combine multiple tables using different forms of concatenation operations. Next, you'll outline how to convert data in a petl table into a form that is compatible with your requirements. This includes transforming strings to numbers, applying calculations to numeric fields, and replacing specific values in the table. Lastly, you'll explore ways to filter content in petl tables using the facet() function and different select operations.

Petl facilitates and streamlines tasks related to data extraction and manipulation, often required by software developers to make data fit for actionable business intelligence (BI). In this course, you'll work with complex operations in petl and outline how to extract data from a source and convert it to a format that complies with your requirements. You'll begin by investigating the use of regular expressions to analyze, search, and extract specific rows and columns in a petl table. You'll then create transform functions and apply them to your data. These include operations on numeric as well as string fields. Moving on, you'll implement sort operations to organize data in a petl table and arrange it in a sequence that suits your purposes. Finally, you'll investigate how to perform joins and set operations on data tables and meaningfully reduce the data in them using aggregation functions.