Operations with petl: Basic Data Transformations


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description
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.

Expected Duration (hours)
1.6

Lesson Objectives

Operations with petl: Basic Data Transformations

  • discover the key concepts covered in this course
  • create a petl data table from Python-based data structures, such as NumPy arrays and Pandas DataFrames
  • perform slicing, dicing, and merging operations on petl data tables
  • combine data from multiple tables into one table
  • insert as well as edit rows and columns in petl data tables
  • perform various replace and type change operations on data
  • find and replace specific values in a field
  • implement SQL-like query operations on petl data tables
  • filter data based on single as well as a combination of conditions
  • use petl's facet() function to define filters for specific fields in a table
  • summarize the key concepts covered in this course
  • Course Number:
    it_pyetlpdj_02_enus

    Expertise Level
    Beginner