SkillSoft Explore Course – Lambers, Inc.

Aspire Pythonista to Python Master Python Master Track 3: Dynamic Data Handling with Python

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.

Asset ID	it_pyetlpdj_01_enus
Course Type	Video Course
Course Category	Pythonista to Python Master

Objectives
Operations with petl: Introduction discover the key concepts covered in this course install petl and create a basic petl table from a toy dataset import data from a CSV file and extract it to a petl table perform various import and export operations on CSV, TSV, and TXT files export data from petl using a template, epilogue, and prologue perform lookups on data imported from pickle files import data from XML files and perform lookups on it implement read operations on data and export it in HTML format read JSON data and perform lookup operations on it export data stored in petl data tables to a persistent file format import data from Microsoft Excel and perform basic operations on it view summary statistics of data in petl and export it to Microsoft Excel create a table in SQLite and import it to petl using SQLAlchemy and SQLite3 slice and dice data stored as records within a petl data table summarize the key concepts covered in this course

Objectives

Operations with petl: Introduction

discover the key concepts covered in this course
install petl and create a basic petl table from a toy dataset
import data from a CSV file and extract it to a petl table
perform various import and export operations on CSV, TSV, and TXT files
export data from petl using a template, epilogue, and prologue
perform lookups on data imported from pickle files
import data from XML files and perform lookups on it
implement read operations on data and export it in HTML format
read JSON data and perform lookup operations on it
export data stored in petl data tables to a persistent file format
import data from Microsoft Excel and perform basic operations on it
view summary statistics of data in petl and export it to Microsoft Excel
create a table in SQLite and import it to petl using SQLAlchemy and SQLite3
slice and dice data stored as records within a petl data table
summarize the key concepts covered in this course