Focusing on data manipulation operations, this course teaches how to perform data projection, filtering, and aggregation using Python without needing advanced external libraries. You will learn how to use both procedural and functional programming techniques when applying filtering and aggregation on the data stream.
Overview
Syllabus
- Lesson 1: Understanding Data Streams: Basics and Operations
- Add Stream Index Method
- DataStream Class Revision
- Add Method to Get DataStream Elements
- Enhance the DataStream Class with Slice String Conversion Method
- DataStream Class Slice to String Method
- Lesson 2: Implementing Data Filtering in Python
- Implement a DataFilter Method Threshold
- Filtering Out Strings Below a Certain Length
- Add a Method to Filter Even Numbers
- Filter Out Even Positive Numbers
- Filter Data Stream by a Custom Condition
- Lesson 3: Data Projection Techniques in Python
- Integrate Data Projection with Custom Attributes
- Enhancing the DataProjector Class Operations
- Add Horsepower Conversion to DataProjector
- Enhance DataProjector with Combined Filter and Map Operations
- Enhance Data Projection with Temperature Unit Conversion
- Lesson 4: Aggregation Methods for Summarizing Data Streams
- Aggregating Exam Scores
- Aggregating Data to Compute Standard Deviation
- Compute Average Temperature with a While Loop
- Aggregating Data to Find the Most Common Element
- Aggregating Adult Participants in a Group
- Lesson 5: Scenario-based Exercises for Data Manipulation
- Add Projection and Aggregation to Calculate Department Budget Share
- Add Method Chaining to Compute Average Sales in the Sales Department
- Add Specific Data Manipulation Methods to DataStream Class
- Calculating Sales Department's High Earners' Average Salary
