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Advanced Data Transformation with Python and Pandas Training Course

Rating

9/10

Duration

3 Days

Course Overview

This advanced course is designed to teach participants the techniques and tools required to perform complex data transformations using Python and Pandas. Participants will learn to reshape, aggregate, and manipulate large datasets efficiently, enabling them to prepare data for analysis or machine learning workflows. With a focus on hands-on exercises, this course is ideal for professionals who already have a basic understanding of Python and Pandas and wish to deepen their knowledge.

Format of Training

  • Instructor-led sessions with in-depth explanations
  • Hands-on lab exercises using real-world datasets
  • Group activities for collaborative problem-solving
  • Practical use cases to demonstrate advanced techniques

Course Objectives

  1. Understand advanced data manipulation techniques using Pandas.
  2. Perform complex reshaping and pivoting operations on datasets.
  3. Utilize advanced filtering, slicing, and indexing methods.
  4. Apply custom functions and transformations using apply and map.
  5. Leverage aggregation and group-by operations for summarizing data.
  6. Handle and process large datasets efficiently.
  7. Develop reusable workflows for advanced data transformation tasks.

Prerequisites

  • Basic knowledge of Python programming
  • Familiarity with Pandas library fundamentals
  • Experience with basic data manipulation tasks
  • Comfortable working with Jupyter Notebooks or similar tools
Course Outline

Day 1
Session 1: Review of Python and Pandas Fundamentals

  • Overview of Pandas data structures (Series, DataFrame)
  • Basic data manipulation techniques (filtering, slicing, and indexing)
  • Hands-on lab: Quick recap of Pandas basics

Session 2: Advanced Data Reshaping Techniques

  • Reshaping data using melt, pivot, and pivot_table
  • Stacking and unstacking data
  • Hands-on lab: Reshaping a complex dataset

Session 3: Working with Hierarchical Indexing

  • Multi-level indexing and slicing
  • Aggregating data with hierarchical indexes
  • Hands-on lab: Handling multi-indexed data

Day 2
Session 1: Advanced Grouping and Aggregation

  • Custom aggregation functions using groupby
  • Performing multiple aggregations simultaneously
  • Hands-on lab: Summarizing large datasets

Session 2: Advanced Data Filtering and Transformation

  • Filtering rows and columns with complex conditions
  • Transforming data using apply, map, and lambda functions
  • Hands-on lab: Applying transformations to datasets

Session 3: Handling Missing and Duplicate Data

  • Advanced techniques for filling missing data
  • Strategies for identifying and removing duplicates
  • Hands-on lab: Cleaning large datasets with Pandas

Day 3
Session 1: Optimizing Performance with Pandas

  • Techniques for handling large datasets (chunking, memory optimization)
  • Efficient merging and joining of large datasets
  • Hands-on lab: Optimizing workflows for large datasets

Session 2: Case Study: Advanced Data Transformation Workflow

  • Analyzing and transforming a real-world dataset
  • Applying advanced techniques learned throughout the course
  • Group activity: Collaborative dataset transformation

Session 3: Automating Data Transformation Tasks

  • Writing reusable and efficient data transformation scripts
  • Using Pandas alongside other libraries for automation
  • Hands-on lab: Building an automated data transformation pipeline

Bespoke Option

We are open to customizing this program to align with your specific learning objectives. If your team has particular goals or areas they wish to focus on, we would be happy to tailor the course outline to meet those needs and ensure the program supports the achievement of your desired outcomes.

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Advanced Data Transformation with Python and Pandas Training Course

Course Name: Advanced Data Transformation with Python and Pandas Training Course

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