Programming in Python Training Course

Module 1: Pandas Functions for Data Frame Operations

• Introduction to Pandas
  • Foundational data structures: Series and DataFrame
• Managing DataFrame Content
  • Data ingestion and export protocols (CSV, Excel, etc.)
  • Core manipulation techniques (selection, filtering, indexing)
• Data Modification Procedures
  • Inserting and deleting columns and rows
  • Updating values within DataFrames
• Data Aggregation and Grouping
  • GroupBy functionality
  • Calculating aggregates, sums, and averages
• Combining and Merging DataFrames
  • Utilization of merge, join, and concat methods
• Handling Missing Data
  • Detection of data gaps
  • Strategies for imputation and filling missing values

Module 2: Code Optimization

• Overview of Optimization Principles
  • The significance of optimization in computational tasks
• General Code Optimization Strategies
  • Selection of efficient data structures
  • Minimizing redundant calculations
  • Loop efficiency improvements
• Pandas-Specific Optimization
  • Vectorized operations
  • Reduction of apply and lambda usage
  • Management of large-scale datasets
• Simplification through Functional Abstraction
  • Development and implementation of functions
  • Code refactoring for maintainability

Module 3: Utilizing the NumPy Library

• Introduction to NumPy
  • Library importation and setup
  • Core data structure: ndarray
• Array Manipulation
  • Array creation and modification
  • Indexing and slicing techniques
• Mathematical and Statistical Operations
  • Elemental mathematical functions
  • Statistical and aggregation computations
• Linear Algebra Applications
  • Matrix multiplication
  • Determinant and inverse matrix calculations
• Multidimensional Data Management
  • 2D, 3D, and higher-dimensional array handling
  • Reshaping array structures
• Integration with Third-Party Libraries

Module 4: Generating Charts in Excel via Python

• Overview of openpyxl and xlsxwriter
• Chart Creation in Excel Environments
  • Construction of basic charts (line, bar, etc.)
  • Chart styling and formatting
• Image-Based Chart Generation (PNG)
  • Utilizing matplotlib for visualization
  • Exporting charts as PNG files
• Advanced Excel Charting Techniques
• Report Automation
  • Generation of automated reports with embedded charts
  • Integration of Pandas with openpyxl and xlsxwriter