Programming in Python Training Course

Module 1: Using Pandas functions for data frame operations

• Introduction to Pandas
  • Basic data structures: Series and DataFrame
• DataFrame operations
  • Reading and writing data (CSV, Excel, etc.)
  • Basic operations (selection, filtering, indexing)
• Data modification
  • Adding, removing columns and rows
  • Modifying values in a DataFrame
• Data aggregation and grouping
  • GroupBy
  • Aggregation, summing, means, etc.
• Joining and merging DataFrames
  • merge, join, concat
• Handling missing data
  • Identifying missing data
  • Methods for imputing missing data

Module 2: Optimising program execution time

• Introduction to optimisation
  • The importance of optimisation in programming
• Code optimisation
  • Efficient data structures
  • Avoiding redundant calculations
  • Loop optimisation
• Pandas optimisation
  • Vectorising operations
  • Avoiding apply and lambda
  • Working with large datasets
• Simplifying code through function creation
  • Creating and using functions
  • Code refactoring

Module 3: Working with the NumPy library

• Introduction to NumPy
  • Importing the library
  • Basic data structures: ndarray
• Array operations
  • Creating and modifying arrays
  • Array indexing and slicing
• Mathematical and statistical functions
  • Basic mathematical operations
  • Statistical and aggregate functions
• Linear algebra
  • Matrix multiplication
  • Determinant, inverse matrix
• Working with multidimensional data
  • 2D, 3D, and higher-dimensional arrays
  • Array shape transformations
• Integration with other libraries

Module 4: Creating charts in Excel using Python

• Introduction to openpyxl and xlsxwriter
• Creating charts in Excel
  • Creating simple charts (line, bar, etc.)
  • Chart formatting
• Generating charts as images (PNG)
  • Using matplotlib to generate charts
  • Saving charts as PNG files
• Advanced charts in Excel
• Report automation
  • Creating automated reports with charts
  • Integrating Pandas with openpyxl/xlsxwriter