Programming in Python Training Course

Module 1: Pandas functions in DataFrame work

• Introduction to Pandas
  • Basic data structures: Series and DataFrame
• Operations on DataFrame
  • Loading and saving data (CSV, Excel, etc.)
  • Basic operations (selection, filtering, indexing)
• Modifying data
  • Adding and removing columns and rows
  • Modifying values in a DataFrame
• Data aggregation and grouping
  • GroupBy
  • Aggregation, summing, averaging, etc.
• Combining and merging DataFrames
  • merge, join, concat
• Working with missing data
  • Identifying missing data
  • Methods for filling missing data

Module 2: Optimising program runtime

• Introduction to optimisation
  • The importance of optimisation in programming
• Code optimisation
  • Efficient data structures
  • Avoiding redundant calculations
  • Optimising loops
• Pandas optimisation
  • Vectorisation of 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
  • Indexing and slicing arrays
• Mathematical and statistical functions
  • Basic mathematical operations
  • Statistical and aggregation 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.)
  • Formatting charts
• Generating charts as images (PNG)
  • Using matplotlib for chart generation
  • Saving charts as PNG files
• Advanced Excel charts
• Report automation
  • Creating automated reports with charts
  • Integrating Pandas with openpyxl/xlsxwriter