FA-0748Data & AnalyticsAutomation, RPA & Power PlatformSoftware Development

Python for Excel Automation with xlwings

Workbook integration, data analysis, charts and Windows UDFs

Introduction

Why this course

Use local Python and xlwings to automate desktop Excel and build a small data-analysis tool. This intensive course combines Python foundations with pandas/NumPy examples, workbook read/write operations, charts and Windows user-defined functions.

The course teaches xlwings integration, not the separate Microsoft cloud-based Python in Excel feature. Selected automation and analysis patterns are practised over three days; it does not provide complete Python, VBA replacement or machine-learning coverage.

Learning outcomes

Write simple Python expressions, collections, conditions, loops and functions.
Use selected pandas/NumPy operations and plotting examples.
Connect to a workbook and exchange scalar, row/column and tabular data.
Run selected Python routines from Excel with xlwings integration.
Create/update plots or Excel charts in a workbook.
Implement a Windows UDF with appropriate argument/return conversions and arrays.
Build and test a small workbook automation/dashboard example, including a supplied permitted API-data input.

Prerequisites

Basic Excel and Windows file-system experience, plus elementary mathematics.
A compatible supported Windows environment with desktop Excel for the complete UDF track.
A compatible local Python/xlwings environment and approved permission to install/configure the selected dependencies/add-in; unrestricted administrator access is not inherently required.
Internet access where required for installation or the permitted API demonstration.

Training outline

3 modules

01Day 1 — Python Foundations and Data Analysis8 topics

Brief Python background, supported versions, local installation, IDEs, environment configuration and documentation.
Hello world and interactive/script programming modes.
Numbers, lists, tuples, dictionaries, sets, copying, strings and formatting; regular-expression overview.
Arithmetic, comparison, assignment, logical/membership operators and precedence.
if/else, for/while, break and continue.
Functions, parameters, documentation, collections, variable arguments and scope; map, filter and lambda awareness.
Introduce NumPy and pandas Series/DataFrames, missing data, grouping and selected merge/join/concatenation operations.
Common data operations, input/output and a supplied data-analysis exercise.

02Day 2 — Workbook Integration and Visualisation7 topics

Matplotlib, line/scatter plots and selected Seaborn/pandas time-series visualisations.
Connect xlwings to a workbook and read/write single values.
Named ranges, range shortcuts, rows/columns, one-/two-dimensional structures and vertical output.
expand, indexing/slicing and reducing unnecessary cell-by-cell calls.
Run main and RunPython; the minimal VBA bridge and how the approaches differ.
Insert/update a Matplotlib or Seaborn plot and control its size/position.
Create an Excel chart with Python; import a small permitted API response through a supplied routine.

03Day 3 — UDFs and Applied Workbook Tool7 topics

Windows UDF setup, approved Excel/add-in configuration and a first function.
Python module names/locations, UDF execution behaviour and troubleshooting.
Argument conversions with @xw.arg and suitable return options.
NumPy/pandas UDFs, array formulas and docstrings.
Use native Excel dynamic arrays where supported; compare legacy xlwings expansion and its overwrite risks without applying obsolete decorators unnecessarily.
Build a small case-study workbook with Python calculations, data output and a chart/dashboard view.
Assessment and review of results, limitations and further practice.

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