Learn how to set up a Python-based workflow that reads Jira export CSV files, cleans and enriches defect data, infers root causes, generates test suggestions, and outputs a formatted Excel workbook with data validation, dropdowns, and sensitive data masking, all configurable via YAML and JSON.
Learn how to create a modular Python script that batch processes Excel files—merging, cleaning, renaming, and more—using pandas and openpyxl, with a clear project structure and extensible design for real-world office automation.
Python in Excel lets Microsoft 365 users write and run Python code directly within spreadsheets, offering built-in libraries for data analysis, visualization, and machine learning, with cloud execution, seamless cell integration, step‑by‑step activation, sample code, library support, data import, troubleshooting, and practical tips.
This guide demonstrates how HR recruiters can use Python and libraries such as pandas and openpyxl to create, read, modify, and manage Excel candidate data, perform filtering, grouping, charting, and automatically send interview notification emails, thereby streamlining recruitment workflows.
This article introduces how to automate Excel chart generation using Python libraries like pandas and openpyxl, enabling efficient data visualization and analysis.
This article walks through using Python and pandas to batch‑process seven Excel evaluation sheets, skipping header rows, cleaning data, computing total and average scores per person, merging results, and outputting aggregated statistics, providing a practical automation solution for repetitive office tasks.
This article demonstrates how to use Python's openpyxl library to automatically insert named images into specific Excel cells in bulk, explaining the problem, providing a complete script, and offering practical tips for handling large files and sharing the solution with the community.
This article demonstrates how to replace tedious manual Excel reporting by using Python libraries pandas and xlwings to read multiple sheets, merge data, write the combined DataFrame back to Excel, and apply conditional formatting such as font colors, borders, and cell shading based on statistical thresholds.
This tutorial demonstrates how to split a master Excel rent ledger into per‑room Excel files, automatically adjust column widths and borders, capture each sheet as an image using xlwings and Pillow, and finally package the script into a standalone executable for distribution.
This article compares VBA and Python for Excel automation, explains why Python is called a glue language, introduces key Python packages like xlwings, demonstrates code examples for creating worksheets and charts, outlines xlwings features, and discusses its learning curve and recommended resources.
This guide walks you through installing openpyxl, opening and creating workbooks, accessing sheets and cells, iterating over ranges, modifying data, applying styles, and saving Excel files using Python, complete with code examples and visual illustrations.
This guide demonstrates how to use Python's xlwings library to programmatically create, rename, list, print, and split Excel workbooks and worksheets, enabling batch processing and automation that significantly improves efficiency for repetitive spreadsheet tasks.
This tutorial demonstrates how to use Python's xlwings library to programmatically create, save, list, rename, print, and split Excel workbooks and worksheets, providing practical code examples for automating common spreadsheet tasks and improving workflow efficiency.
This article walks you through automating daily loan reporting for a bank using Python and pandas, covering data loading, date filtering, table splitting, column renaming, concatenation, missing‑value handling, calculated fields, and pivot‑table generation to replace repetitive Excel tasks.
This tutorial shows how to use Python's openpyxl (and optionally glob) to extract rows with purchase counts over 50 from an Excel sheet, create a new workbook, and scale the solution to batch‑process a thousand similar files automatically.
This guide introduces the xlwings library for Python, covering installation, core concepts, and detailed code examples for opening Excel, reading and writing cells, managing workbooks, handling ranges, formatting, formulas, and colors, helping you automate Excel tasks efficiently.
Learn how to use Python's openpyxl and glob modules to automatically extract rows with purchase quantities over 50 from single or thousands of Excel files, create new workbooks, and merge results, with complete code examples for both basic and advanced scenarios.
Learn how to replace repetitive Excel payroll creation with a Python script that reads, copies, styles, and inserts rows, updates formulas, and outputs a ready-to-use payroll sheet, complete with full code examples and detailed explanations.
This article demonstrates how to use Python's pandas library to read CSV and XLS files, filter and merge data based on group assignments, compute derived columns, and export the results to a new Excel workbook, providing a complete automation workflow for Excel data processing.
This article presents a Python script for validating and cross-referencing data between Excel files, particularly useful for big data testing scenarios where developers need to verify filtered data accuracy.
