This tutorial demonstrates how to use Python libraries such as pandas, matplotlib, openpyxl, and python-docx to load, clean, analyze, visualize, and automatically generate Excel and Word reports from CSV data, complete with code examples for each step.
This tutorial shows how to use Python libraries such as pandas, python-docx, PyPDF2, and python-pptx to read, write, merge, and manipulate Excel, Word, PDF, and PowerPoint files, providing ready‑to‑run code snippets for each common automation scenario.
This article explains how to use Python's os module and python-docx library to recursively traverse a folder hierarchy, read .docx files, search for a specific keyword such as "nan", and output the names of matching documents, with optional performance tips.
This article introduces the python-docx library, explains how to install it, and provides a complete code example that demonstrates creating a Word document with headings, styled paragraphs, images, tables, and saving the file, helping Python developers automate document processing.
This article demonstrates how to use Python, pandas, and python‑docx to read sales data from Excel, compute necessary metrics, and automatically generate formatted Word daily‑report documents in bulk, turning a repetitive manual task into an efficient automated workflow.
This tutorial demonstrates how to install and use Python libraries such as xlrd, xlwt, xlutils, XlsxWriter, OpenPyXL, python-docx, and the csv module to read, write, modify, and format Excel, Word, and CSV files, including code examples and feature comparisons.
This article introduces the python-docx library, explains how to install it, and provides a comprehensive code example that demonstrates creating Word documents, adding headings, formatted text, images, tables, and saving the file, along with links to official documentation and GitHub resources.
The pdf2docx library uses PyMuPDF and python-docx to extract PDF layouts, paragraphs, images, and tables, offering multi‑process conversion while noting current limitations such as lack of OCR and support for only left‑to‑right languages, and provides simple pip installation and a code example.
This article explains how Python can boost office productivity by using libraries such as xlrd/xlwt, openpyxl, pandas for Excel, python‑docx for Word, and python‑pptx for PowerPoint, highlighting their ease of use and efficiency in handling large or repetitive documents.
This article introduces the python‑docx library, explains its document model—including Document, Paragraph, Run, and Table objects—and provides practical Python code examples for creating, modifying, and styling Word documents, inserting headings, page breaks, tables, and images.
This tutorial demonstrates how to use Python's Pillow library for image manipulation, openpyxl for Excel spreadsheet handling, and python-docx for creating and editing Word documents, providing code examples for common operations such as cropping, resizing, filtering, and data insertion.
This tutorial introduces Python libraries such as xlrd/xlwt/xlutils, python-docx, and the csv module, compares their features, shows how to install them, and provides complete code examples for reading, writing, and modifying Excel, Word, and CSV files.
This tutorial walks through setting up a Python environment, installing libraries, creating and editing Word documents with python-docx, converting files and generating PDFs using win32com, extracting Excel data with xlrd, visualizing scores with matplotlib, and automating batch document generation with docx-mailmerge.
This tutorial shows how to use Python's glob, python-docx, and openpyxl libraries to automatically scan a folder of Word meeting notices, pull out study time, content, format, and host information, and populate an Excel spreadsheet, saving hours of manual work.
This tutorial shows how to use Python's openpyxl and python-docx libraries to read company data from an Excel sheet, replace placeholder tags in a Word contract template, and automatically generate individualized contracts for each company in a batch process.
This article walks through using Python to read and process data from an Excel file, generate a structured filename, convert legacy .doc files to .docx, and automatically populate a Word document’s tables, providing a complete automation workflow for reporting tasks.
This article demonstrates how to use Python and the python‑docx library to read student scores from CSV files, generate appropriate evaluation comments, and programmatically insert those comments into each student's Word report, streamlining the grading workflow.
