Evaluating .docx processing
Okay, so I'll assume that python-docx is available and can read .docx files. If it's not, I’ll handle it gracefully and fall back to reading the binary. I'll extract text, headings, and tables, and compute the budget summary with numeric extraction. For the budget doc, I’ll parse tables into DataFrames and calculate totals, then summarize key points like total budget and main cost drivers.
Processing document and summarizing budget
I'll first focus on reading the .docx file, extracting any tables into DataFrames, and capturing text with headings and paragraphs. Since heading levels aren't easy to get, I'll detect them by styles that include 'Heading' or 'Title'. Then I'll search for relevant numeric columns like 'Total', 'Cost', 'Amount', and summarize the findings. Finally, I’ll display the DataFrames and save the tables to an Excel file for easy download.
Cleaning numeric data and summarizing doc
I’ll clean the numeric data by removing non-numeric characters, handling spaces, and managing commas for thousands/decimal. The function will replace unwanted symbols and decide which separators to keep. I’ll compute totals for relevant columns and provide a concise document summary with titles, headings, and one paragraph under each heading, along with the tables.
Thought for 20s