The Scenario
Your data team scraped 1,500 product pages last week and the raw HTML landed in the 'Raw HTML' column of an Excel workbook. Before you can run sentiment analysis or topic modeling, you need the 'Clean Text' column to contain readable plain text — no tags, no attributes, no script blocks from the page footer. The scraper ran on Friday. It's Monday. The analysis pipeline won't start without this column.
The bad version:
- Try a regex formula in Excel to strip HTML tags, realize it handles
<p>and<br>but not inline styles,&entities, or<script>blocks - Pull the workbook into Python with BeautifulSoup, get it working, run it, find that 200 rows with nested tables and JSON-LD structured data still have artifacts after extraction
- Manually clean the 200 problem rows, find that each one takes 4 minutes, do the math, accept that you're not finishing today
The analysis pipeline is waiting. You have 200 rows still dirty and a script that only solves 85% of the problem.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It uses Tisane's text extraction to strip markup reliably and write clean plain text into the destination column.
For all rows in my sheet, extract pure text from the 'Markup' column using Tisane and place results in 'Extracted Text' — skip any rows that are already plain text
What You Get
- The 'Extracted Text' column filled with readable plain text for all 1,500 rows
- HTML tags, inline styles, script blocks, and HTML entities (
&, ) are removed - Rows that are already plain text pass through unchanged — no double-processing
What If the Data Is Not Quite Ready
Some rows in the 'Raw HTML' column are empty or contain only whitespace
Extract plain text from the 'Raw HTML' column using Tisane — skip any row where the column is blank or contains only whitespace — write results into 'Clean Text'
The 'Clean Text' column already has partial results from a previous run
For rows where the 'Clean Text' column is empty, use Tisane to strip HTML from 'Raw HTML' and fill in the result — leave rows that already have a value in 'Clean Text' untouched
The scraped content is split across two worksheets: 'Electronics' and 'Apparel'
Strip HTML from the 'Raw HTML' column on both the 'Electronics' and 'Apparel' worksheets using Tisane and write the clean plain text into the 'Clean Text' column on each respective worksheet
Full pipeline: clean, then run sentiment analysis in one shot
Strip HTML from the 'Raw HTML' column using Tisane's text extraction, write the clean text into 'Clean Text', then run Tisane sentiment analysis on 'Clean Text' and write the sentiment label into a 'Sentiment' column — all in one pass
Extraction and analysis in a single instruction. No intermediate export, no intermediate step.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook with a column of raw HTML you need cleaned before analysis, then ask it to extract plain text across all rows. Once the column is clean, see bulk text analysis with Tisane to continue the pipeline. The full Tisane overview is at the hub.