Pivot & Unpivot 10M+ CSV Rows.
No Python. No Upload. No Wait.
Aggregate millions of rows with 12 aggregation functions. Melt wide columns into long format. Wildcard and regex column selection. 10M rows in 18 seconds — entirely in your browser.
The pivot table tool that actually works on your real-world data sizes.
Why Excel and Python Keep Failing You
Excel crashes above 1M rows
Excel's hard row limit is 1,048,576. Files larger than that simply cannot be opened. Pivot Tables crash or produce incorrect results near the limit on most hardware.
Python requires setup you don't have time for
pandas.pivot_table() is powerful but needs Python, pip, virtualenvs, and code. For a one-off pivot on a 2M row file, that's 30 minutes of setup before you even touch the data.
Cloud tools upload your sensitive data
Most online pivot tools require file upload — a compliance problem for PII, financial records, and HIPAA-covered data. SplitForge processes everything locally, in your browser.
Two Modes, One Tool
Pivot aggregates rows into summary statistics. Unpivot transforms wide columns into long-format rows. Both modes handle 10M+ rows in under 20 seconds.
How to Pivot a CSV File — Step by Step
Pivoting a CSV means grouping rows by one or more key columns and computing summary statistics per group — the same operation as SQL GROUP BY or Excel Pivot Tables, but with no row limit and no upload. For a deep technical walkthrough, see SQL-style GROUP BY on CSV and pivoting 2M rows without Python.
What Makes This Different from Excel
Six capabilities Excel and Google Sheets don't have.
12 Aggregation Functions
SUM, COUNT, AVG, MIN, MAX, Count Distinct, Weighted Average, % of Total, StdDev, Variance, Median, and Mode. The last two are marked as high-memory and gated behind an explicit toggle with cardinality warnings.
Wildcard + Regex Column Selection
Select unpivot columns with patterns: Q* selects Q1, Q2, Q3, Q4. ^Revenue_[0-9]+ selects revenue columns by regex. Pattern-matching column selection is essential for budget files with 30+ monthly columns.
3-Level Hierarchical Pivoting
Pivot by Region → Category → Product in a single pass. Drag-drop level reordering in the UI. Output includes all three group columns plus your selected aggregations. No re-running required to change level order.
Save & Share Configurations
Save up to 20 named configurations (group-by columns, aggregations, output format). Export as JSON and share with teammates. Import someone else's config in one click. Works across sessions.
Native XLSX Support with Sheet Selector
Drop an Excel workbook directly. Choose which sheet to pivot or unpivot from a visual sheet selector. No CSV export step required. Handles .xlsx and legacy .xls.
Streaming Web Worker Architecture
Processing runs in a dedicated Web Worker — the browser tab stays fully responsive at 10M rows. PapaParse streaming parser reads data in 50K-row chunks. UI shows live progress: rows processed, throughput, estimated time remaining.
Tool Comparison
Where SplitForge fits vs Excel, Google Sheets, and Python.
| Tool | Row Limit | Aggregations | Unpivot | Pattern Cols | Privacy | Cost |
|---|---|---|---|---|---|---|
| Excel Pivot Table | 1,048,576 rows max | 6 basic + Power Pivot | Power Query only | Local file | $160/yr (M365) | |
| Google Sheets | 10M cells, ~500K rows | 5 basic | Manual formula or script | ⚠️ Uploaded to Google | Free / $6/mo | |
| Python pandas | RAM-limited (64GB+) | Unlimited (code) | pd.melt() | Code only | Local (depends) | Free (setup time $$) |
| SplitForge← You are here | ~10M rows (browser) | 12 functions | Built-in, with patterns | 100% local | Free |
Who Uses This and Why
Real-world tasks where SplitForge replaces a Python script or a crashed Excel session.
Monthly Sales Reporting
2M row transaction CSV. Need revenue by Region × Product Category for board report. Excel crashes on open.
Drop CSV, group by Region and Category, select SUM(Revenue) + COUNT. Download summary in 36 seconds.
Budget Variance Analysis
Finance export has one column per month (Jan_2021 through Dec_2026) — 72 columns. Need long format for Power BI import.
Wildcard pattern Jan_*, Feb_*, ... selects all month columns. Unpivot to Month/Value in 8 seconds.
Healthcare Quality Metrics
3.5M patient encounter rows. Need AVG readmission rate by Department × Provider, but can't upload to any cloud tool.
100% local processing — zero HIPAA exposure. Pivot with AVG aggregation. Done in 64 seconds.
E-commerce Inventory Reshape
Supplier inventory export: one row per SKU, one column per warehouse location (50 warehouses). ETL expects long format.
Regex pattern ^WH_[A-Z]{3}$ selects all 50 warehouse columns. Unpivot to SKU/Warehouse/Qty rows.
Financial GL Rollup
General ledger CSV: 800K journal entries. Need SUM and COUNT by Account Code × Cost Center × Period. pandas script keeps crashing on 16GB laptop.
3-level hierarchical pivot. SUM + COUNT. 15-second processing time on 800K rows.
Survey Data Normalization
Survey export: one row per respondent, one column per question (Q1 through Q48). Need long format for statistical analysis.
Pattern Q* selects all 48 question columns. Unpivot to Respondent/Question/Answer in 4 seconds.
Technical Capabilities
What's under the hood — for people who need to know.
Wildcard & Regex Column Pattern Matching
Select dozens of unpivot columns with a single pattern. Q* matches Q1, Q2, Q3. ^Revenue_[0-9]+ matches by regex.
12 Aggregation Functions with Memory Model Transparency
10 memory-safe aggregations + Median and Mode (with explicit memory warnings and 50K value/group cap).
3-Level Hierarchical Pivoting
Group by up to 3 columns simultaneously. Drag-drop to reorder levels. Output includes all group columns.
Save & Export Configurations (JSON)
Store up to 20 named configs in localStorage. Export as JSON for version control or team sharing.
Streaming Web Worker — 50K Row Chunks
PapaParse streams input in 50K-row chunks. Worker emits progress events. UI never blocks.
Perfect For
Not Designed For
Who Uses SplitForge Pivot & Unpivot
Business Analysts
Produce weekly or monthly summary reports from large transaction CSVs without Excel row limits or Python setup. Save configurations for recurring reports.
Data Engineers
Quickly validate pivot logic on sample datasets before building a production pandas or SQL pipeline. Faster than writing and debugging a script for a one-off check.
Compliance Teams
Process PII-containing datasets that cannot leave the local machine. 100% browser-based — no upload, no third-party server, no data residency concern.
Time Savings Calculator
Estimate how much time and money you recover by replacing manual Excel Pivot Table workflows.
Weekly reporting = 4/mo
Year-round reporting = 12
Analyst average: $45–75/hr
10M Row Pivot in 18 Seconds
Throughput verified on Chrome 132, Intel i5-12600KF, 64GB RAM, February 2026. Full methodology and aggregation overhead breakdown at the performance page.
Pivot operation: 3 group-by columns, SUM + COUNT + AVG, CSV output.
Unpivot operation: 2 ID columns, 48 value columns, CSV output.
Variance: ±15–20% by hardware, browser, aggregation, file complexity.
Frequently Asked Questions
What's the difference between pivot and unpivot?
How many rows can I process?
Does my data get uploaded anywhere?
Can I use regex to select columns for unpivot?
What aggregation functions are available?
Can I save my pivot configuration?
How does this compare to Python pandas?
Does it work with Excel files?
What output formats are supported?
Related Guides & Deep Dives
Ready to Pivot or Unpivot Your Data?
Drop a CSV or Excel file. Configure in 30 seconds. Download your result. File contents never leave your browser.
Also try: Aggregate & Group By · VLOOKUP Join · Data Profiler · CSV Splitter