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Processing a 1 GB CSV file
Excel
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Crashes / OOM
ChatGPT
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File too large
dataprep.dev
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Toolkit Highlights
CSV Merger
Drag in 50 CSV files with mismatched columns and merge them into one unified table.
Open toolJSON ↔ CSV Converter
Flatten deeply nested JSON arrays into a clean CSV with dot-notation column names.
Open toolShopify Order Normalizer
Collapse Shopify's multi-line order export into one row per order with aggregated totals.
Open toolLocal VLOOKUP (Joiner)
Join two large CSV files on a shared key column instantly without Excel freezing.
Open toolReal-world Cleaning SOPs
How to Merge 50 Shopify Order CSVs Into One File Without Crashing Excel
Shopify caps order exports at ~10,000 rows per file via the Admin UI. The Admin API paginates at 250 orders per request (limit=250). A store pushing 500 orders/day accumulates 45,000 rows monthly—requiring 6+ separate exports that drift in schema as Shopify silently renames columns (e.g., 'Billing Country' → 'Billing Country Code' in 2024-Q3). Paste a few months of high-volume store data into Excel, cross 150K rows with 34+ columns, and watch it freeze due to 32-bit COM interop memory allocation. This workflow merges dozens of fragmented CSVs, deduplicates by Order ID using the 'Updated at' timestamp as tiebreaker, and realigns shifted columns. The output is a clean, flat table compliant with RFC 4180 quoting rules, ready for Triple Whale ingestion, Pivot Tables, or LTV/ROAS analysis.
Read workflowNormalize Shopify Multi-Line Order Exports for Accurate Profit Calculation
When a customer buys three products, Shopify's CSV creates three rows—but only populates shipping, discounts, and tax on the first (parent) row. The second and third (child) rows leave these financial fields completely blank. If you sort this export in Excel by SKU, the child rows detach from their parent order's shipping cost, making order-level gross profit calculation impossible. This workflow groups rows by Order Name (e.g., #1042), forward-fills shipping and discount fields to all child rows, then pivots the data to preserve the single-row-per-order structure required by QuickBooks and Xero.
Read workflowMerge Date-Range-Limited Shopify Exports Into One Master File
High-volume Shopify stores must pull data in monthly chunks due to the Admin UI's ~10,000 row export limit. But an order placed at 11:58 PM on March 31st that gets fulfilled after midnight will appear in both the March and April exports with different Fulfillment Status values ('unfulfilled' vs 'fulfilled'). Simply concatenating these files creates duplicate orders that inflate revenue. This workflow merges dozens of CSVs sequentially, identifies overlaps via the Name column, and keeps only the most recent version based on the 'Updated at' timestamp. It also flags schema drift if Shopify silently added or renamed fields between your January and June exports.
Read workflowTest with Dummy Data
Shopify Order Export Sample CSV (Dirty + Clean)
A production-realistic Shopify order export (200 rows) covering the exact scenarios that break data pipelines: multi-line items (one order → multiple rows), partial refunds, mixed fulfillment statuses, and discount code stacking. The 'dirty' version contains trailing whitespace on emails, HTML entities (&) in Lineitem name, and timezone-naive Created at timestamps that shift order dates by ±12 hours during UTC conversion. The 'clean' version normalizes all fields to warehouse-ready format. Perfect for testing ShipStation ERP imports, QuickBooks reconciliation, or Shopify API mock data. All processing happens locally in your browser — your order data never leaves your machine.
View datasetAmazon FBA Settlement Report Sample TSV (Dirty + Clean)
A representative Amazon Seller Central settlement report (150 transactions, TSV format) covering all critical row types: Orders, Refunds, FBA Fees, Adjustments, and Transfers. The 'dirty' version includes Transfer rows (which cause double-counting if not filtered), TSV tab delimiters that Excel silently converts to spaces, and amount-description values with embedded commas that break re-parsing. The 'clean' version collapses to a profit summary ready for QuickBooks import. Ideal for auditing FBA fees or testing automated profit calculation scripts without exposing actual store revenue. All processing runs locally — your financial data never touches a server.
View dataset