An export lands in your downloads folder, you double-click it, and Excel shows a dialog about the file not being loaded completely. You click through it because you are in a hurry, and now you are looking at a spreadsheet that appears perfectly normal and is missing an unknown number of rows.
This is the most expensive failure mode in spreadsheet work, because it does not look like a failure. The file opens. The columns are right. The totals are simply wrong, and nothing on screen says so.
An Excel worksheet holds 1,048,576 rows and 16,384 columns. That is 220 rows — a structural property of the file format introduced in 2007, not a setting, not a licensing tier, and not something a newer version raises. Excel 365 has the same limit as Excel 2007.
The limit is per worksheet. A workbook can hold many sheets, which is why splitting a large export across sheets works while cramming it into one does not.
When a CSV has more rows than that, Excel loads the first 1,048,576 and stops. It tells you once, in a dialog, and then never mentions it again.
How to check whether you lost rows. Count the lines in the file without opening it in a spreadsheet.
Windows PowerShell: (Get-Content file.csv | Measure-Object -Line).Lines
macOS or Linux: wc -l file.csv
Subtract one for the header, then compare with what Excel shows. If Excel's last row is exactly 1,048,576, treat the file as truncated until you prove otherwise — landing on that number by coincidence is vanishingly unlikely.
Even when the row count fits, a large CSV is the case where Excel's import conversions do the most damage, because nobody scrolls through 900,000 rows to notice. Leading zeros disappear from account codes, long numeric identifiers become 1.23457E+14, and anything that resembles a date gets rewritten into one. On a small file you catch it. On a large one you ship it.
That is a separate problem with its own fixes, covered in why Excel ruins CSV files. It is worth reading before you decide that opening the file in Excel is the goal at all.
| Approach | Good for | The catch |
|---|---|---|
| Split the file into parts | You need Excel specifically, and the work is per-row | Cross-file totals have to be added up by hand |
| Open it somewhere with no row limit | Reading, filtering, summarising, charting | Bounded by your machine's memory instead |
| Excel's Power Query / Data Model | Aggregates over the whole file inside Excel | You can summarise more rows than you can display, but it is a different tool with its own learning curve |
| A database or command-line tools | Tens of millions of rows, repeated work | Setup, and a skill set not everyone has |
If the destination really has to be Excel — a template someone else built, a process you do not control — then split the export and work in parts. Split by row count to get even pieces, or by the value of a column to get one file per region, per month or per client, which is usually more useful because each part is then a coherent unit rather than an arbitrary slice.
Split a CSV does both, in the browser, without uploading the file.
A browser imposes no fixed row ceiling. What bounds it is memory: the whole file is held at once, so the practical limit is your machine rather than a number in a specification. On an ordinary laptop a few hundred thousand rows are comfortable, which covers the overwhelming majority of exports that break Excel's limit — most of them are between one and three million rows, not a hundred million.
This is worth being precise about, because the honest answer is not "unlimited":
awk. Anything that holds the file in memory will struggle, and that includes Excel.Excel can summarise more rows than it can display. Loading a CSV through Data → Get Data → From Text/CSV and choosing Only Create Connection with Add this data to the Data Model keeps the rows out of the worksheet grid and lets a PivotTable aggregate over all of them. It is genuinely capable and genuinely unintuitive; if you do this monthly it is worth the afternoon, and if you do it once it is not.
Step back from "open the file" and ask what the file is for. Most of the time the goal is not to look at 1.4 million rows — nobody reads 1.4 million rows — but to answer something about them: which categories carry the total, whether last month broke the pattern, how many rows are duplicates, which columns are half empty.
Those are summary questions, and a summary does not require the grid. It requires something that can read every row once and give you the aggregate. That is why the row limit, which feels like the whole problem while you are staring at the dialog, is usually not the problem at all.
Each is a single page with no account and no server behind it. Open developer tools, watch the Network tab, and drop a file in: nothing goes out.
Excel stops at 1,048,576 rows, warns you once in a dialog that is easy to click past, and then shows you a file that looks complete. Count the lines before you trust a total. If the file is bigger than the limit, either split it into parts that Excel can hold, or summarise it somewhere that has no grid to fill — and if it runs to tens of millions of rows, stop trying to open it at all and query it instead.
Why Excel ruins CSV files — and how to stop it: the damage that happens to the rows Excel does load.
How to analyze a CSV without uploading it anywhere: why the upload step most online tools require is unnecessary, and how to verify a page is not doing it.
How to combine multiple CSV files into one: the merge that usually produces the oversized file in the first place.
How to find duplicates in a spreadsheet: large exports built from joins are full of them.
Sheet Insights reads an Excel or CSV file in your browser and builds the summary straight away — totals by category, trends over time, column statistics, outliers, data-quality checks and a repeatable clean-up recipe for the columns that always come in dirty. No row limit, no account, no upload. The free version opens two files of your own and shows all of it; saving the cleaned file, the report or the JSON back out is what the Windows app does.
Open it and drop a file in