How to Split a Large Excel File Into Multiple Smaller Files

Your Excel file is 180 MB, your colleague's email server bounces anything over 10 MB, and the CRM you're importing into has a 25 MB limit. You need smaller files — and you need them now, without learning VBA or waiting for IT. Here are the methods that actually work.

Why Excel files get large (and why that matters for splitting)

An XLSX file is heavier than the equivalent CSV for a few reasons: each cell stores not just data but formatting, formulas, number formats, and sometimes embedded charts or images. A sheet with 500,000 rows of plain text data might be 40 MB as XLSX and 12 MB as CSV. This matters because when you're splitting for a size limit, the output format choice affects how many chunks you get.

The other thing to understand: Excel's row limit is 1,048,576 rows per sheet. If you're regularly hitting file size limits, you're probably also approaching row limits — which is one of several reasons professional data teams move large datasets out of Excel entirely.

But you don't need to change your entire workflow to solve today's problem. You just need smaller files.

Method 1: Split in your browser (fastest, no install)

CSV Splitter Online reads XLSX files natively and splits them by file size, row count, number of files, or column value. Your data never leaves your computer — it all runs in JavaScript in your browser tab. This is the fastest path for a one-off split.

Method 2: Split by column value (one file per category)

If your Excel file contains a mix of records that belong to different categories — different regions, different departments, different product types — you can split by the value in a column rather than by size. Every unique value gets its own output file.

Use the "By column value" mode in CSV Splitter Online. Select the column you want to group by — say "Region" — and you'll get files named data_Region_North.csv, data_Region_South.csv, and so on. This is more useful than arbitrary size-based splitting for cases where the files will be sent to different people or uploaded to different accounts.

Method 3: The manual Excel approach

Excel doesn't have a native "split into multiple files" feature, but you can do it manually when you only have two or three chunks to create and don't want to install anything.

1. Open your Excel file and note the total row count (shown in the status bar when you select all)
2. Decide your cutoff point — rows 1–50,000 go in file 1, rows 50,001–100,000 in file 2
3. Select rows 50,001 through the last row, copy them
4. Open a new workbook, paste into row 1
5. Copy the header row from the original, paste as row 1 in the new workbook (shifting everything down)
6. Save the new workbook as XLSX or CSV
7. Back in the original, delete the rows you moved out, save

Method 4: Python (for large-scale or automated splitting)

If you're splitting Excel files regularly or dealing with files that have millions of rows, a Python script with pandas is the right long-term tool. It's fast, reproducible, and handles files that would crash Excel.

import pandas as pd

    # Read the Excel file (first sheet)
    df = pd.read_excel('large_file.xlsx')

    chunk_size = 50000
    for i, start in enumerate(range(0, len(df), chunk_size)):
    chunk = df.iloc[start:start + chunk_size]
    chunk.to_csv(f'output_part{i+1:02d}.csv', index=False)
    print(f'Part {i+1}: {len(chunk)} rows')

To split by column value instead:

import pandas as pd

    df = pd.read_excel('large_file.xlsx')

    for region, group in df.groupby('Region'):
    safe_name = str(region).replace('/', '_').replace(' ', '_')
    group.to_csv(f'data_{safe_name}.csv', index=False)
    print(f'{region}: {len(group)} rows')

Splitting multi-sheet Excel workbooks

If your workbook has multiple sheets and you want each as a separate file — common when exporting monthly reports or regional data into one workbook — here's the Python approach:

import pandas as pd

    xl = pd.ExcelFile('workbook.xlsx')
    for sheet_name in xl.sheet_names:
    df = xl.parse(sheet_name)
    safe = sheet_name.replace('/', '_').replace(' ', '_')
    df.to_csv(f'{safe}.csv', index=False)
    print(f'Exported: {sheet_name} — {len(df)} rows')

In Excel manually: right-click a sheet tab → "Move or Copy" → tick "Create a copy" → choose "(new book)". Repeat for each sheet. Workable for 3–4 sheets, not practical beyond that.

Choosing output format: CSV vs XLSX after splitting

The most common mistake: splitting a 100 MB XLSX into 4 × 25 MB XLSX chunks when CSV output would produce 2 × 18 MB files. Always check whether your destination actually requires XLSX before committing to it as the output format.

Verifying your split files before uploading

Before uploading anything, spend two minutes checking your split files are correct:

• Open each chunk in CSV Splitter Online and verify the row counts sum to the original total
• Confirm each chunk has the header row and it matches the original
• Check that the last row of chunk 1 and the first row of chunk 2 are adjacent records, not duplicates or gaps
• Verify the actual file sizes on disk are under your upload limit (not just what CSV Splitter Online estimated)