Prepare a large Excel spreadsheet
Select only the fields you need from thousands of spreadsheet records, edit values where necessary, and prepare a focused dataset.
Data Preparation Tool
Work with spreadsheet and structured data by selecting columns, editing cells, filtering records, sorting rows, calculating values, and preparing clean datasets for export.
Drop your data file here, or browse your device
Excel · CSV · JSON · up to 100 MB
Files are processed locally in your browser whenever supported.
Prepare the exact dataset you need without working through unnecessary rows and columns.
Select only the fields you need from thousands of spreadsheet records, edit values where necessary, and prepare a focused dataset.
Select student information, filter by class or attendance, sort records, calculate values, and prepare a focused gradebook.
Keep customer, invoice, amount, and due-date fields, then filter and sort the dataset to prepare the records you need.
Filter products by stock level, category, or supplier and prepare a focused inventory dataset for further work.
Select the columns you need, edit individual cells, remove unwanted rows, and organize the dataset before you export it.
Live example · Student Results
2,500 records · 5 fields — try selecting columns and filtering below.
Select columns
Filter: Marks < 40 (failing)
| Student Name | Class | Marks | Attendance | Result |
|---|---|---|---|---|
| Fatima Ali | 7A | 16 | 87 | Fail |
| Liam Hassan | 7A | 4 | 89 | Fail |
| Priya Wong | 6A | 12 | 95 | Fail |
| Chen Hassan | 6B | 19 | 61 | Fail |
| Noor Ibrahim | 6A | 31 | 80 | Fail |
Showing first 5 of 1,000 matching rows.
Work with large datasets, organize records, group related values, and calculate summaries from the data currently included in your view.
Choose specific columns and edit individual cells directly in the dataset.
Filter records using conditions and sort the current dataset by one or more columns.
Group records and calculate counts, sums, averages, minimums, and maximums.
Move from an original dataset to a focused, organized dataset in a few steps.
Upload an Excel, CSV, or JSON file.
DocBit identifies headers, columns, data types, and data quality.
Choose the columns you need and edit individual data values.
Filter rows, sort records, group data, and calculate values.
Review the prepared dataset and export it as Excel, CSV, or JSON.
Practical tools for preparing Excel, CSV, and JSON data for the next stage of your workflow.
Select columns, edit cells, filter records, sort rows, group data, and calculate values from the dataset you are working with.
Your preparation settings work as a separate view, allowing you to change the working dataset without overwriting the original uploaded data.
Supported processing is performed locally in your browser whenever the selected operation allows it.
Common questions about preparing spreadsheet and structured data. For a full walkthrough, see the Documentation.
DocBit currently supports Excel workbooks (.xlsx and .xls), CSV files, and JSON files.
You can select columns, edit cells, remove rows from the working dataset, filter records, sort data, group records, calculate values, and export the prepared dataset.
Yes. DocBit lets you work with supported Excel data by selecting columns, editing individual cells, filtering rows, sorting records, calculating values, and preparing the resulting dataset for export.
Yes. CSV files can be opened, reviewed, edited, filtered, sorted, calculated, and prepared for export.
Yes. Supported JSON datasets can be analyzed and prepared using the available column, editing, filtering, sorting, grouping, and calculation tools.
Supported processing is performed locally in your browser whenever the selected operation allows it. This allows supported data preparation operations to run without sending the dataset to a remote processing service.
Yes. Live cell edits can be undone and redone, and the dataset can be reset to its original uploaded state.
The current workflow supports Excel, CSV, and JSON exports.
Yes. Calculations run against the current filtered dataset, so totals, averages, counts, minimums, and maximums reflect the records currently included in the working dataset.