Validate Arrow Files Online
Validate Arrow file structure in your browser. Check null counts, distinct values, and data types for every column — no upload required.
How to validate Arrow files
- Drop your file onto the upload area. The report starts as soon as the file has loaded. There are no settings.
- Read the four summary cards: total rows, columns, null-heavy columns and all-null columns.
- Scan the Column Report table for each column's detected type, null count, percentage of nulls and number of distinct values.
- Check the warnings under the table. Columns that are entirely null are flagged in red and columns that are more than half null in amber.
Your file is processed locally in your browser and is never uploaded. The free limit is 50 MB per file; larger files work if your device has the memory for them.
Worked example
A clinic exports a week of appointments before loading it into a reporting database. The analyst wants to know which fields are reliable before writing any queries.
Input (Arrow)
Arrow IPC file (binary, columnar) — shown as a table with its schema
| patient_ref | clinic | appointment_date | no_show | notes |
|---|---|---|---|---|
| P-104 | Eastside | 2026-06-02 | false | NULL |
| P-221 | Eastside | 2026-06-02 | true | Called to rebook |
| P-104 | Harbour | 2026-06-09 | false | NULL |
| P-318 | NULL | 2026-06-11 | false | NULL |
| P-450 | Harbour | 2026-06-11 | true | NULL |
Schema: patient_ref VARCHAR, clinic VARCHAR, appointment_date DATE, no_show BOOLEAN, notes VARCHAR
Settings
- No settings. The report is generated when the file loads.
Result
| Column | Type | Nulls | % Null | Distinct |
|---|---|---|---|---|
| patient_ref | VARCHAR | 0 | 0.0% | 4 |
| clinic | VARCHAR | 1 | 20.0% | 2 |
| appointment_date | DATE | 0 | 0.0% | 3 |
| no_show | BOOLEAN | 0 | 0.0% | 2 |
| notes | VARCHAR | 4 | 80.0% | 1 |
The summary cards read 5 rows, 5 columns, 1 null-heavy column and 0 all-null columns. notes is flagged in amber at 80% null. patient_ref has 4 distinct values in 5 rows, which shows P-104 appears twice, so it cannot be used as a unique key. Distinct counts ignore nulls, which is why clinic shows 2 rather than 3.
Frequently Asked Questions
Does Validate change or download my file?
No. It only produces the on-screen report. Nothing is modified and there is no download.
What counts as a null-heavy column?
Any column where more than 50% of values are null. The Null-heavy card counts all-null columns too, so a column that is 100% null is included in both cards.
Do distinct counts include nulls?
No. Distinct counts only non-null values. A column with values A, B and some nulls shows 2.
Related Tools
Fill Empty Values in CSV Files Online
Fill empty and null values in CSV files with a custom replacement value, directly in your browser.
Cast Column Types in CSV Files Online
Change column data types in CSV files directly in your browser. Cast text to numbers, dates to timestamps, or any supported type conversion — no upload required.
Manage Columns in CSV Files Online
Drop or select specific columns from CSV files directly in your browser. No upload required.
Validate CSV Files Online
Validate CSV file structure in your browser. Check null counts, distinct values, and data types for every column — no upload required.
Validate Excel Files Online
Validate Excel file structure in your browser. Check null counts, distinct values, and data types for every column — no upload required.
Validate Parquet Files Online
Validate Parquet file structure in your browser. Check null counts, distinct values, and data types for every column — no upload required.
Validate JSON Files Online
Validate JSON file structure in your browser. Check null counts, distinct values, and data types for every column — no upload required.
Arrow Viewer Online
View and inspect Arrow files directly in your browser. Browse rows, check column names and data types — no upload required, your data stays on your device.