CSV Tools

Sample Feather File

A downloadable sample Feather (Arrow IPC) file with 30 fictional employee records, deliberately uncompressed so every reader — including browser tools — can open it.

Data Feather Binary format
Download Feather

sample-employees.feather

Data Preview

30 rows × 7 columns
1nameemaildepartmentrolesalarystart_dateoffice
2Marcus Chenmarcus.chen@example.comEngineeringSenior Software Engineer1550002019-03-15San Francisco
3Priya Sharmapriya.sharma@example.comEngineeringStaff Engineer1780002019-06-01San Francisco
4David Kimdavid.kim@example.comEngineeringSoftware Engineer1250002021-01-10New York
5Rachel Torresrachel.torres@example.comEngineeringEngineering Manager1680002020-02-20San Francisco
6James Okaforjames.okafor@example.comEngineeringJunior Developer920002024-06-15Austin
7Lena Vogtlena.vogt@example.comEngineeringDevOps Engineer1400002022-04-01New York
8Amir Patelamir.patel@example.comEngineeringBackend Engineer1320002023-01-09London
9Sofia Lindbergsofia.lindberg@example.comDesignLead Designer1450002019-09-12New York
10Carlos Riveracarlos.rivera@example.comDesignUX Designer1120002021-07-20San Francisco
11Hannah Beckerhannah.becker@example.comDesignUI Designer1050002022-11-01London
12Yuki Tanakayuki.tanaka@example.comDesignProduct Designer1180002023-03-14San Francisco
13Olivia Martinolivia.martin@example.comMarketingVP of Marketing1650002019-04-22New York
14Ethan Brooksethan.brooks@example.comMarketingContent Strategist950002021-10-05Austin
15Nina Kowalskinina.kowalski@example.comMarketingSEO Specialist880002022-08-15New York
16Daniel Ochoadaniel.ochoa@example.comMarketingMarketing Analyst910002023-05-20Austin
17Samira Hassansamira.hassan@example.comMarketingSocial Media Manager820002024-01-08London
18Tyler Washingtontyler.washington@example.comSalesSales Director1580002019-11-30New York
19Jessica Huangjessica.huang@example.comSalesAccount Executive1100002020-06-14San Francisco
20Ryan O'Brienryan.obrien@example.comSalesAccount Executive1050002021-03-22London
21Fatima Al-Rashidfatima.alrashid@example.comSalesSales Development Rep720002023-09-01Austin
22Kevin Dupontkevin.dupont@example.comSalesSolutions Engineer1350002022-01-17San Francisco
23Megan Stewartmegan.stewart@example.comSalesAccount Manager980002024-03-11New York
24Laura Chenlaura.chen@example.comHRHR Director1480002019-08-05New York
25Brian Nakamurabrian.nakamura@example.comHRHR Business Partner1050002020-12-01San Francisco
26Chloe Duboischloe.dubois@example.comHRRecruiter780002022-05-23London
27Angela Morettiangela.moretti@example.comHRPeople Operations850002023-07-10Austin
28Isaac Fernandezisaac.fernandez@example.comEngineeringFrontend Engineer1280002022-09-19New York
29Sarah Mitchellsarah.mitchell@example.comDesignDesign Systems Lead1380002020-04-06San Francisco
30Omar Farahomar.farah@example.comEngineeringQA Engineer950002024-02-12London
31Natalie Parknatalie.park@example.comMarketingGrowth Manager1080002021-11-28San Francisco

Schema

Field Type Description
name string Employee full name.
email string Work email address on the fictional example.com domain.
department string One of Engineering, Sales, Marketing, HR, or Design.
role string Job title within the department.
salary int32 Annual salary in USD, stored as a 32-bit integer column.
start_date string Hire date as an ISO 8601 string (YYYY-MM-DD).
office string Office location — San Francisco, New York, Austin, or London.

About the Feather Format

Feather (v2) is the Apache Arrow IPC file format: Arrow’s in-memory columnar layout written to disk essentially verbatim, with a schema block up front and record batches behind it. Files carry .feather, .arrow, or .ipc extensions interchangeably — they are the same format.

Because the on-disk bytes match Arrow’s in-memory representation, reading Feather is close to a no-op: a reader can memory-map the file and use the buffers directly, with zero parsing and zero copying. That makes it the fastest way to move a dataframe between processes and languages — pandas to polars, Python to R — when both ends speak Arrow. The embedded schema travels with the data, so salary arrives as an int32 column with no type inference, same as the Parquet sample.

This sample is deliberately uncompressed. Feather supports optional LZ4 and ZSTD compression of record batches, and many writers enable it by default — but browser builds of the apache-arrow JavaScript library ship without those codecs, so compressed files fail in web tools with a codec error. Writing with compression='uncompressed' keeps the file readable by every Arrow implementation, including the site’s own Feather to CSV converter. At 30 rows the size cost is irrelevant; at scale, you’d enable ZSTD for storage and accept the narrower reader support.

Feather versus Parquet is a recurring question, and the honest answer is: Parquet for storage (heavier encoding and compression, broad ecosystem, predicate pushdown), Feather for interchange (minimal encode/decode cost, exact Arrow fidelity). If you need this data as Parquet, convert via CSV to Parquet or inspect it in the Parquet Viewer.

All eleven format samples in this section carry the same 30 employee rows, so converted output can be checked against the CSV baseline.

FAQ

4 questions
How do I open a Feather file?
In your browser, the Feather to CSV tool at /feather-to-csv/ converts this file to plain text instantly. In code: pandas.read_feather('sample-employees.feather') or polars.read_ipc() in Python, and arrow::read_feather() in R. A text editor won't help — the format is binary.
Why is this sample uncompressed?
On purpose. Feather files are often written with LZ4 or ZSTD compression, but browser builds of the apache-arrow library ship without those codecs, so compressed files fail in web-based tools with a codec error. This sample uses compression='uncompressed' so it opens everywhere. If your own file hits a codec error, re-save it with df.to_feather('file.feather', compression='uncompressed') in Python or write_feather(df, 'file.feather', compression='uncompressed') in R.
Does downloading this file send any data to a server?
No. The sample is a static file served directly by the site — nothing is uploaded, processed, or inspected. The Feather to CSV converter linked below runs entirely in your browser too.
Is the employee data real?
No. All 30 records are fictional, and every email address uses the reserved example.com domain, so the file is safe for demos, tests, and documentation.

Work With Feather Files 5 tools

Feather to CSV

Convert Apache Feather/Arrow files to CSV format

Parquet to CSV

Convert Apache Parquet files to CSV format

CSV to Parquet

Convert CSV into columnar Parquet format for efficient storage

Parquet Viewer

View parquet files online — sortable table plus full schema, types, and row counts

CSV Converter

Every CSV conversion tool on the site, searchable in one place.