NumPy NPY to CSV
Export NumPy numeric arrays as CSV with explicit shape and precision limits.
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Supported input formats
- NumPy NPY numeric array (.npy)
Output format
Comma-separated values (.csv)
Support applies to this conversion direction. Check the limits below for features that may change or be discarded.
Compare all supported formats and conversion limits →How to use NumPy NPY to CSV
- Add your supported file using the chooser or drop zone.
- Review the settings and conversion limits before processing.
- Select Convert files, then download the result.
What to expect
- Maximum 64 MiB and 2 million stored values/coordinates; each dimension is at most 2 million. Only finite values are supported. Dense CSV is capped at 2 million cells.
- NPY v1/v2/v3, plain numeric/bool dtype only: signed/unsigned 1/2/4/8-byte integers, float32/64 and bool. Endianness and C/Fortran order are handled. No object/pickle, structured, string, float16, complex, NPZ or masked arrays. JSON stores flat data in original storage order with shape/dtype; unsafe integers are decimal strings. CSV supports rank 0–2 and lays out rows/columns; JSON supports rank up to 32.
Engine: Local scientific matrix parser. The engine may need a first-use download. Your file stays in this browser session.Check conversion engines and offline requirements.
About this conversion
Is numpy npy to csv free?
Yes. This tool runs on your device without an account or a conversion fee.
Are files uploaded during conversion?
File processing happens locally in your browser. Engines may download their code on first use; your input files are not sent to a conversion server. Read how file privacy works.
What if conversion fails?
Check that the file matches a supported input, review the engine’s limitations and try a smaller representative file. If the engine cannot load, check its engine assets and browser requirements. The app reports failures without switching to a remote converter.
Continue with your output
These tools accept this tool’s output format. Each step has its own settings and fidelity limits.
- Numeric data to HDF5
Create a single selected HDF5 dataset from a numeric matrix or an exported JSON envelope.
- Numeric CSV to Matrix Market
Turn a headerless numeric CSV matrix into sparse Matrix Market coordinate data, omitting zero entries.
- CSV to JSON
Convert CSV locally with an explicit structured-data mapping.
- CSV to TSV
Convert CSV locally with an explicit structured-data mapping.
- CSV to YAML
Convert CSV locally with an explicit structured-data mapping.
- CSV to XML
Convert CSV locally with an explicit structured-data mapping.
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- NumPy NPY to JSON
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- HDF5 dataset to JSON
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- HDF5 dataset to CSV
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- Inspect FASTA sequences
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- FASTA to CSV
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