Skip to main content

Pandas DataFrame API on Apache Spark

Project description

Koalas makes data scientists more productive when interacting with big data, by augmenting Apache Spark’s Python DataFrame API to be compatible with Pandas’.

Pandas is the de facto standard (single-node) dataframe implementation in Python, while Spark is the de facto standard for big data processing. With this package, data scientists can:

  • Be immediately productive with Spark, with no learning curve, if one is already familiar with Pandas.

  • Have a single codebase that works both with Pandas (tests, smaller datasets) and with Spark (distributed datasets).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

koalas-0.1.0-py3-none-any.whl (41.7 kB view details)

Uploaded Python 3

File details

Details for the file koalas-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: koalas-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 41.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.8

File hashes

Hashes for koalas-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c29d1344df21dd18034c2c895dd93c4f036692d853879701131ddd1126f5e832
MD5 1410985fe86b41d51146603e9f9632a9
BLAKE2b-256 5b0a7f038b39257cd7178190082558d6a1586092201c4d04ad985b31b25b5b6c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page