Skip to main content

This project provides a collection of utilities for doing lightweight data wrangling.

Project description

datashaper

This project provides a collection of utilities for doing lightweight data wrangling.

There are two goals of the project:

  1. Create a shareable client/server schema for serialized wrangling instructions
  2. Maintain an implementation of a basic wrangling engine (based on Arquero) and in the case of python implemented in Pandas

Building

  • You need to install poetry python package manager.
  • Run: poetry install

Usage

This project is intended to be used as a library for lightweight data wrangling. In the examples folder there is a Notebook which provides several examples of how to create data wrangling pipelines and how to read json specifications that can be generated by the js implementation.

Example of joining two tables:

from datashaper.pipeline import Pipeline
import datashaper.types as types
import pandas as pd

# id   name
# 1    bob
# 2    joe
# 3    jane
parents = pd.DataFrame({
    "id": [1, 2, 3],
    "name": ['bob', 'joe', 'jane']
})

# id   kid
# 1    billy
# 1    jill
# 2    kaden
# 2    kyle
# 3    moe
kids = pd.DataFrame({
    "id": [1, 1, 2, 2, 3],
    "kid": ['billy', 'jill', 'kaden', 'kyle', 'moe']
})

pipeline = Pipeline()

pipeline.add_dataset('parents', parents)
pipeline.add_dataset('kids', kids)

pipeline.add(Step(
    verb=Verb.join,
    input="parents",
    output="output",
    args={
        "other": "kids",
        "on":["id"]
    }
))

# id   name    kid
# 1    bob     billy
# 1    bob     jill
# 2    joe     kaden
# 2    joe     kyle
# 3    jane    moe
result = pipeline.run()

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

Project details


Download files

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

Source Distribution

datashaper-0.0.36.tar.gz (35.4 kB view details)

Uploaded Source

Built Distribution

datashaper-0.0.36-py3-none-any.whl (69.5 kB view details)

Uploaded Python 3

File details

Details for the file datashaper-0.0.36.tar.gz.

File metadata

  • Download URL: datashaper-0.0.36.tar.gz
  • Upload date:
  • Size: 35.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for datashaper-0.0.36.tar.gz
Algorithm Hash digest
SHA256 059627932fd0c20afe538c776391e2bedd8ace6ff0b66272c920774be8bb0d23
MD5 9180a7f68837cfe5eac2b9ac731be0a0
BLAKE2b-256 9f66d360de5171ade16ce545b6ecc886c3f15c531af3fc3fb0e2078e4dedd64d

See more details on using hashes here.

File details

Details for the file datashaper-0.0.36-py3-none-any.whl.

File metadata

  • Download URL: datashaper-0.0.36-py3-none-any.whl
  • Upload date:
  • Size: 69.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for datashaper-0.0.36-py3-none-any.whl
Algorithm Hash digest
SHA256 d9b6e6ef5ef84846215758a8fb18343e8248cb0220bb1138375079d6f1a23e57
MD5 ecfdaf0d42e1b4a0e1c0644eb8444a6c
BLAKE2b-256 d9e267e737a81c71f4b554881f583aa731d8453e56b4802cc2809fc770eef33a

See more details on using hashes here.

Supported by

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