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datashaper

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

There are two goals of the project:

Create a shareable client/server schema for serialized wrangling instructions
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.

Metadata

Release files for datashaper 0.0.49

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Source distribution (sdist)

Source distribution for datashaper 0.0.49
File	Size	Uploaded
datashaper-0.0.49.tar.gz	36.4 kB	Mar 18, 2024	Details

Built distribution (wheel)

Table of built distributions (wheels) for datashaper 0.0.49
File	Interpreter	ABI	Platform	Reset
datashaper-0.0.49-py3-none-any.whl 72.0 kB Mar 18, 2024	Python 3	none	any	Details

Total release size: 108.4 kB

Release files / datashaper-0.0.49.tar.gz

Download URL	datashaper-0.0.49.tar.gz
Size	36.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`05bfba5964474a62bdd5259ec3fa0173d01e365208b6a4aff4ea0e63096a7533`
BLAKE2b-256 checksum How to use checksums	`e6d328663b75307748e36a026d32a6d60e0725ed054f28cc5a72fa418ac166ae`
Upload date	Mar 18, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/5.0.0 CPython/3.12.2`

Release files / datashaper-0.0.49-py3-none-any.whl

Download URL	datashaper-0.0.49-py3-none-any.whl
Size	72.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`7f58cabacc834765595c6e04cfbbd05be6af71907e46ebc7a91d2a4add7c2643`
BLAKE2b-256 checksum How to use checksums	`cbb9f5cebf0fd2ebee6449663989f275f186928c92b94d05c9503c9ccc814757`
Upload date	Mar 18, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/5.0.0 CPython/3.12.2`