Skip to main content

Classes for data manipulation

Project description

Python Classes for Data Manipulation

Test Documentation Status PyPI Downloads

Dataiter currently includes the following classes.

DataFrame is a class for tabular data similar to R's data.frame or pandas.DataFrame. It is under the hood a dictionary of NumPy arrays and thus capable of fast vectorized operations. You can consider this to be a light-weight alternative to Pandas with a simple and consistent API. Performance-wise Dataiter relies on NumPy and Numba and is likely to be at best comparable to Pandas.

ListOfDicts is a class useful for manipulating data from JSON APIs. It provides functionality similar to libraries such as Underscore.js, with manipulation functions that iterate over the data and return a shallow modified copy of the original. attd.AttributeDict is used to provide convenient access to dictionary keys.

GeoJSON is a simple wrapper class that allows reading a GeoJSON file into a DataFrame and writing a data frame to a GeoJSON file. Any operations on the data are thus done with methods provided by the data frame class. Geometry is read as-is into the "geometry" column, but no special geometric operations are currently supported.

Installation

# Latest stable version
pip install -U dataiter

# Latest development version
pip install -U git+https://github.com/otsaloma/dataiter

# Numba (optional)
pip install -U numba

Dataiter optionally uses Numba to speed up certain operations. If you have Numba installed and importing it succeeds, Dataiter will use it automatically. It's currently not a hard dependency, so you need to install it separately.

Documentation

https://dataiter.readthedocs.io/

If you're familiar with either dplyr (R) or Pandas (Python), the comparison table in the documentation will give you a quick overview of the differences and similarities.

https://dataiter.readthedocs.io/en/latest/comparison.html

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

dataiter-0.51.tar.gz (49.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dataiter-0.51-py3-none-any.whl (67.7 kB view details)

Uploaded Python 3

File details

Details for the file dataiter-0.51.tar.gz.

File metadata

  • Download URL: dataiter-0.51.tar.gz
  • Upload date:
  • Size: 49.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.11.9

File hashes

Hashes for dataiter-0.51.tar.gz
Algorithm Hash digest
SHA256 8052b8231ff88b61409f27fac093f74db5b0242aae3815d216c20f8cbcc86e5c
MD5 198a17c10e12f80c83007458b4ff1017
BLAKE2b-256 6a83ba485b8a3d8c650e0252d2f74ad6bce6cc432f375d6b03273ce9fc779b35

See more details on using hashes here.

File details

Details for the file dataiter-0.51-py3-none-any.whl.

File metadata

  • Download URL: dataiter-0.51-py3-none-any.whl
  • Upload date:
  • Size: 67.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.11.9

File hashes

Hashes for dataiter-0.51-py3-none-any.whl
Algorithm Hash digest
SHA256 aa5e1f25ffc36e6ff2d3e5865922c6316e128c5fa3d250d306963788168e2bef
MD5 bd4c2f2f53fdee4965f237a83fff7e17
BLAKE2b-256 0a3695af17a73698db85327a54eec66ffa85d9c56af40a16e1c75e7ebea011dc

See more details on using hashes here.

Supported by

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