Skip to main content

Simple Objected based approach to using data from a csv

Project description

csvObject

Simple Objected based approach to using data from a csv

About The Project

csvObject is just a simple object base approach to loading in a csv file and using the data. In more complex cases when doing actual data analysis or changing the structure of the file, using pandas makes much more sense. But if all you want is to have a light weight way of extracting the data from the csv file parsed into an object with a few basic options without Numpy then this may be of interest.

All the source code can be found at the csvObject git repository with additional information found on the docs site

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

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

csvObject-0.6.2-py3-none-any.whl (6.1 kB view details)

Uploaded Python 3

File details

Details for the file csvObject-0.6.2-py3-none-any.whl.

File metadata

  • Download URL: csvObject-0.6.2-py3-none-any.whl
  • Upload date:
  • Size: 6.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.53.0 CPython/3.9.0

File hashes

Hashes for csvObject-0.6.2-py3-none-any.whl
Algorithm Hash digest
SHA256 85f3832e3fec2def0a1663f2867e2e07762912009123704a5731217c67106209
MD5 77301fca18212cf70f50c9c3c942b45c
BLAKE2b-256 2b004a1905eee3264f143e5bb5e96e020ec58d9e122d16c59f8738c7b48e93f4

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