Simple Objected based approach to using data from a csv All the source code can be found at the csvObject git repository
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.
csvObject is available as a package via Pypi so you can pip install by the following command
python -m pip install csvObjectThe simplest use case is when the only argument to passed to the object is the path to the file. In this case the only thing this package is doing is creating an object that holds the filename, the headers, and the data in a row and column format from the csv module within python. CsvObject does have other options, detailed on the docs page although you may find it more useful to look at it in a interactive session via the jupyter file within the Examples folder.
from csvObject.csvObject import CsvObject
csv_object = CsvObject("Example Data.csv")
print(csv_object.row_data)Contributions are always welcome, if you want to make a contribution simply make a pull request based on your fork of the project
Distributed under the MIT License. See LICENSE for more information.