data exploration terser
dexter is a lightweight Python package built on top of numpy and pandas that allows fast data exploration for multiple structured table files in a folder. It's a high-level tool suitable for a first contact with a dataset composed of multiple dataframes.
- Importing multiple table files with readm_csv()
- Saving DataFrames and Names with the FrameMap class
- Applying pandas methods to multiple DataFrames at once
PyPI:
pip install dexter
https://pypi.org/project/dexter/
Importing dexter:
import dexter as dxt
Reading multiple dataframes in a folder:
dataframes = dxt.readm_csv("./folder/")
Displaying results:
dataframes.display()
Out:
Names and Frames
names = dataframes.names
frames = dataframes.frames
Multiple Dataframes Types
dataframes.dtypes()
Multiple Missing Values
dataframes.multiple_missing()
Multiple Descriptions
dataframes.describe()
For more concrete examples, check the notebook
- Fork it (https://github.com/igormagalhaesr/dexter)
- Create your feature branch (
git checkout -b feature/fooBar
) - Commit your changes (
git commit -am 'Add some fooBar'
) - Push to the branch (
git push origin feature/fooBar
) - Create a new Pull Request
Distributed under the BSD 3 license. See LICENSE.txt
for more information.
Igor Magalhaes – @igormagalhaesr – igormagalhaesr@gmail.com