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

1. Fork it (https://github.com/igormagalhaesr/dexter)
2. Create your feature branch (git checkout -b feature/fooBar)
3. Commit your changes (git commit -am 'Add some fooBar')
4. Push to the branch (git push origin feature/fooBar)
5. Create a new Pull Request

• NumPy
• Pandas
• IPython

Distributed under the BSD 3 license. See LICENSE.txt for more information.

Igor Magalhaes – @igormagalhaesr – igormagalhaesr@gmail.com

github.com/igormagalhaesr