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Data Exploration Terser

Project description

dexter

PyPI version GitHub license Documentation Status


data exploration terser

What is dexter?

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.

Features

  • Importing multiple table files with readm_csv()
  • Saving DataFrames and Names with the FrameMap class
  • Applying pandas methods to multiple DataFrames at once

Installing

PyPI:

pip install dexter

https://pypi.org/project/dexter/

Usage

Importing dexter:

import dexter as dxt

Reading multiple dataframes in a folder:

dataframes = dxt.readm_csv(./folder/)

Displaying results:

dataframes.display()

Out:

df1
col1 col2 col3
0 value1 $3
1 value2 $5
2 value3 $7
df2
first second third
0 one 17%
1 two 19%
2 three 23%

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

Contributing

  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

Dependencies

License

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

Contact

Igor Magalhaes – @igormagalhaesrigormagalhaesr@gmail.com

github.com/igormagalhaesr

Project details


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