Data Exploration Terser
Project description
dexter
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
- 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
Dependencies
License
Distributed under the BSD 3 license. See LICENSE.txt
for more information.
Contact
Igor Magalhaes – @igormagalhaesr – igormagalhaesr@gmail.com
Project details
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