A python library for automated exploratory data analysis
Documentation - https://klareda.github.io/klar-EDA/
Presentation - https://youtu.be/FsDV6a-L-wo
The library aims to ease the data exploration and preprocessing steps and provide a smart and automated technique for exploratory analysis of the data
The library consists of the following modules
- CSV Data Visualization
- CSV Data Preprocessing
- Image Data Visualization
- Image Data Preprocessing
You can install the test version of the library by the below command::
$ pip3 install -i https://test.pypi.org/simple/ klar-eda
The above mentioned modules can be used as below::
>>> import klar_eda
>>> from klar_eda.visualization import visualize_csv
>>> visualize_csv(<csv-file-path>)
OR
>>> visualize_csv(<data-frame>)
>>> from klar_eda.preprocessing import preprocess_csv
>>> preprocess_csv(<csv-file-path>)
OR
>>> preprocess_csv(<data-frame>)
>>> from klar_eda.visualization import visualize_images
>>> ds = tfds.load('cifar10', split='train', as_supervised=True)
>>> images = []
>>> labels = []
>>> for image, label in tfds.as_numpy(ds):
h = randint(24, 56)
w = randint(24, 56)
image = cv2.resize(image, (w, h))
images.append(image)
labels.append(label)
>>> visualize_images(images, labels)
>>> from klar_eda.preprocessing import preprocess_images
>>> preprocess_images(<images-folder-path>)
If you liked our project, it would be really helpful if you could share this project with others.
For contributing to this project, feel free to clone the repository::
git clone https://github.com/klarEDA/klar-EDA.git
For installing the necessary packages, run the below command::
$ pip3 install -r requirement.txt
To test the documentation in local::
$ cd docsource/
$ make html
To push the latest documentation in github::
$ cd docsource/
$ make github
klar-eda is released under the MIT license.
Please feel free to contact us for any issues OR for discussion of future scope of the library at [email protected]