sensor-dataset 0.0.1

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Outlier Detection

Detect and filter outliers.

Documentation and Code can be found on Github

Install

pip install sensor_dataset

Z-SCORE Normalization

Normalize data with Z-SCORE

from sensor_dataset.outlier_detection import ZSCORE

Get a normalized Koalas dataframe for the sensor dataset and fig objects by calling:

kdf, figs = ZSCORE()

figs['NORMAL'].write_image("images/zscore_normal.png")
figs['RECOVERING'].write_image("images/zscore_recovering.png")
figs['BROKEN'].write_image("images/zscore_broken.png")

When running on a notebook you may show an interactive plot by using:

fig.show()

IQR

Filter data using IQR

from sensor_dataset.outlier_detection import IQR

kdf, figs = IQR()

figs['NORMAL'].write_image("images/iqr_normal.png")
figs['RECOVERING'].write_image("images/iqr_recovering.png")
figs['BROKEN'].write_image("images/iqr_broken.png")