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Kathryn Hurchla khurchla

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khurchla / numpy_unique.py
Created July 15, 2022 13:46
factorize string objects with python numpy courtesy of Matt
unique = np.unique(df[['Rank 1','Rank 2','Rank 3','Rank 78','Rank 79','Rank 80']])
factors = np.arange(len(unique))
df[['Rank 1','Rank 2','Rank 3','Rank 78','Rank 79','Rank 80']] = df[['Rank 1','Rank 2','Rank 3','Rank 78','Rank 79','Rank 80']].replace(unique, factors)
df
@khurchla
khurchla / whylogs_profile_views.py
Last active June 7, 2022 02:33
whylogs v1 profile visualizer examples
import whylogs as why
result = why.log(pandas=wine_target)
prof_view = result.view()
result_ref = why.log(pandas=wine_reference)
prof_view_ref = result_ref.view()
from whylogs.viz import NotebookProfileVisualizer
visualization = NotebookProfileVisualizer()
# add some missing values to a feature to see how they
ixs = wine.iloc[100:110].index
wine.loc[ixs,'citric acid'] = None
bins = (2, 6.5, 8)
group_names = ['bad', 'good']
wine_reference['quality'] = pd.cut(wine_reference['quality'], bins = bins, labels = group_names)
wine_target['quality'] = pd.cut(wine_target['quality'], bins = bins, labels = group_names)
cond_reference = (wine['alcohol']<=11)
wine_reference = wine.loc[cond_reference]
cond_target = (wine['alcohol']>11)
wine_target = wine.loc[cond_target]
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@khurchla
khurchla / profile_visualizer_initialize
Created June 7, 2022 01:55
initialize whylogs v1 profile visualizer
from whylogs.viz import NotebookProfileVisualizer
visualization = NotebookProfileVisualizer()
visualization.set_profiles(target_profile_view=prof_view, reference_profile_view=prof_view_ref)
@khurchla
khurchla / Notebook_Profile_Visualizer_drift_analysis-wine_quality_drift_report.ipynb
Last active June 7, 2022 01:47
demo example of whylogs v1 profile visualizer summary drift report to compare two data profile views
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@khurchla
khurchla / whylogs_profile_visualizer_install_dependencies.ipynb
Last active June 7, 2022 01:33
whylogs v1 profile visualizer install dependencies in a Jupyter Notebook
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@khurchla
khurchla / profile_visualizer_visualization_write.py
Last active June 7, 2022 02:47
download whylogs profile visualizer charts or report in HTML format
# write the Difference Distribution bar chart of the citric acid feature to file
# in an output subdirectory
import os
os.getcwd()
visualization.write(
rendered_html=visualization.difference_distribution_chart(
feature_name="citric acid", profile="target"
),
html_file_name=os.getcwd() + "/output/diff_dist_citric_acid_example",
)
@khurchla
khurchla / radial_charts.py
Created May 27, 2022 23:05
Plotly Dash Python Radial Chart manual subplots
values = {'Timestamp':['5/20/2022 19:44:43', '5/20/2022 20:14:36',
'5/20/2022 20:14:38', '5/20/2022 20:14:39',
'5/20/2022 19:44:43', '5/20/2022 20:14:46',
'5/20/2022 20:14:47', '5/20/2022 19:44:49',
'5/20/2022 20:14:51', '5/20/2022 20:14:53',
'5/20/2022 20:14:56'],
'Build':[6, 4, 6, 6, 3, 6, 1, 4, 5, 6, 2],
'Story':[6, 3, 6, 5, 6, 3, 1, 3, 3, 3, 1],
'Design':[6, 6, 5, 4, 4, 4, 2, 6, 1, 2, 2],
'Systems':[6, 2, 6, 1, 1, 5, 6, 1, 2, 3, 2],