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Update for Clean Code
Update for Clean Code - add 'return' to indicate the end of method - add a line break after a condition statement
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python/userCommand.py

Lines changed: 13 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -10,6 +10,7 @@
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import fitz
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import nltk
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nltk.download('punkt')
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######
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# Visual Python: Data Analysis > PDF
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######
@@ -43,6 +44,7 @@ def vp_pdf_get_sentence(fname_lst):
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df = _vp_pd.concat([df,df_doc])
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return df.reset_index().drop('index', axis=1)
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######
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# Visual Python: Data Analysis > Frame
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######
@@ -63,6 +65,7 @@ def vp_drop_outlier(df, col, weight=1.5):
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df_res = df.drop(outlier_index).copy()
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return df_res
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######
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# Visual Python: Machine Learning > Model Info
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######
@@ -74,10 +77,12 @@ def vp_create_feature_importances(model, X_train=None, sort=False):
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df_i = _vp_pd.DataFrame(model.feature_importances_, index=feature_names, columns=['Feature_importance'])
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df_i['Percentage'] = 100 * (df_i['Feature_importance'] / df_i['Feature_importance'].max())
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if sort: df_i.sort_values(by='Feature_importance', ascending=False, inplace=True)
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if sort:
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df_i.sort_values(by='Feature_importance', ascending=False, inplace=True)
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df_i = df_i.round(2)
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return df_i
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######
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# Visual Python: Machine Learning > Model Info
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######
@@ -91,10 +96,13 @@ def vp_plot_feature_importances(model, X_train=None, sort=False, top_count=0):
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df_i['Percentage'].sort_values().plot(kind='barh')
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else:
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df_i['Percentage'].plot(kind='barh')
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_vp_plt.xlabel('Feature importance Percentage')
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_vp_plt.ylabel('Features')
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_vp_plt.show()
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return
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######
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# Visual Python: Visualization > Seaborn
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######
@@ -134,4 +142,6 @@ def _single(ax):
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for idx, ax in _vp_np.ndenumerate(axs):
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_single(ax)
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else:
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_single(axs)
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_single(axs)
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return

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