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Runtime error
Commit ·
86ee792
1
Parent(s): 9d378bb
some changing
Browse files- Dictionary_guesser/__init__.py +0 -0
- __init__.py +0 -0
- app.py +3 -2
Dictionary_guesser/__init__.py
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__init__.py
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app.py
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@@ -10,6 +10,8 @@ import utils.plot as plot
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class GenderPredictorApp:
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def __init__(self, modelpath):
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self.gender_predictor = GenderPredictor(modelpath)
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self.setup_ui()
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def setup_ui(self):
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@@ -44,13 +46,12 @@ class GenderPredictorApp:
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return prediction
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def predict_github_url(self, url):
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commit_info = CommitInfo(url)
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Region_predictor=RegionPredictor("saved_model/Regions")
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df,first_commit_dates = commit_info.get_first_commit_dates()
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first_commit_dates[['Predicted_Gender', 'Confidence']] = first_commit_dates['Author'].apply(lambda name: pd.Series(self.gender_predictor.predict_gender(name)))
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first_commit_dates['Predicted_Gender'] = first_commit_dates['Predicted_Gender'].replace({0: "Male", 1: "Female", 2: "Unknown"})
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Gender_Percentage=plot.get_gender_percentage(first_commit_dates)
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Results=first_commit_dates[first_commit_dates["Predicted_Gender"]!="Unknown"]
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Results=Region_predictor.get_region(Results)
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merged_df = df.merge(Results[["Author","sub-region-prediction","Predicted_Gender","Confidence"]], on=["Author"])
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# Group by Year and Predicted_Gender, then count the occurrences
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class GenderPredictorApp:
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def __init__(self, modelpath):
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self.gender_predictor = GenderPredictor(modelpath)
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self.Region_predictor=RegionPredictor("saved_model/Regions")
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self.setup_ui()
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def setup_ui(self):
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return prediction
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def predict_github_url(self, url):
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commit_info = CommitInfo(url)
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df,first_commit_dates = commit_info.get_first_commit_dates()
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first_commit_dates[['Predicted_Gender', 'Confidence']] = first_commit_dates['Author'].apply(lambda name: pd.Series(self.gender_predictor.predict_gender(name)))
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first_commit_dates['Predicted_Gender'] = first_commit_dates['Predicted_Gender'].replace({0: "Male", 1: "Female", 2: "Unknown"})
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Gender_Percentage=plot.get_gender_percentage(first_commit_dates)
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Results=first_commit_dates[first_commit_dates["Predicted_Gender"]!="Unknown"]
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Results=self.Region_predictor.get_region(Results)
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merged_df = df.merge(Results[["Author","sub-region-prediction","Predicted_Gender","Confidence"]], on=["Author"])
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# Group by Year and Predicted_Gender, then count the occurrences
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