Feat: get_questions_scores wrote
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@ -15,6 +15,13 @@ with open(DEFAULT_CONFIG_FILE, "r") as config:
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DEFAULT_CONFIG = yaml.load(config, Loader=yaml.FullLoader)
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def maybe_dataframe(datas):
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try:
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return [e[1] for e in datas.iterrows()]
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except AttributeError:
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return datas
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class CSVLoader(Loader):
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"""Loader when scores and metadatas are stored in csv files
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@ -99,7 +106,7 @@ class CSVLoader(Loader):
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def get_exam_questions(self, exams=[]):
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"""Get questions for exams stored in score_files
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:param exams: list of exams metadatas (need origin field to find the csv)
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:param exams: list or dataframe of exams metadatas (need origin field to find the csv)
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:example:
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>>> loader = CSVLoader("./test_config.yml")
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@ -114,10 +121,7 @@ class CSVLoader(Loader):
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'Bareme', 'Est_nivele', 'origin', 'exam_id', 'id'],
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dtype='object')
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"""
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try:
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_exams = [e[1] for e in exams.iterrows()]
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except AttributeError:
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_exams = exams
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_exams = maybe_dataframe(exams)
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questions = []
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for exam in _exams:
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@ -144,9 +148,45 @@ class CSVLoader(Loader):
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def get_questions_scores(self, questions=[]):
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"""Get scores of those questions
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:param questions: score for those questions
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:param questions: list or dataframe of questions metadatas (need origin field to find the csv)
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:example:
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>>> loader = CSVLoader("./test_config.yml")
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>>> exams = loader.get_exams(["Tribe1"])
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>>> questions = loader.get_exam_questions(exams)
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>>> scores = loader.get_questions_scores(questions)
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>>> scores.columns
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Index(['id', 'origin', 'student_name', 'score'], dtype='object')
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>>> scores["student_name"].unique()
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array(['Star Tice', 'Umberto Dingate', 'Starlin Crangle',
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'Humbert Bourcq', 'Gabriella Handyside', 'Stewart Eaves',
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'Erick Going', 'Ase Praton', 'Rollins Planks', 'Dunstan Sarjant',
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'Stacy Guiton', 'Ange Stanes', 'Amabelle Elleton',
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'Darn Broomhall', 'Dyan Chatto', 'Keane Rennebach', 'Nari Paulton',
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'Brandy Wase', 'Jaclyn Firidolfi', 'Violette Lockney'],
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dtype=object)
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"""
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return ""
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scores = []
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group_questions = questions.groupby("origin")
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for origin, questions_df in group_questions:
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scores_df = pd.read_csv(origin)
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common_columns = [c for c in questions_df.columns if c in scores_df.columns]
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scores_df = pd.merge(scores_df, questions_df, on=common_columns)
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scores_df = scores_df.drop(
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columns=list(self._config["csv_fields"].values()) + ["exam_id"]
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)
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kept_columns = ["id", "origin"]
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student_names = [c for c in scores_df.columns if c not in kept_columns]
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scores_df = pd.melt(
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scores_df,
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id_vars=kept_columns,
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value_vars=student_names,
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var_name="student_name",
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value_name="score",
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)
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scores.append(scores_df)
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return pd.concat(scores)
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def get_student_scores(self, student):
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"""Get scores of the student
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