add normalized column into digest_flat_df
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@ -69,6 +69,8 @@ def note_to_mark(x):
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def compute_marks(df):
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""" Add Mark column to df
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:param df: DataFrame with "Note", "Niveau" and "Bareme" columns.
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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... "Nom": ["N1"]*4+["N2"]*2 + ["N1"]*4+["N2"]*2,
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... "Exercice":["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"] + ["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"],
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@ -100,6 +102,8 @@ def compute_marks(df):
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def compute_latex_rep(df):
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""" Add Latex_rep column to df
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:param df: DataFrame with "Note" and "Niveau" columns.
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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... "Nom": ["N1"]*4+["N2"]*2 + ["N1"]*4+["N2"]*2,
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... "Exercice":["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"] + ["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"],
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@ -128,6 +132,40 @@ def compute_latex_rep(df):
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"""
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return df[["Note", "Niveau"]].apply(note_to_rep, axis=1).fillna("??")
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def compute_normalized(df):
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""" Compute the normalized mark (Mark / Bareme)
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:param df: DataFrame with "Mark" and "Bareme" columns
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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... "Nom": ["N1"]*4+["N2"]*2 + ["N1"]*4+["N2"]*2,
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... "Exercice":["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"] + ["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"],
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... "Question":["Q1"]+["Q2"]+["Q1"]+["Q2"]+["Q1"]+["Q1"] + ["Q1"]+["Q2"]+["Q1"]+["Q2"]+["Q1"]+["Q1"],
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... "Date":["16/09/2016"]*4+["01/10/2016"]*2 + ["16/09/2016"]*4+["01/10/2016"]*2,
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... "Trimestre": ["1"]*12,
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... "Bareme":[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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... "Niveau":[0]*4+[1]*2 + [0]*4+[1]*2,
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... "Note":[1, 0.33, 2, 1.5, 1, 3, 0.666, 1, 1.5, 1, 2, 3],
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... }
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>>> df = pd.DataFrame(d)
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>>> df["Mark"] = compute_marks(df)
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>>> compute_normalized(df)
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0 1.000000
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1 0.330000
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2 1.000000
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3 0.750000
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4 0.333333
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5 1.000000
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6 0.666000
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7 1.000000
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8 0.750000
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9 0.500000
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10 0.666667
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11 1.000000
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dtype: float64
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"""
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return df["Mark"] / df["Bareme"]
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# Computing custom values
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def compute_exo_marks(df):
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@ -229,9 +267,12 @@ def digest_flat_df(flat_df):
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df = flat_df.copy()
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df["Mark"] = compute_marks(flat_df)
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df["Latex_rep"] = compute_latex_rep(flat_df)
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df["Normalized"] = compute_normalized(flat_df)
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exo_df = compute_exo_marks(df)
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exo_df["Normalized"] = compute_normalized(exo_df)
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eval_df = compute_eval_marks(exo_df)
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eval_df["Normalized"] = compute_normalized(eval_df)
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return df, exo_df, eval_df
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