From ec469214daa0199318ed1ce1f27085955caef182 Mon Sep 17 00:00:00 2001
From: Benjamin Bertrand <lafrite@poneyworld.net>
Date: Sun, 13 Nov 2016 14:40:36 +0300
Subject: [PATCH] add normalized column into digest_flat_df

---
 notes_tools/df_marks_manip.py | 41 +++++++++++++++++++++++++++++++++++
 1 file changed, 41 insertions(+)

diff --git a/notes_tools/df_marks_manip.py b/notes_tools/df_marks_manip.py
index 157b220..478bbb6 100644
--- a/notes_tools/df_marks_manip.py
+++ b/notes_tools/df_marks_manip.py
@@ -69,6 +69,8 @@ def note_to_mark(x):
 def compute_marks(df):
     """ Add Mark column to df
 
+    :param df: DataFrame with "Note", "Niveau" and "Bareme" columns.
+
     >>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
     ...    "Nom": ["N1"]*4+["N2"]*2 + ["N1"]*4+["N2"]*2,
     ...    "Exercice":["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"] + ["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"],
@@ -100,6 +102,8 @@ def compute_marks(df):
 def compute_latex_rep(df):
     """ Add Latex_rep column to df
 
+    :param df: DataFrame with "Note" and "Niveau" columns.
+
     >>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
     ...    "Nom": ["N1"]*4+["N2"]*2 + ["N1"]*4+["N2"]*2,
     ...    "Exercice":["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"] + ["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"],
@@ -128,6 +132,40 @@ def compute_latex_rep(df):
     """
     return df[["Note", "Niveau"]].apply(note_to_rep, axis=1).fillna("??")
 
+def compute_normalized(df):
+    """ Compute the normalized mark (Mark / Bareme)
+
+    :param df: DataFrame with "Mark" and "Bareme" columns
+
+    >>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
+    ...    "Nom": ["N1"]*4+["N2"]*2 + ["N1"]*4+["N2"]*2,
+    ...    "Exercice":["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"] + ["Ex1"]*2+["Ex2"]*2+["Ex1"]+["Ex2"],
+    ...    "Question":["Q1"]+["Q2"]+["Q1"]+["Q2"]+["Q1"]+["Q1"] + ["Q1"]+["Q2"]+["Q1"]+["Q2"]+["Q1"]+["Q1"],
+    ...    "Date":["16/09/2016"]*4+["01/10/2016"]*2 + ["16/09/2016"]*4+["01/10/2016"]*2,
+    ...    "Trimestre": ["1"]*12,
+    ...    "Bareme":[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
+    ...    "Niveau":[0]*4+[1]*2 + [0]*4+[1]*2,
+    ...    "Note":[1, 0.33, 2, 1.5, 1, 3,   0.666, 1, 1.5, 1, 2, 3],
+    ...    }
+    >>> df = pd.DataFrame(d)
+    >>> df["Mark"] = compute_marks(df)
+    >>> compute_normalized(df)
+    0     1.000000
+    1     0.330000
+    2     1.000000
+    3     0.750000
+    4     0.333333
+    5     1.000000
+    6     0.666000
+    7     1.000000
+    8     0.750000
+    9     0.500000
+    10    0.666667
+    11    1.000000
+    dtype: float64
+    """
+    return df["Mark"] / df["Bareme"]
+
 # Computing custom values
 
 def compute_exo_marks(df):
@@ -229,9 +267,12 @@ def digest_flat_df(flat_df):
     df = flat_df.copy()
     df["Mark"] = compute_marks(flat_df)
     df["Latex_rep"] = compute_latex_rep(flat_df)
+    df["Normalized"] = compute_normalized(flat_df)
 
     exo_df = compute_exo_marks(df)
+    exo_df["Normalized"] = compute_normalized(exo_df)
     eval_df = compute_eval_marks(exo_df)
+    eval_df["Normalized"] = compute_normalized(eval_df)
 
     return df, exo_df, eval_df