Move eval_tools to eval annd Start Student pov
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Benjamin Bertrand
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#!/usr/bin/env python
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# encoding: utf-8
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import pandas as pd
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import numpy as np
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class Student(object):
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"""
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Informations on a student which can be use inside template.
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Those informations should not be modify or use for compute analysis otherwise they won't be spread over other POV.
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"""
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def __init__(self, quest_df, exo_df, eval_df):
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"""
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Description of a student from quest, exo and eval
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"""
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name = {*quest_df["Eleve"].unique(),
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*exo_df["Eleve"].unique(),
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*eval_df["Eleve"].unique(),
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}
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if len(name) != 1:
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raise ValueError("Can't initiate Student: dfs contains different student names")
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self.name = name.pop()
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evalname = {*quest_df["Nom"].unique(),
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*exo_df["Nom"].unique(),
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*eval_df["Nom"].unique(),
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}
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if len(evalname) != 1:
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raise ValueError("Can't initiate Student: dfs contains different evaluation names")
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self.quest_df = quest_df
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self.exo_df = exo_df
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self.eval = eval_df.to_dict('records')[0]
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@property
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def latex_exo_tabulars(self):
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""" Return list of latex tabulars. One by exercise of the evaluation """
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try:
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self._latex_exo_tabulars
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except AttributeError:
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self._latex_exo_tabulars = self.build_latex_exo_tabulars()
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return self._latex_exo_tabulars
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def build_latex_exo_tabulars(self):
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tabulars = []
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for t in self.exo_df["Exercice"]:
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tabulars.append(self.build_latex_exo_tabular(t))
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return tabulars
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def build_latex_exo_tabular(self, exo_name):
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exo = self.exo_df[self.exo_df["Exercice"] == exo_name]
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quest = self.quest_df[self.quest_df["Exercice"] == exo_name]
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tabular = [r"\begin{tabular}{|p{2cm}|c|}"]
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tabular.append(r"\hline")
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if type(exo_name) == int:
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tabular.append(f"Exercice {exo_name} & {exo['Mark_barem'].all()} \\\\")
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else:
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tabular.append(f"{exo_name} & {exo['Mark_barem'].all()} \\\\")
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tabular.append(r"\hline")
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if len(quest) > 1:
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for _, q in quest.iterrows():
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line = ""
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if not pd.isnull(q["Question"]):
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line += str(q['Question'])
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if not pd.isnull(q["Commentaire"]):
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line += str(q['Commentaire'])
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line += " & "
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if q["Niveau"] == 1:
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line += q['Latex_rep']
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else:
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line += str(q['Mark'])
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tabular.append(line)
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tabular.append(r"\hline")
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tabular.append(r"\end{tabular}")
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return '\n'.join(tabular)
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class Classe(object):
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"""
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Informations on a class which can be use inside template.
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Those informations should not be modify or use for compute analysis otherwise they won't be spread over other POV.
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"""
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pass
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# TODO: à factoriser Il y a la même dans term.py |jeu. mars 23 19:36:28 EAT 2017
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def select(quest_df, exo_df, eval_df, index, value):
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""" Return quest, exo and eval rows which correspond index == value
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:param quest_df: TODO
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:param exo_df: TODO
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:param eval_df: TODO
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"""
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qu = quest_df[quest_df[index] == value]
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exo = exo_df[exo_df[index] == value]
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ev = eval_df[eval_df[index] == value]
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return qu, exo, ev
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def select_contains(quest_df, exo_df, eval_df, index, name_part):
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""" Return quest, exo and eval rows which contains name_part
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:param quest_df: TODO
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:param exo_df: TODO
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:param eval_df: TODO
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"""
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qu = quest_df[quest_df[index].str.contains(name_part)]
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exo = exo_df[exo_df[index].str.contains(name_part)]
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ev = eval_df[eval_df[index].str.contains(name_part)]
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return qu, exo, ev
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def students_pov(quest_df, exo_df, eval_df):
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es = []
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for e in eval_df["Eleve"].unique():
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d = select(quest_df, exo_df, eval_df, "Eleve", e)
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eleve = Student(*d)
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es.append(eleve)
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return es
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def class_pov(quest_df, exo_df, eval_df):
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return Classe(quest_df, exo_df, eval_df)
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# -----------------------------
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# Reglages pour 'vim'
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# vim:set autoindent expandtab tabstop=4 shiftwidth=4:
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# cursor: 16 del
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@ -1,108 +0,0 @@
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#!/usr/bin/env python
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# encoding: utf-8
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import pandas as pd
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import numpy as np
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def select(quest_df, exo_df, eval_df, evalname):
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""" Return quest, exo and eval rows which correspond to evalname
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:param quest_df: TODO
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:param exo_df: TODO
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:param eval_df: TODO
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"""
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qu = quest_df[quest_df["Nom"] == evalname]
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exo = exo_df[exo_df["Nom"] == evalname]
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ev = eval_df[eval_df["Nom"] == evalname]
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return qu, exo, ev
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def select_contains(quest_df, exo_df, eval_df, name_part):
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""" Return quest, exo and eval rows which contains name_part
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:param quest_df: TODO
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:param exo_df: TODO
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:param eval_df: TODO
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"""
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qu = quest_df[quest_df["Nom"].str.contains(name_part)]
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exo = exo_df[exo_df["Nom"].str.contains(name_part)]
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ev = eval_df[eval_df["Nom"].str.contains(name_part)]
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return qu, exo, ev
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def get_present_absent(eval_df):
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""" Return list of student who where present (Mark > 0) and
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the list of those who weren't
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"""
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presents = eval_df[eval_df["Mark"] > 0]["Eleve"]
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absents = eval_df[eval_df["Mark"] == 0]["Eleve"]
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return {"presents": presents, "absents": absents}
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def keep_only_presents(quest_df, exo_df, eval_df, presents):
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""" Return quest, exo and eval rows of presents students """
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qu = quest_df[quest_df["Eleve"].isin(presents)]
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exo = exo_df[exo_df["Eleve"].isin(presents)]
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ev = eval_df[eval_df["Eleve"].isin(presents)]
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return qu, exo, ev
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def students_pov(quest_df, exo_df, eval_df):
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"""
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>>> from .df_marks_manip import digest_flat_df
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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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>>> quest_df, exo_df, eval_df = digest_flat_df(df)
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>>> std_pov = students_pov(quest_df, exo_df, eval_df)
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>>> std = std_pov[0]
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>>> std["Nom"]
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'E1'
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>>> "{} / {}".format(std["Total"]["Mark"], std["Total"]["Bareme"])
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'5.0 / 6.0'
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>>> for exo in std["Exercices"]:
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... print("{}: {} / {}".format(exo["Nom"], exo["Total"]["Mark"], exo["Total"]["Bareme"]))
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Ex1: 1.5 / 2.0
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Ex2: 3.5 / 4.0
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>>> exo = std["Exercices"][0]
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>>> for _,q in exo["Questions"].iterrows():
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... print("{} : {}".format(q["Question"], q["Latex_rep"]))
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Q1 : 1.0
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Q2 : 0.33
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Q1 : \RepU
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"""
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es = []
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for e in eval_df["Eleve"].unique():
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eleve = {"Nom":e}
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e_quest = quest_df[quest_df["Eleve"] == e]
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eleve["quest"] = e_quest
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e_exo = exo_df[exo_df["Eleve"] == e]
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#e_df = ds_df[ds_df["Eleve"] == e][["Exercice", "Question", "Bareme", "Commentaire", "Niveau", "Mark", "Latex_rep"]]
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eleve["Total"] = eval_df[eval_df["Eleve"]==e].iloc[0]
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exos = []
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for exo in e_exo["Exercice"].unique():
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ex = {"Nom":exo}
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ex["Total"] = e_exo[e_exo["Exercice"]==exo].iloc[0]
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ex["Questions"] = e_quest[e_quest["Exercice"] == exo]
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exos.append(ex)
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eleve["Exercices"] = exos
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es.append(eleve)
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return es
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# -----------------------------
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# Reglages pour 'vim'
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# vim:set autoindent expandtab tabstop=4 shiftwidth=4:
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# cursor: 16 del
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