Feat: Base for student exploration
This commit is contained in:
parent
1fc7270bed
commit
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@ -1,5 +1,5 @@
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#!/usr/bin/env python
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# encoding: utf-8
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from .csv_extraction import flat_clear_csv
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from .csv_extraction import flat_df_students, flat_df_for
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from .df_marks_manip import pp_q_scores
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@ -8,6 +8,7 @@ from .config import NO_ST_COLUMNS, COLUMNS, VALIDSCORE
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pd.set_option("Precision", 2)
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def try_replace(x, old, new):
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try:
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return str(x).replace(old, new)
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@ -26,8 +27,10 @@ def extract_students(df, no_student_columns=NO_ST_COLUMNS.values()):
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return students
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def flat_df_students(df, no_student_columns=NO_ST_COLUMNS.values()):
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""" Flat the ws for students
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def flat_df_students(
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df, no_student_columns=NO_ST_COLUMNS.values(), postprocessing=True
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):
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""" Flat the dataframe by returning a dataframe with on student on each line
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:param df: the dataframe (one row per questions)
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:param no_student_columns: columns that are not students
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@ -52,18 +55,45 @@ def flat_df_students(df, no_student_columns=NO_ST_COLUMNS.values()):
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value_name=COLUMNS["score"],
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).dropna(subset=[COLUMNS["score"]])
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)
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if postprocessing:
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return postprocess(pd.concat(scores))
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return pd.concat(scores)
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def flat_clear_csv(csv_df, no_student_columns=NO_ST_COLUMNS.values()):
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""" Flat and clear the dataframe extracted from csv
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def flat_df_for(
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df, student, no_student_columns=NO_ST_COLUMNS.values(), postprocessing=True
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):
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""" Extract the data only for one student
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:param csv_df: data frame read from csv
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:param df: the dataframe (one row per questions)
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:param no_student_columns: columns that are not students
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:return: dataframe with one row per questions and students
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Columns of csv files:
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- NO_ST_COLUMNS meta data on questions
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- one for each students
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"""
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students = extract_students(df, no_student_columns)
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if student not in students:
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raise KeyError("This student is not in the table")
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st_df = df[list(no_student_columns) + [student]]
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st_df = st_df.rename(columns={student: COLUMNS["score"]}).dropna(
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subset=[COLUMNS["score"]]
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)
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if postprocessing:
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return postprocess(st_df)
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return st_df
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def postprocess(df):
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""" Postprocessing score dataframe
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- Replace na with an empty string
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- Replace "NOANSWER" with -1
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- Turn commas number to dot numbers
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"""
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df = flat_df_students(csv_df)
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df[COLUMNS["question"]].fillna("", inplace=True)
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df[COLUMNS["exercise"]].fillna("", inplace=True)
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@ -76,9 +106,8 @@ def flat_clear_csv(csv_df, no_student_columns=NO_ST_COLUMNS.values()):
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.apply(lambda x: try_replace(x, ",", "."))
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)
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df[COLUMNS["score_rate"]] = pd.to_numeric(
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df[COLUMNS["score_rate"]]
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.apply(lambda x: try_replace(x, ",", ".")),
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errors="coerce"
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df[COLUMNS["score_rate"]].apply(lambda x: try_replace(x, ",", ".")),
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errors="coerce",
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)
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return df
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@ -2,8 +2,20 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"execution_count": 1,
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"metadata": {
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"extensions": {
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"jupyter_dashboards": {
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"version": 1,
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"views": {
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"grid_default": {},
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"report_default": {
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"hidden": true
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}
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}
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}
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}
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},
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"outputs": [],
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"source": [
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"from IPython.display import Markdown as md\n",
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@ -11,7 +23,7 @@
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"import pandas as pd\n",
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"from pathlib import Path\n",
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"from datetime import datetime\n",
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"from recopytex import flat_clear_csv, pp_q_scores\n",
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"from recopytex import flat_df_students, pp_q_scores\n",
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"#import prettytable as pt\n",
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"%matplotlib inline"
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]
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@ -20,6 +32,17 @@
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"extensions": {
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"version": 1,
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"views": {
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"grid_default": {},
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"report_default": {
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"hidden": true
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}
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}
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}
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},
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"tags": [
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"parameters"
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]
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@ -35,7 +58,19 @@
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"hidden": false
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}
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}
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}
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}
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},
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"outputs": [
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{
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"data": {
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@ -59,107 +94,65 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"execution_count": 5,
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"metadata": {
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"extensions": {
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"hidden": true
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}
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}
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}
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}
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},
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"outputs": [],
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"source": [
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"stack_scores = pd.read_csv(csv_file, encoding=\"latin_1\")\n",
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"scores = flat_clear_csv(stack_scores).dropna(subset=[\"Score\"])\n",
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"scores = flat_df_students(stack_scores).dropna(subset=[\"Score\"])\n",
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"scores = pp_q_scores(scores)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th>Note</th>\n",
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" <th>Bareme</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>Exercice</th>\n",
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" <th>Eleve</th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th rowspan=\"5\" valign=\"top\">1</th>\n",
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" <th>ABDOU Asmahane</th>\n",
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" <td>3.67</td>\n",
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" <td>6.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>ABOU Roihim</th>\n",
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" <td>0.00</td>\n",
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" <td>6.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>AHMED BOINALI Kouraichia</th>\n",
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" <td>1.33</td>\n",
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" <td>6.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>AHMED Rahada</th>\n",
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" <td>2.67</td>\n",
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" <td>6.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>ALI SAID Anchourati</th>\n",
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" <td>0.00</td>\n",
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" <td>6.0</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Note Bareme\n",
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"Exercice Eleve \n",
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"1 ABDOU Asmahane 3.67 6.0\n",
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" ABOU Roihim 0.00 6.0\n",
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" AHMED BOINALI Kouraichia 1.33 6.0\n",
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" AHMED Rahada 2.67 6.0\n",
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" ALI SAID Anchourati 0.00 6.0"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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"execution_count": 6,
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"metadata": {
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"report_default": {
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"hidden": true
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}
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}
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}
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}
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],
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},
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"outputs": [],
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"source": [
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"exercises_scores = scores.groupby([\"Exercice\", \"Eleve\"]).agg({\"Note\": \"sum\", \"Bareme\": \"sum\"})\n",
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"exercises_scores.head()"
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"#exercises_scores.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"execution_count": 7,
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"metadata": {
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"extensions": {
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"version": 1,
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"views": {
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"grid_default": {},
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"report_default": {
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"hidden": false
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}
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}
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}
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},
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"outputs": [
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{
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"data": {
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@ -195,117 +188,117 @@
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" <tr>\n",
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" <th>ABDOU Asmahane</th>\n",
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" <td>5.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>ABOU Roihim</th>\n",
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" <td>0.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>AHMED BOINALI Kouraichia</th>\n",
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" <td>2.67</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>AHMED Rahada</th>\n",
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" <td>6.33</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>ALI SAID Anchourati</th>\n",
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" <td>0.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>ASSANE Noussouraniya</th>\n",
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" <td>4.67</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>BACAR Issiaka</th>\n",
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" <td>0.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>BACAR Samina</th>\n",
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" <td>3.67</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>CHAIHANE Said</th>\n",
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" <td>5.33</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>COMBO Houzaimati</th>\n",
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" <td>5.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>DAOUD Anzilati</th>\n",
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" <td>5.17</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>DAOUD Talaenti</th>\n",
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" <td>5.67</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>DARKAOUI Rachma</th>\n",
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" <td>5.67</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>DHAKIOINE Nabaouya</th>\n",
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" <td>1.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>DJANFAR Soioutinour</th>\n",
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" <td>5.33</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>DRISSA Ibrahim</th>\n",
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" <td>0.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>HACHIM SIDI Assani</th>\n",
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" <td>7.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>HAFIDHUI Zalifa</th>\n",
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" <td>5.67</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>HOUMADI Marie</th>\n",
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" <td>6.67</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>HOUMADI Sania</th>\n",
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" <td>5.33</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>MAANDHUI Halouoi</th>\n",
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" <td>7.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>MASSONDI Nasma</th>\n",
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" <td>7.33</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>SAIDALI Irichad</th>\n",
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" <td>5.00</td>\n",
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" <td>12.0</td>\n",
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" <td>12</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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@ -314,32 +307,32 @@
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"text/plain": [
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" Note Bareme\n",
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"Eleve \n",
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"ABDOU Asmahane 5.00 12.0\n",
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"ABOU Roihim 0.00 12.0\n",
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"AHMED BOINALI Kouraichia 2.67 12.0\n",
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"AHMED Rahada 6.33 12.0\n",
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"ALI SAID Anchourati 0.00 12.0\n",
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"ASSANE Noussouraniya 4.67 12.0\n",
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"BACAR Issiaka 0.00 12.0\n",
|
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"BACAR Samina 3.67 12.0\n",
|
||||
"CHAIHANE Said 5.33 12.0\n",
|
||||
"COMBO Houzaimati 5.00 12.0\n",
|
||||
"DAOUD Anzilati 5.17 12.0\n",
|
||||
"DAOUD Talaenti 5.67 12.0\n",
|
||||
"DARKAOUI Rachma 5.67 12.0\n",
|
||||
"DHAKIOINE Nabaouya 1.00 12.0\n",
|
||||
"DJANFAR Soioutinour 5.33 12.0\n",
|
||||
"DRISSA Ibrahim 0.00 12.0\n",
|
||||
"HACHIM SIDI Assani 7.00 12.0\n",
|
||||
"HAFIDHUI Zalifa 5.67 12.0\n",
|
||||
"HOUMADI Marie 6.67 12.0\n",
|
||||
"HOUMADI Sania 5.33 12.0\n",
|
||||
"MAANDHUI Halouoi 7.00 12.0\n",
|
||||
"MASSONDI Nasma 7.33 12.0\n",
|
||||
"SAIDALI Irichad 5.00 12.0"
|
||||
"ABDOU Asmahane 5.00 12\n",
|
||||
"ABOU Roihim 0.00 12\n",
|
||||
"AHMED BOINALI Kouraichia 2.67 12\n",
|
||||
"AHMED Rahada 6.33 12\n",
|
||||
"ALI SAID Anchourati 0.00 12\n",
|
||||
"ASSANE Noussouraniya 4.67 12\n",
|
||||
"BACAR Issiaka 0.00 12\n",
|
||||
"BACAR Samina 3.67 12\n",
|
||||
"CHAIHANE Said 5.33 12\n",
|
||||
"COMBO Houzaimati 5.00 12\n",
|
||||
"DAOUD Anzilati 5.17 12\n",
|
||||
"DAOUD Talaenti 5.67 12\n",
|
||||
"DARKAOUI Rachma 5.67 12\n",
|
||||
"DHAKIOINE Nabaouya 1.00 12\n",
|
||||
"DJANFAR Soioutinour 5.33 12\n",
|
||||
"DRISSA Ibrahim 0.00 12\n",
|
||||
"HACHIM SIDI Assani 7.00 12\n",
|
||||
"HAFIDHUI Zalifa 5.67 12\n",
|
||||
"HOUMADI Marie 6.67 12\n",
|
||||
"HOUMADI Sania 5.33 12\n",
|
||||
"MAANDHUI Halouoi 7.00 12\n",
|
||||
"MASSONDI Nasma 7.33 12\n",
|
||||
"SAIDALI Irichad 5.00 12"
|
||||
]
|
||||
},
|
||||
"execution_count": 15,
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -351,8 +344,20 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"execution_count": 8,
|
||||
"metadata": {
|
||||
"extensions": {
|
||||
"jupyter_dashboards": {
|
||||
"version": 1,
|
||||
"views": {
|
||||
"grid_default": {},
|
||||
"report_default": {
|
||||
"hidden": false
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
|
|
@ -368,7 +373,7 @@
|
|||
"Name: Note, dtype: float64"
|
||||
]
|
||||
},
|
||||
"execution_count": 7,
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -379,16 +384,38 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"execution_count": 9,
|
||||
"metadata": {
|
||||
"extensions": {
|
||||
"jupyter_dashboards": {
|
||||
"version": 1,
|
||||
"views": {
|
||||
"grid_default": {},
|
||||
"report_default": {
|
||||
"hidden": false
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"/usr/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
|
||||
" return f(*args, **kwds)\n",
|
||||
"/usr/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
|
||||
" return f(*args, **kwds)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f0ae61e5cf8>"
|
||||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f104b318090>"
|
||||
]
|
||||
},
|
||||
"execution_count": 8,
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
},
|
||||
|
|
@ -413,13 +440,44 @@
|
|||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"extensions": {
|
||||
"jupyter_dashboards": {
|
||||
"version": 1,
|
||||
"views": {
|
||||
"grid_default": {},
|
||||
"report_default": {
|
||||
"hidden": true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"celltoolbar": "Tags",
|
||||
"extensions": {
|
||||
"jupyter_dashboards": {
|
||||
"activeView": "grid_default",
|
||||
"version": 1,
|
||||
"views": {
|
||||
"grid_default": {
|
||||
"cellMargin": 10,
|
||||
"defaultCellHeight": 20,
|
||||
"maxColumns": 12,
|
||||
"name": "grid",
|
||||
"type": "grid"
|
||||
},
|
||||
"report_default": {
|
||||
"name": "report",
|
||||
"type": "report"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
|
|
@ -435,7 +493,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.3"
|
||||
"version": "3.7.4"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
|
|
|||
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Load Diff
Loading…
Reference in New Issue