661 lines
62 KiB
Plaintext
661 lines
62 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Exploration des résultats des 302"
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import sqlite3\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"from math import ceil\n",
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"import seaborn as sns\n",
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline\n",
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"from pprint import pprint"
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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": 2,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"db = \"recopytex.db\"\n",
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"conn = sqlite3.connect(db)\n",
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"c = conn.cursor()"
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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": 3,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"tribe_name = \"302\""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Id de la classe de 302"
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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": 4,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"tribe_id = c.execute(\"SELECT id from tribe WHERE tribe.name == ?\", (tribe_name,)).fetchone()[0]"
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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": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1\n"
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]
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}
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],
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"source": [
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"print(tribe_id)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Evaluations disponibles"
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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": 6,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"evals = c.execute(\"SELECT id, name from eval WHERE eval.tribe_id == ?\", (tribe_id,))"
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[(1, 'DS1 mise en jambe')]"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"evals.fetchmany()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## DS 1 mise en jambre"
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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": 8,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"eval_id = 1"
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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": 9,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"questions_scores = pd.read_sql_query(\"SELECT student.name, student.surname, score.value, question.competence\\\n",
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" FROM score\\\n",
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" JOIN question ON score.question_id==question.id \\\n",
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" JOIN exercise ON question.exercise_id==exercise.id \\\n",
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" JOIN eval ON exercise.eval_id==eval.id \\\n",
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" JOIN student ON score.student_id==student.id\\\n",
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" WHERE eval.id == (?)\",\n",
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" conn,\n",
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" params = (eval_id,))"
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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": 10,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"questions_scores = questions_scores[questions_scores[\"value\"]!='']"
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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": 11,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def note2score(x):\n",
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" if x[\"value\"] == '.':\n",
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" return 0\n",
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" if x[\"value\"] not in [0, 1, 2, 3]:\n",
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" raise ValueError(f\"The evaluation is out of range: {x['value']} at {x}\")\n",
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" return x[\"value\"]"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"questions_scores[\"score\"] = questions_scores.apply(note2score, axis=1)"
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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": 13,
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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>\n",
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" .dataframe thead tr:only-child th {\n",
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" text-align: right;\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: left;\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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"</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>name</th>\n",
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" <th>surname</th>\n",
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" <th>value</th>\n",
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" <th>competence</th>\n",
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" <th>score</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>0</th>\n",
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" <td>ABDALLAH ALLAOUI</td>\n",
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" <td>Taiassima</td>\n",
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" <td>1</td>\n",
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" <td>Cher</td>\n",
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" <td>1</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>ABDALLAH ALLAOUI</td>\n",
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" <td>Taiassima</td>\n",
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" <td>2</td>\n",
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" <td>Cal</td>\n",
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" <td>2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>ABDALLAH ALLAOUI</td>\n",
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" <td>Taiassima</td>\n",
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" <td>.</td>\n",
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" <td>Cal</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>ADANI</td>\n",
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" <td>Ismou</td>\n",
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" <td>2</td>\n",
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" <td>Cher</td>\n",
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" <td>2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>ADANI</td>\n",
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" <td>Ismou</td>\n",
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" <td>2</td>\n",
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" <td>Cal</td>\n",
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" <td>2</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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" name surname value competence score\n",
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"0 ABDALLAH ALLAOUI Taiassima 1 Cher 1\n",
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"1 ABDALLAH ALLAOUI Taiassima 2 Cal 2\n",
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"2 ABDALLAH ALLAOUI Taiassima . Cal 0\n",
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"3 ADANI Ismou 2 Cher 2\n",
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"4 ADANI Ismou 2 Cal 2"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"questions_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": 14,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"questions_scores[\"fullname\"] = questions_scores[\"name\"] + \" \" + questions_scores[\"surname\"]"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def score_mean(x):\n",
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" mean = np.mean(x)\n",
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" return round(mean, 0)\n",
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"\n",
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"score_mean.__name__ = \"Moyenne discrète\""
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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": 16,
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"metadata": {},
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"outputs": [],
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"source": [
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"report_comp = pd.pivot_table(questions_scores,\n",
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" index=[\"fullname\"],\n",
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" columns = ['competence'],\n",
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" values = [\"score\"],\n",
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" aggfunc = [score_mean])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Applatissement du nom des colonnes"
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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": 17,
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"metadata": {},
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"outputs": [],
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"source": [
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"report_comp.columns = report_comp.columns.levels[-1]"
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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": 18,
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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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||
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"<style>\n",
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" .dataframe thead tr:only-child th {\n",
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" text-align: right;\n",
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" }\n",
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"\n",
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||
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" .dataframe thead th {\n",
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" text-align: left;\n",
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" }\n",
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"\n",
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||
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" .dataframe tbody tr th {\n",
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||
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" vertical-align: top;\n",
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" }\n",
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"</style>\n",
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||
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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>competence</th>\n",
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" <th>Cal</th>\n",
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" <th>Cher</th>\n",
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" <th>Com</th>\n",
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" <th>Rai</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>fullname</th>\n",
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" <th></th>\n",
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" <th></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>ABDALLAH ALLAOUI Taiassima</th>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>ADANI Ismou</th>\n",
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|
|
" <td>1</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>AHAMADA Dhoulkamal</th>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>AHAMADI Asbahati</th>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>AHAMADI OUSSENI Ansufiddine</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>AHAMED Fayadhi</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>AHMED SAID Hadaïta</th>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>ALI MADI Anissa</th>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>ALI Raydel</th>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>ATTOUMANE ALI Fatima</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>BACHIROU Elzame</th>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>BINALI Zalida</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>BOINA Abdillah Mze Limassi</th>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>BOUDRA Zaankidine</th>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>HALADI Asna</th>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>HALIDI Soibrata</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>HAMEDALY Doulkifly</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>IBRAHIM Nassur</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>INOUSSA Anchoura</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>MOHAMED Nadia</th>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>MOUHOUDHOIRE Izak</th>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>MOUSSRI Bakari</th>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>SAKOTRA Claudiana</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>0</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>SAÏD Fatoumia</th>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <th>TOUFAIL Salahou</th>\n",
|
||
|
|
" <td>1</td>\n",
|
||
|
|
" <td>2</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" <td>3</td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" </tbody>\n",
|
||
|
|
"</table>\n",
|
||
|
|
"</div>"
|
||
|
|
],
|
||
|
|
"text/plain": [
|
||
|
|
"competence Cal Cher Com Rai\n",
|
||
|
|
"fullname \n",
|
||
|
|
"ABDALLAH ALLAOUI Taiassima 2 2 2 2\n",
|
||
|
|
"ADANI Ismou 1 2 1 2\n",
|
||
|
|
"AHAMADA Dhoulkamal 0 3 1 0\n",
|
||
|
|
"AHAMADI Asbahati 3 3 3 3\n",
|
||
|
|
"AHAMADI OUSSENI Ansufiddine 1 1 1 0\n",
|
||
|
|
"AHAMED Fayadhi 1 3 2 1\n",
|
||
|
|
"AHMED SAID Hadaïta 2 3 3 3\n",
|
||
|
|
"ALI MADI Anissa 2 3 2 3\n",
|
||
|
|
"ALI Raydel 3 2 2 2\n",
|
||
|
|
"ATTOUMANE ALI Fatima 1 1 0 0\n",
|
||
|
|
"BACHIROU Elzame 0 2 1 0\n",
|
||
|
|
"BINALI Zalida 1 2 2 0\n",
|
||
|
|
"BOINA Abdillah Mze Limassi 2 2 2 3\n",
|
||
|
|
"BOUDRA Zaankidine 0 0 0 0\n",
|
||
|
|
"HALADI Asna 2 3 3 3\n",
|
||
|
|
"HALIDI Soibrata 1 2 2 0\n",
|
||
|
|
"HAMEDALY Doulkifly 1 0 1 1\n",
|
||
|
|
"IBRAHIM Nassur 1 2 1 1\n",
|
||
|
|
"INOUSSA Anchoura 1 2 2 2\n",
|
||
|
|
"MOHAMED Nadia 0 1 0 0\n",
|
||
|
|
"MOUHOUDHOIRE Izak 0 1 0 0\n",
|
||
|
|
"MOUSSRI Bakari 0 2 1 1\n",
|
||
|
|
"SAKOTRA Claudiana 1 0 1 0\n",
|
||
|
|
"SAÏD Fatoumia 2 3 2 3\n",
|
||
|
|
"TOUFAIL Salahou 1 2 3 3"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 18,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"report_comp"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 32,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
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||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.figure.Figure at 0x7f528777cc88>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure(figsize=(10, 10))\n",
|
||
|
|
"ax = sns.heatmap(report_comp, cmap='YlOrRd', linewidths=.5)\n",
|
||
|
|
"ax.tick_params(labelbottom='on',labeltop='on')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.6.2"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|