{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "with open('myjournal.csv','w',newline='') as fichiercsv:\n",
    "    writer=csv.writer(fichiercsv)\n",
    "    writer.writerow(['Date', 'Cahier', 'événement', 'heures_travail'])\n",
    "    writer.writerow(['04/01/2022', 'projet_arduino', 'rdv_UCA', '8'])\n",
    "    writer.writerow(['05/01/2022', 'partition_bach', 'zoom_XR', '12'])\n",
    "    writer.writerow(['06/01/2022', 'cello_vocalise', 'rdv_CIRM', '9'])\n",
    "    writer.writerow(['07/01/2022', 'formation_éthique', 'cours_en_ligne', '14'])\n",
    "    writer.writerow(['08/01/2022', 'projet_collège', '', '13'])\n",
    "    writer.writerow(['09/01/2022', 'partition_bach', 'zoom_prof', '8'])\n",
    "    writer.writerow(['10/01/2022', 'cello_vocalise', 'répétition_CRR',  '6'])\n",
    "    writer.writerow(['11/01/2022', 'formation_articles', 'concert_CRR', '10'])\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "04/01/2022 projet_arduino\n",
      "05/01/2022 partition_bach\n",
      "06/01/2022 cello_vocalise\n",
      "07/01/2022 formation_éthique\n",
      "08/01/2022 projet_collège\n",
      "09/01/2022 partition_bach\n",
      "10/01/2022 cello_vocalise\n",
      "11/01/2022 formation_articles\n"
     ]
    }
   ],
   "source": [
    "\n",
    " with open('myjournal.csv', newline='') as fichiercsv:\n",
    "     reader = csv.DictReader(fichiercsv)\n",
    "     for row in reader:\n",
    "         print(row['Date'], row['Cahier'])\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rdv_UCA\n",
      "zoom_XR\n",
      "rdv_CIRM\n",
      "cours_en_ligne\n",
      "\n",
      "zoom_prof\n",
      "répétition_CRR\n",
      "concert_CRR\n"
     ]
    }
   ],
   "source": [
    "\n",
    " with open('myjournal.csv', newline='') as fichiercsv:\n",
    "     reader = csv.DictReader(fichiercsv)\n",
    "     for row in reader:\n",
    "         print(row['événement'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Date,Cahier,événement,heures_travail\\n']\n",
      "['04/01/2022,projet_arduino,rdv_UCA,8\\n', '05/01/2022,partition_bach,zoom_XR,12\\n', '06/01/2022,cello_vocalise,rdv_CIRM,9\\n', '07/01/2022,formation_éthique,cours_en_ligne,14\\n', '08/01/2022,projet_collège,,13\\n', '09/01/2022,partition_bach,zoom_prof,8\\n', '10/01/2022,cello_vocalise,répétition_CRR,6\\n', '11/01/2022,formation_articles,concert_CRR,10\\n']\n"
     ]
    }
   ],
   "source": [
    "with open('myjournal.csv') as file:\n",
    "    content = file.readlines()\n",
    "header = content[:1]\n",
    "rows = content[1:]\n",
    "print(header)\n",
    "print(rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Cahier</th>\n",
       "      <th>événement</th>\n",
       "      <th>heures_travail</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>04/01/2022</td>\n",
       "      <td>projet_arduino</td>\n",
       "      <td>rdv_UCA</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>05/01/2022</td>\n",
       "      <td>partition_bach</td>\n",
       "      <td>zoom_XR</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>06/01/2022</td>\n",
       "      <td>cello_vocalise</td>\n",
       "      <td>rdv_CIRM</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>07/01/2022</td>\n",
       "      <td>formation_éthique</td>\n",
       "      <td>cours_en_ligne</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>08/01/2022</td>\n",
       "      <td>projet_collège</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>09/01/2022</td>\n",
       "      <td>partition_bach</td>\n",
       "      <td>zoom_prof</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10/01/2022</td>\n",
       "      <td>cello_vocalise</td>\n",
       "      <td>répétition_CRR</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>11/01/2022</td>\n",
       "      <td>formation_articles</td>\n",
       "      <td>concert_CRR</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date              Cahier       événement  heures_travail\n",
       "0  04/01/2022      projet_arduino         rdv_UCA               8\n",
       "1  05/01/2022      partition_bach         zoom_XR              12\n",
       "2  06/01/2022      cello_vocalise        rdv_CIRM               9\n",
       "3  07/01/2022   formation_éthique  cours_en_ligne              14\n",
       "4  08/01/2022      projet_collège             NaN              13\n",
       "5  09/01/2022      partition_bach       zoom_prof               8\n",
       "6  10/01/2022      cello_vocalise  répétition_CRR               6\n",
       "7  11/01/2022  formation_articles     concert_CRR              10"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data= pd.read_csv(\"myjournal.csv\")\n",
    "data\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'Cahier', 'événement', 'heures_travail'], dtype='object')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('cello_vocalise', 7.5)\n",
      "('formation_articles', 10.0)\n",
      "('formation_éthique', 14.0)\n",
      "('partition_bach', 10.0)\n",
      "('projet_arduino', 8.0)\n",
      "('projet_collège', 13.0)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "data= pd.read_csv(\"myjournal.csv\")\n",
    "\n",
    "groupby_gender = data.groupby('Cahier')\n",
    "for gender, value in groupby_gender['heures_travail']:\n",
    "     print((gender, value.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10.0\n",
      "80\n",
      "14\n",
      "6\n",
      "8\n",
      "9.5\n",
      "2.7774602993176543\n",
      "7.714285714285714\n"
     ]
    }
   ],
   "source": [
    "data= pd.read_csv(\"myjournal.csv\")\n",
    "\n",
    "mean1 = data['heures_travail'].mean()\n",
    "sum1 = data['heures_travail'].sum()\n",
    "max1 = data['heures_travail'].max()\n",
    "min1 = data['heures_travail'].min()\n",
    "count1 = data['heures_travail'].count()\n",
    "median1 = data['heures_travail'].median() \n",
    "std1 = data['heures_travail'].std() \n",
    "var1 = data['heures_travail'].var() \n",
    "\n",
    "print(mean1)\n",
    "print(sum1)\n",
    "print(max1)\n",
    "print(min1)\n",
    "print(count1)\n",
    "print(median1)\n",
    "print(std1)\n",
    "print(var1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{partition_bach: 2 } {# of rows: 2 }\n"
     ]
    }
   ],
   "source": [
    "my_reader = open('myjournal.csv', encoding = 'utf-8')\n",
    "rows = 0\n",
    "partition_bach = 0\n",
    "\n",
    "for record in my_reader:\n",
    "    if record.count('partition_bach') > 0:\n",
    "        rows += 1\n",
    "        partition_bach += record.count('partition_bach')\n",
    "\n",
    "print('{partition_bach: %d } {# of rows: %d }' % (partition_bach, rows))\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{projet: 2 } {# of rows: 2 }\n"
     ]
    }
   ],
   "source": [
    "my_reader = open('myjournal.csv', encoding = 'utf-8')\n",
    "rows = 0\n",
    "projet = 0\n",
    "\n",
    "for record in my_reader:\n",
    "    if record.count('projet') > 0:\n",
    "        rows += 1\n",
    "        projet += record.count('projet')\n",
    "\n",
    "print('{projet: %d } {# of rows: %d }' % (projet, rows))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{arduino: 1 } {# of rows: 1 }\n"
     ]
    }
   ],
   "source": [
    "my_reader = open('myjournal.csv', encoding = 'utf-8')\n",
    "rows = 0\n",
    "arduino = 0\n",
    "\n",
    "for record in my_reader:\n",
    "    if record.count('arduino') > 0:\n",
    "        rows += 1\n",
    "        arduino += record.count('arduino')\n",
    "\n",
    "print('{arduino: %d } {# of rows: %d }' % (arduino, rows))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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