{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e328e5fa-ee7e-4045-9164-624573b73562",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1\n",
      "1    3\n",
      "2    7\n",
      "3    8\n",
      "dtype: int64\n",
      "7\n",
      "int64\n",
      "[1 3 7 8]\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "s1 = pd.Series([1, 3, 7, 8])\n",
    "print(s1)\n",
    "print(s1[2])\n",
    "print(s1.dtype)\n",
    "print(s1.values)\n",
    "print(s1.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4f15f4f9-2580-41c3-a26c-80152d739ab5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         0     1\n",
      "0     Paul  1974\n",
      "1  Quentin  1991\n",
      "2     Aude  1987\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "dataframe = pd.DataFrame(data=[[\"Paul\", 1974], [\"Quentin\", 1991], [\"Aude\", 1987]])\n",
    "print(dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1f2c617f-3ee6-4254-ba1d-1c517e4be013",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Alain\n",
      "Index(['U1', 'U2', 'U3', 'U4', 'U5', 'U6'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "s1 = pd.Series(data=[\"Alain\", \"Lucie\", \"Gilles\", \"André\", \"Zoé\", \"Paul\"], index=[\"U1\", \"U2\", \"U3\", \"U4\", \"U5\", \"U6\"])\n",
    "print(s1[\"U1\"])  # Affiche la valeur \"Alain\" en extrayant depuis l'index \"U1\"\n",
    "print(s1.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "008357ca-4a95-48bb-a411-aaf2b6182ae2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1\n",
      "1    3\n",
      "2    2\n",
      "3    3\n",
      "dtype: int64\n",
      "0    False\n",
      "1    False\n",
      "2     True\n",
      "3     True\n",
      "dtype: bool\n",
      "False\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "s1 = pd.Series([1, 3, 7, 8])\n",
    "print(s1 % 5)\n",
    "print(s1 * 2 - 7 > 4)\n",
    "print(8 in s1)  # C'est faux car \"in\" cherche uniquement dans l'index (comme avec les dict)\n",
    "print(8 in s1.values)  # C'est vrai car la valeur 8 est présente dans le tableau de valeurs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b4cb5f27-485d-4d79-bf4b-a6dcbfc906b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "19 in {\"plop\": 19, \"plip\": 99}"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}