Conclusion.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/MartinBordes/Python_2A/blob/main/Conclusion.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TwJnJMVGzwQC"
      },
      "source": [
        "# 1 - Préparation du traitement des données"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "e5tK70FzzYRO"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "import time\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "from sklearn.pipeline import make_pipeline \n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "t = time.time()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3Ro6jkYQzYRS"
      },
      "outputs": [],
      "source": [
        "NB_DATA_140 = 50000"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6vjaogXF1gV2"
      },
      "source": [
        "Nous avons enregistré plusieurs versions des deux bases de données préprocessées (Sentiment140, base de tweets webscrapés) de manières différentes avec des combinaisons différentes des arguments *stop_words*, *lemmatization* et *negation*. Nous créons ici une fonction *data* qui, en fonction des paramètres de *preprocessing* choisis par l'utilisateur, chargera les deux *Dataframes* (sentiment140 et tweets scrapés) correspondants."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "q--nOp-ezYRT"
      },
      "outputs": [],
      "source": [
        "def data(stop_words, lemmatization, negation):\n",
        "    file = \"train\"\n",
        "    if stop_words:\n",
        "        file += \"_stop\"\n",
        "    if lemmatization:\n",
        "        file += \"_lemm\"\n",
        "    if negation:\n",
        "        file += \"_neg\"\n",
        "    df_140 = pd.read_pickle(os.path.join(\"data\", \"Sentiment140\", file + \".bz2\")).sample(NB_DATA_140, random_state=1234).reset_index(drop=True)\n",
        "\n",
        "    file = \"web\"\n",
        "    if stop_words:\n",
        "        file += \"_stop\"\n",
        "    if lemmatization:\n",
        "        file += \"_lemm\"\n",
        "    if negation:\n",
        "        file += \"_neg\"\n",
        "    df_web = pd.read_csv(os.path.join(\"data\", \"webcsv\", file + \".csv\"))\n",
        "\n",
        "    X_140 = df_140.text.to_list()\n",
        "    y_140 = df_140.sentiment.to_list()\n",
        "\n",
        "    X_web = df_web.Text.to_list()\n",
        "    \n",
        "    return X_140, y_140, X_web, df_web"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6ynSmwbE2HO1"
      },
      "source": [
        "Les études réalisées sur les modèles *Gaussian Naive Bayes*, *Multinomial Naive Bayes*, et *Logistic Regression*, nous ont permis de conclure que le modèle *Logistic Regression* couplé à la méthode de *feature extraction* *TfidfVectorizer avec ngram* donnait les meilleurs résultats. De plus, les études menées nous ont permis de conclure que la combinaison de paramètres de preprocessing la plus pertinente est la suivante : *stop_words=False*, *lemmatization=True*, *negation=False*.\n",
        "\n",
        "Nous utiliserons donc les outils suivants pour traiter notre base webscrapée :\n",
        "\n",
        "- modèle : LogisticRegression(max_iter=1000000, random_state=1234)\n",
        "- vectorizer : TfidfVectorizer(max_features=2725, ngram_range=(1, 2))\n",
        "- combinaison : stop_words=False, lemmatization=True, negation=False"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "T0j6ZiL4zYRU"
      },
      "outputs": [],
      "source": [
        "model = make_pipeline(TfidfVectorizer(max_features=2725, ngram_range=(1,2)), LogisticRegression(max_iter=1000000, random_state=1234))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9xmD7e1J29VK"
      },
      "source": [
        "# 2 - Application du modèle"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0RYP8AWD3RBy"
      },
      "source": [
        "Nous choisissons nos arguments de *preprocessing*, et nous appelons les bases correspondantes à l’aide de la fonction *data*."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9z-DUTYlzYRU"
      },
      "outputs": [],
      "source": [
        "STOP_WORDS = False\n",
        "LEMMATIZATION = True\n",
        "NEGATION = False\n",
        "X_140, y_140, X_web, df_web = data(STOP_WORDS, LEMMATIZATION, NEGATION)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K2yih5zpuJf0"
      },
      "source": [
        "On entraîne le modèle sur l'échantillon de la base Sentiment140 préprocessée selon la combinaison (*stop_words*, *lemmatization*, *negation*) choisie. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pQCSwln0uJf1",
        "outputId": "803b448f-60ad-4476-f803-add1aa7600cc"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Pipeline(steps=[('tfidfvectorizer',\n",
              "                 TfidfVectorizer(max_features=2725, ngram_range=(1, 2))),\n",
              "                ('logisticregression',\n",
              "                 LogisticRegression(max_iter=1000000, random_state=1234))])"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "model.fit(X_140, y_140)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q-KbxwGU3Vbh"
      },
      "source": [
        "Une fois le modèle entraîné, il ne nous reste plus qu'à l'appliquer à notre base de tweets webscrapés. Ces tweets sont des commentaires faits par des utilisateurs de Tweeter à propos des films Dune et Space Jam.\n",
        "\n",
        "L'idée de cette étude est devoir si l'un des deux films a connu plus de succès que l'autre, en identifiant le succès d'un film à la proportion de commentaires positifs qu'il a suscités chez les utilisateurs de Tweeter.\n",
        "\n",
        "A priori, nous nous attendons à trouver que le film Dune a connu plus de succès que le film Space Jam. En particulier, nous nous attendons à trouver que Dune a connu un franc succès, alors que Space Jam a plutôt déçu."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "p06ryRehzYRV"
      },
      "outputs": [],
      "source": [
        "y_web = model.predict(X_web)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wsrk8S9Y3wUN"
      },
      "source": [
        "Une fois la prédiction effectuée par le modèle, il convient de l'ajouter au *DataFrame* sur lequel nous travaillons."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ZarsmNr0zYRV"
      },
      "outputs": [],
      "source": [
        "df_web['sentiment'] = y_web"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "YqhssjgWuJf4"
      },
      "outputs": [],
      "source": [
        "df_web['sentiment'] = df_web['sentiment'].replace([0, 4], [\"Négatif\", \"Positif\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bSJS1Ed930UI"
      },
      "source": [
        "# 3 - Visualisation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5DONbxEauJf5"
      },
      "source": [
        "Lors de la phase de *scraping* des données, des tweets ont été récoltés pour les deux films, à des moments stratégiques : \n",
        "\n",
        "- pendant deux semaines après la sortie du premier trailer\n",
        "- pendant deux semaines après la sortie du deuxième trailer \n",
        "- pendant les deux semaines précédant la sortie du film, puis pendant les trois semaines suivant sa sortie en salle aux Etats-Unis "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-nyrnnsNzYRW",
        "outputId": "0ca9074b-a6e0-46bc-b9ad-679c7ae04940"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Text(0.5, 1.0, 'Sentiments exprimés (total)')]"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "sns.countplot(x='sentiment', data=df_web).set(title='Sentiments exprimés (total)')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HFcNPRbguJf6"
      },
      "source": [
        "Ce premier graphique montre que la base de tweets webscrapés contient une majorité de tweets positifs concernant les deux films étudiés. Cela laisse donc penser que dans l'ensemble, ces deux films étaient attendus sur la base d'a priori plutôt positifs, et qu'ils ont été plutôt appréciés par les personnes qui les ont vus."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gj0AO6vdzYRW",
        "outputId": "835daadf-88e3-4fa2-c753-1597425544bd"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Text(0.5, 1.0, 'Sentiments exprimés concernant chaque film')]"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "sns.histplot(x='Film', hue='sentiment', data=df_web).set(title=\"Sentiments exprimés concernant chaque film\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G6sW1bBRuJf7"
      },
      "source": [
        "Cet histogramme montre la répartition des sentiments pour les deux films. \n",
        "\n",
        "Attention: la fonction histplot ne stacke pas les résultats mais les superpose horizontalement. Ainsi, dans le graphique ci-dessus, les tweets négatifs sont indiqués en orange dans la légende mais apparaissent gris sur le graphique car la barre orange qui est derrière se superpose au bleu. On doit donc lire le graphique en considérant que si la barre positif est au-dessus de la barre négatif c'est-qu'il y a plus de positif que de négatif.\n",
        "\n",
        "\n",
        "Tout d'abord, il apparaît que Dune a beaucoup plus fait parler que Space Jam. De plus, Dune a suscité une majorité de commentaires positifs de la part des personnes qui ont tweeté à son propos. Space Jam a également reçu une majorité de commentaires positifs (la barre orange arrive au-dessus de la barre bleue) mais avec un ratio moins favorable que Dune.\n",
        "\n",
        "\n",
        "Pour plus de lisibilité, nous remplaçons les dates des périodes pendant lesquelles les tweets scrapés ont été émis, par leur correspondance en termes de sortie d'un trailer ou de sortie d'un film."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7JOHDqjhzYRW"
      },
      "outputs": [],
      "source": [
        "df_web = df_web.replace([\"['2021-10-08', '2021-10-09', '2021-10-10', '2021-10-11', '2021-10-12', '2021-10-13', '2021-10-14', '2021-10-15', '2021-10-16', '2021-10-17', '2021-10-18', '2021-10-19', '2021-10-20', '2021-10-21', '2021-10-22', '2021-10-23', '2021-10-24', '2021-10-25', '2021-10-26', '2021-10-27', '2021-10-28', '2021-10-29', '2021-10-30', '2021-10-31', '2021-11-01', '2021-11-02', '2021-11-03', '2021-11-04', '2021-11-05', '2021-11-06', '2021-11-07', '2021-11-08', '2021-11-09', '2021-11-10', '2021-11-11', '2021-11-12', '2021-11-13']\",\n",
        "                                                     \"['2021-07-03', '2021-07-04', '2021-07-05', '2021-07-06', '2021-07-07', '2021-07-08', '2021-07-09', '2021-07-10', '2021-07-11', '2021-07-12', '2021-07-13', '2021-07-14', '2021-07-15', '2021-07-16', '2021-07-17', '2021-07-18', '2021-07-19', '2021-07-20', '2021-07-21', '2021-07-22', '2021-07-23', '2021-07-24', '2021-07-25', '2021-07-26', '2021-07-27', '2021-07-28', '2021-07-29', '2021-07-30', '2021-07-31', '2021-08-01', '2021-08-02', '2021-08-03', '2021-08-04', '2021-08-05', '2021-08-06', '2021-08-07', '2021-08-08']\",\n",
        "                                                     \"['2020-09-09', '2020-09-10', '2020-09-11', '2020-09-12', '2020-09-13', '2020-09-14', '2020-09-15', '2020-09-16', '2020-09-17', '2020-09-18', '2020-09-19', '2020-09-20', '2020-09-21', '2020-09-22', '2020-09-23']\",\n",
        "                                                     \"['2021-07-22', '2021-07-23', '2021-07-24', '2021-07-25', '2021-07-26', '2021-07-27', '2021-07-28', '2021-07-29', '2021-07-30', '2021-07-31', '2021-08-01', '2021-08-02', '2021-08-03', '2021-08-04', '2021-08-05']\",\n",
        "                                                    \"['2021-04-03', '2021-04-04', '2021-04-05', '2021-04-06', '2021-04-07', '2021-04-08', '2021-04-09', '2021-04-10', '2021-04-11', '2021-04-12', '2021-04-13', '2021-04-14', '2021-04-15', '2021-04-16', '2021-04-17']\",\n",
        "                                                    \"['2021-06-09', '2021-06-10', '2021-06-11', '2021-06-12', '2021-06-13', '2021-06-14', '2021-06-15', '2021-06-16', '2021-06-17', '2021-06-18', '2021-06-19', '2021-06-20', '2021-06-21', '2021-06-22', '2021-06-23']\"],\n",
        "                                                    [\"Sortie Dune\", \"Sortie Space Jam\", \"Premier trailer Dune\", \"Second trailer Dune\",\"Premier trailer Space Jam\", \"Second trailer Space Jam\"])\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JZbq8ePIuJf7"
      },
      "source": [
        "A présent, nous allons nous intéresser à la perception qu'avaient les personnes qui ont tweeté sur ces films, aux différents moments de la sortie des films (du premier trailer à la sortie en salle)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6Kxeq6QMzYRX",
        "outputId": "7fe6d324-979a-4666-ba4b-2ca74cd714ce"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Text(0.5, 1.0, 'Évolution des sentiments exprimés sur le film Dune à chaque période')]"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, axs = plt.subplots(1, 1, figsize=(10, 5))\n",
        "sns.histplot(x='Time Range', hue='sentiment', data=df_web.loc[df_web['Film'] == 'dune']).set(title=\"Évolution des sentiments exprimés sur le film Dune à chaque période\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "plUo59gkuJf8"
      },
      "source": [
        "Tout d'abord, il apparaît que peu importe la période étudiée, Dune a suscité une majorité de tweets positifs.\n",
        "\n",
        "Cet histogramme montre que le film était positivement attendu par les utilisateurs de Tweeter qui se sont exprimé à ce propos. Il montre également que le second trailer a suscité moins de réactions que le premier. Enfin, il apparaît que la sortie du film en salle a énormément fait parler, avec une grande majorité de tweets positifs."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Hnpvf5vuzYRX",
        "outputId": "a4ca3fa7-40a0-41fa-c4ba-1799360a954b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Text(0.5, 1.0, 'Évolution des sentiments exprimés sur le film Space Jam 2 à chaque période')]"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, axs = plt.subplots(1, 1, figsize=(10, 5))\n",
        "sns.histplot(x='Time Range', hue='sentiment', data=df_web.loc[df_web['Film'] == 'space jam']).set(title=\"Évolution des sentiments exprimés sur le film Space Jam 2 à chaque période\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lSx-jgmguJf9"
      },
      "source": [
        "Les tendances sont assez similaires pour Space Jam, bien qu'elles soient beaucoup moins élogieuses que pour Dune. Par rapport à Dune, Space Jam a globalement suscité moins de réactions. \n",
        "\n",
        "La tendance principale qui se dégage est la suivante : peu importe la période étudiée, Space Jam a suscité une majorité de tweets positifs mais avec à chaque fois une proportion de tweets positifs sur le total de tweets publiés moins élevée que pour Dune.\n",
        "\n",
        "Ainsi, les utilisateurs de Tweeter qui se sont exprimé à propos de Space Jam avaient, en majorité, un a priori positif sur le film mais moins que ceux qui s'exprimaient à propos de Dune. Comme pour Dune, la sortie du deuxième trailer a suscité moins de réactions que la sortie du premier trailer, même si elle a tout de même confirmé l'a priori positif moins marqué que pour Dune. Un à priori qui était suggéré par les tweets relatifs à la sortie du premier trailer. \n",
        "\n",
        "Enfin, il apparaît que la sortie du film en salle a suscité beaucoup plus de réactions que les trailers, avec toujours une majorité de tweets positifs.\n",
        "\n",
        "Nos a priori semblent donc se confirmer : Dune semble avoir connu un franc succès, tandis que Space Jam a moins plu (même si la proportion de tweets positifs est supérieure à 1/2."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "27M6JflbuJf9"
      },
      "source": [
        "En vue d'améliorer la lisibilité des graphiques suivants, nous faisons en sorte de ne récupérer que le jour et le mois de la date de publication des tweets de notre base."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "S7rc94qQzYRY"
      },
      "outputs": [],
      "source": [
        "df_web['day'] = df_web['Datetime'].apply(np.vectorize(lambda string : string[5:10]))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-N8pyzyvzYRZ",
        "outputId": "1554d222-0f28-42e9-a474-5c0d63b7a44f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Text(0.5, 1.0, 'Évolution des sentiments exprimés sur le film Dune')]"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1800x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, axs = plt.subplots(1, 1, figsize=(25, 7))\n",
        "sns.histplot(x='day', hue='sentiment', data=df_web.loc[df_web['Film'] == 'dune'].loc[df_web['Time Range'] == \"Sortie Dune\"]).set(title=\"Évolution des sentiments exprimés sur le film Dune\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zLP4-ERguJf-"
      },
      "source": [
        "Ce graphique montre la répartition jour par jour des sentiments relatifs à Dune, les deux semaines précédant sa sortie en salle, et les trois semaines suivant cette dernière.\n",
        "\n",
        "Notons d'abord que ce graphique ne stacke pas les résultats, ne les empile pas verticalement, mais les superpose horizontalement. Autrement dit, ce qui pourrait sembler être une variation quotidienne du nombre de tweets publiés à propos du film est un trompe-l'oeil. En réalité, pour obtenir le nombre de tweets publiés il faut additionner la hauteur des deux barres. Ce que révèlerait cette addition du nombre de tweets positifs (un peu moins de 400 le 10-08) et du nombre de tweets négatifs (un peu plus de 100 le 10-08) c'est que le nombre de tweets publiés chaque jour est constant: il s'agit d'un effet du scraping puisque l'on s'est limité à scraper 500 tweeets par jour. Ainsi, les données que nous avons récoltées permettent juste de savoir que, chaque jour, au moins 500 tweets ont été publiés sur Dune mais ne permettent pas de formuler d'observation sur l'évolution du nombre de tweets publiés dans le temps car le nombre de tweets scrapés chaque jour est constant.\n",
        "\n",
        "Comme précédemment, il apparaît que dans l'immense majorité des cas, Dune a suscité chaque jour une majorité de commentaires positifs.\n",
        "\n",
        "Pour observer une diminution franche du nombre de tweets publiés faisant référence à Dune, il aurait sans doute fallu étendre la période d'observation de quelques semaines."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mIXSIk6BzYRZ",
        "outputId": "57c3680b-69c0-4993-eb51-0ec2ab07d86a"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Text(0.5, 1.0, 'Évolution des sentiments exprimés sur le film Space Jam')]"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1800x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, axs = plt.subplots(1, 1, figsize=(25, 7))\n",
        "sns.histplot(x='day', hue='sentiment', data=df_web.loc[df_web['Film'] == 'space jam'].loc[df_web['Time Range'] == \"Sortie Space Jam\"]).set(title=\"Évolution des sentiments exprimés sur le film Space Jam\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xucjOva7uJf_"
      },
      "source": [
        "Ce graphique montre la répartition jour par jour des sentiments relatifs à Space Jam, les deux semaines précédant sa sortie en salle, et les trois semaines suivant cette dernière.\n",
        "\n",
        "Il apparaît que globalement, Space Jam a suscité des réactions plus mitigées  que Dune, malgré une majorité de commentaires positifs chaque jour (ou presque) (cela se voit au fait que la barre des sentiments positifs est plus haute que celle des sentiments négatifs car elle la dépasse par l'arrière). \n",
        "\n",
        "Contrairement à Dune, le nombre de tweets publiés chaque jour n'est pas du tout constant : il est très faible les premiers jours de la semaine qui précède la sortie du film en salle; il augmente jusqu'à la sortie du film, puis atteint le maximum scrapable de 500 tweeets par jour le 13 juillet c'est-à-dire trois jours avant la sortie du film. Ensuite, pendant deux semaines la capacité de scraping est saturée avec au moins 500 tweets par jour avant de retomber assez franchement les jours suivants (tendance qui n'est pas observée dans le cas de Dune).\n",
        "\n",
        "Ces résultats soulignent le fait que Space Jam était un film bien moins attendu que Dune, et qui a beaucoup moins fait parler de lui après sa sortie."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WBLPoyGhuJgA"
      },
      "source": [
        "## Conclusion"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "akKeiNiOuJgA"
      },
      "source": [
        "Toutes ces analyses nous ont permis de dégager plusieurs tendances, qui tendent à opposer Dune et Space Jam :\n",
        "\n",
        "- Dune a suscité davantage de réactions positives que Space Jam\n",
        "- Dune a suscité beaucoup plus de réactions que Space Jam\n",
        "- Dune était un film plus attendu que Space Jam\n",
        "- Dune est un film qui a fait beaucoup parler de lui pendant longtemps, contrairement a Space Jam dont la popularité est rapidement retombée après sa sortie\n",
        "\n",
        "Finalement, tous ces résultats viennent confirmer nos a priori : Dune est un film qui a connu un franc succès, alors que Space Jam a globalement déçu.\n",
        "\n",
        "On peut toutefois remarquer un fait, qui sans être une surprise, est très intéressant: la proportion de tweets positifs ou négatifs parmis ceux publiés à propos d'un film semble ne pas être impactée par la sortie du film. En particulier, pour Dune on ne voit pas d'évolution majeure entre les deux semaines précédant la sortie du Film et les trois suivantes et il en va, à peu de choses près, de même pour Space Jam.\n",
        "\n",
        "Faut-il en conclure que les avis à propos d'un film sont déjà forgés avant sa sortie en salles ? On ne peut évidemment pas l'affirmer sur la base des données dont nous disposons mais il s'agit là d'un sujet qui mériterait une étude, ou un futur projet Python."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dQhZu1ZtuJgA",
        "outputId": "b3829137-eef5-4d39-fb87-ea53edafe075"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Temps d'exécution total : 00:00:25\n"
          ]
        }
      ],
      "source": [
        "print(f\"Temps d'exécution total : {time.strftime('%H:%M:%S', time.gmtime(time.time()-t))}\")"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "name": "Conclusion.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "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": "3.8.5"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}