PLN_04.ipynb

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      "name": "PLN_04.ipynb",
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      "mount_file_id": "1bR4_WeaZCwmG_WbXqIzOeBZWzCcbz5EL",
      "authorship_tag": "ABX9TyMPUuHNcbXn2LKduT0ropaw"
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    {
      "cell_type": "markdown",
      "source": [
        "Adaptado por Bruno Menezes (https://github.com/brunoleomenezes) e será utilizado apenas para fins acadêmicos."
      ],
      "metadata": {
        "id": "CdkNziK2lYid"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "[IMDB PT BR](https://www.kaggle.com/luisfredgs/imdb-ptbr)"
      ],
      "metadata": {
        "id": "cQbVw5EYgI8V"
      }
    },
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>text_en</th>\n",
              "      <th>text_pt</th>\n",
              "      <th>sentiment</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Once again Mr. Costner has dragged out a movie...</td>\n",
              "      <td>Mais uma vez, o Sr. Costner arrumou um filme p...</td>\n",
              "      <td>neg</td>\n",
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              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>This is an example of why the majority of acti...</td>\n",
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              "      <td>neg</td>\n",
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              "      <td>3</td>\n",
              "      <td>First of all I hate those moronic rappers, who...</td>\n",
              "      <td>Primeiro de tudo eu odeio esses raps imbecis, ...</td>\n",
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              "      <td>Not even the Beatles could write songs everyon...</td>\n",
              "      <td>Nem mesmo os Beatles puderam escrever músicas ...</td>\n",
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              "      <th>4</th>\n",
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              "      <td>Brass pictures movies is not a fitting word fo...</td>\n",
              "      <td>Filmes de fotos de latão não é uma palavra apr...</td>\n",
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            "text/plain": [
              "   id  ... sentiment\n",
              "0   1  ...       neg\n",
              "1   2  ...       neg\n",
              "2   3  ...       neg\n",
              "3   4  ...       neg\n",
              "4   5  ...       neg\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 78
        }
      ],
      "source": [
        "import pandas as pd\n",
        "\n",
        "textos = pd.read_csv(\"/content/drive/MyDrive/Curso_PLN/imdb-reviews-pt-br.csv\")\n",
        "textos.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Definindo dados de treinamento e teste."
      ],
      "metadata": {
        "id": "n-MIvsG-kN-5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "treino, teste, c_treino, c_teste = train_test_split(textos.text_pt, textos.sentiment, random_state = 42)"
      ],
      "metadata": {
        "id": "a8LjzCFihRly"
      },
      "execution_count": 79,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "teste"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "WcmBDtmUkd8Q",
        "outputId": "12c0776d-8ecb-40a1-ae26-fc276bc4639d"
      },
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "12532    Isso era incomum: um filme moderno que era ult...\n",
              "35445    Alguns dos meus velhos amigos sugeriram que eu...\n",
              "20279    Que prazer. Isto é realmente uma paródia. Some...\n",
              "2969     Há cerca de dez minutos a meio da Strangeland,...\n",
              "45161    Otelo, a clássica história de Shakespearen sob...\n",
              "                               ...                        \n",
              "16421    Crescendo como filho do cinema, uma das trilog...\n",
              "39861    Este filme é o melhor filme de todos os tempos...\n",
              "309      \"Electra Glide in Blue\" é um movimento lento e...\n",
              "20638    Eu amo esse filme ! Eu acho que já vi 5 vezes ...\n",
              "38935    Eu vi alguns filmes sobre transtornos alimenta...\n",
              "Name: text_pt, Length: 12365, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "c_teste"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "foaMpnxTkePl",
        "outputId": "71e8677f-e820-45e8-e583-9b96aa12796c"
      },
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "12532    pos\n",
              "35445    neg\n",
              "20279    pos\n",
              "2969     neg\n",
              "45161    pos\n",
              "        ... \n",
              "16421    pos\n",
              "39861    pos\n",
              "309      neg\n",
              "20638    pos\n",
              "38935    pos\n",
              "Name: sentiment, Length: 12365, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "treino"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IcRPxaY3kkIS",
        "outputId": "5666bc9f-784b-42f8-ae3a-9103259ce0a7"
      },
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1348     Embora o filme tenha sido apenas assim, o clos...\n",
              "27466    Este é provavelmente um dos piores filmes que ...\n",
              "29998    De vez em quando, um filme irá varrer ao seu r...\n",
              "48186    Este é um conto completamente diabólico de quã...\n",
              "26473    Lenta, chata, extremamente repetitiva. Não adm...\n",
              "                               ...                        \n",
              "11284    Naach teria ganhado um Razzie para o Pior Film...\n",
              "44732    Apenas assisti a esse filme em DVD e achei a a...\n",
              "38158    Melhor show desde Seinfeld. Ela é realmente mu...\n",
              "860      Eu pareço estar discordando com muitas pessoas...\n",
              "15795    Minhas duas filhas de 11 e 13 anos e eu tive s...\n",
              "Name: text_pt, Length: 37094, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "c_treino"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YgZjI_SHkn6D",
        "outputId": "a5b08a41-b67b-4216-980f-2d977bd1ead4"
      },
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1348     neg\n",
              "27466    neg\n",
              "29998    neg\n",
              "48186    pos\n",
              "26473    neg\n",
              "        ... \n",
              "11284    neg\n",
              "44732    pos\n",
              "38158    pos\n",
              "860      neg\n",
              "15795    pos\n",
              "Name: sentiment, Length: 37094, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "r_log = LogisticRegression()\n",
        "r_log.fit(treino, c_treino)\n",
        "ac = r_log.score(teste, c_teste)\n",
        "print(ac)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "Yu1jzbPyhmFp",
        "outputId": "9f7fa9f1-0bd0-41d7-a3f4-d961ffb408d4"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-84-8f7075e78e8a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mr_log\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mr_log\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtreino\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mc_treino\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0mac\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mr_log\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscore\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mteste\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mc_teste\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mac\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/sklearn/linear_model/_logistic.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m   1512\u001b[0m             \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_dtype\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1513\u001b[0m             \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"C\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1514\u001b[0;31m             \u001b[0maccept_large_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msolver\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m\"liblinear\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"sag\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"saga\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1515\u001b[0m         )\n\u001b[1;32m   1516\u001b[0m         \u001b[0mcheck_classification_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/sklearn/base.py\u001b[0m in \u001b[0;36m_validate_data\u001b[0;34m(self, X, y, reset, validate_separately, **check_params)\u001b[0m\n\u001b[1;32m    579\u001b[0m                 \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mcheck_y_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    580\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 581\u001b[0;31m                 \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_X_y\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mcheck_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    582\u001b[0m             \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    583\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)\u001b[0m\n\u001b[1;32m    974\u001b[0m         \u001b[0mensure_min_samples\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mensure_min_samples\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    975\u001b[0m         \u001b[0mensure_min_features\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mensure_min_features\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 976\u001b[0;31m         \u001b[0mestimator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    977\u001b[0m     )\n\u001b[1;32m    978\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)\u001b[0m\n\u001b[1;32m    744\u001b[0m                     \u001b[0marray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcasting\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"unsafe\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    745\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 746\u001b[0;31m                     \u001b[0marray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    747\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mComplexWarning\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mcomplex_warning\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    748\u001b[0m                 raise ValueError(\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/numpy/core/_asarray.py\u001b[0m in \u001b[0;36masarray\u001b[0;34m(a, dtype, order)\u001b[0m\n\u001b[1;32m     81\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     82\u001b[0m     \"\"\"\n\u001b[0;32m---> 83\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     84\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/core/series.py\u001b[0m in \u001b[0;36m__array__\u001b[0;34m(self, dtype)\u001b[0m\n\u001b[1;32m    855\u001b[0m               dtype='datetime64[ns]')\n\u001b[1;32m    856\u001b[0m         \"\"\"\n\u001b[0;32m--> 857\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_values\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    858\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    859\u001b[0m     \u001b[0;31m# ----------------------------------------------------------------------\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/numpy/core/_asarray.py\u001b[0m in \u001b[0;36masarray\u001b[0;34m(a, dtype, order)\u001b[0m\n\u001b[1;32m     81\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     82\u001b[0m     \"\"\"\n\u001b[0;32m---> 83\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     84\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: could not convert string to float: 'Embora o filme tenha sido apenas assim, o closed caption foi de longe o melhor que eu já vi! Na maioria das vezes, a ortografia é terrível e a legenda está fora de sincronia. Eu uso o closed captioning mesmo que eu possa ouvir bem, mas acho que muitos atores resmungam. Também muitas vezes a trilha sonora substitui o diálogo. Obrigado!'"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Erro! Qual o motivo?"
      ],
      "metadata": {
        "id": "Nok_SUbAkuYF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Primeiro: conhecer aspectos dos textos."
      ],
      "metadata": {
        "id": "88cEm9SXp9rT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Negativa\n",
        "print(textos.text_pt[189])\n",
        "#Este é sem dúvida o PIOR filme..."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-j4qrOAip1MS",
        "outputId": "b40c32f8-a65b-429d-dda9-02bd75ecfa7f"
      },
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Este é sem dúvida o pior filme que eu já vi. E acredite em mim, eu vi muitos filmes. A reviravolta inacreditável que o filme faz - passando de um extremamente mau filme \"Formas de vida alienígenas habitam a terra\", com um filme que tenta espalhar um arquicristiano \"O dia do julgamento está próximo, buscar Jesus ou queimar por toda a eternidade em as dívidas ardentes do inferno \"mensagem - deixou-me atordoado depois de ter sido atormentado por 85 minutos. Até mesmo os cristãos religiosos devem se envergonhar ou ficar furiosos ao ver suas crenças postadas dessa maneira. Eu não sabia o que fazer comigo quando assisti a atuação horrível que poderia ter sido realizada por crianças de 7 anos de idade. Simplesmente repugnante. Eu não sou cristão nem muito religioso. Mas se eu estivesse, não teria mais medo do Inferno. Rich Christiano mostrou ser algo muito pior.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Poitivo\n",
        "print(textos.text_pt[49002])\n",
        "#...BRILHANTE..."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8TJZoYkwq2uW",
        "outputId": "380ffe8f-e66a-415c-a3d6-2ab366f3867f"
      },
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Crescendo em Nova York no final dos anos 80 e início dos anos 90, posso dizer pessoalmente que este é um dos documentários mais importantes feitos para cobrir esse lugar neste período de tempo. Não Madonna não veio com a idéia de Voguing, mas é de onde ela tirou! Em vez de combater a violência uns dos outros ou em brigas de gato, o voguing permitia que as pessoas \"lutassem\" dentro dos confins de tudo, menos que tocassem umas às outras, o que justificaria uma desqualificação automática. Vendo este tipo de extraordinariamente talentosas / bem orquestradas \"jogadas\" nos clubes foi nada menos do que espetacular e todos os grandes nomes de antigamente estão aqui ... Pepper La Beija, Paris Duprée, Xtragavaganza, etc. ..tudo comemorado nos gostos de peças de época como a música de Malcom McLarens \"Deep in Vogue\" ... não importava quem você era, ou de onde você era porque quando você passava por aquelas portas nesse \"reino mágico\" de De certa forma, você se tornou parte de algo maior que você / você era importante / e, o mais importante, a criação de seus próprios movimentos e imaginação ... e qualquer pessoa de qualquer lugar poderia se tornar Rei ou Rainha como poderia ter sido. As palavras e inteligência eram tão afiadas quanto os movimentos no chão. Toda a tensão, excitação e magia dessa energia urbana de NYC é capturada neste filme. BRILHANTE!!! POR FAVOR, LIBERE EM DVD para o mundo ver !!! Obrigado!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(textos.sentiment.value_counts())\n",
        "#Está bem balanceado?\n",
        "classi = textos[\"sentiment\"].replace([\"neg\", \"pos\"], [0,1])\n",
        "textos[\"classi\"] = classi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AHZ2P0FjrC4T",
        "outputId": "705e4952-6da3-4060-97ca-44be79465076"
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "neg    24765\n",
            "pos    24694\n",
            "Name: sentiment, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "textos.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "-iZjLMRqsXJM",
        "outputId": "a16b2fc6-e981-4009-affa-0ec255533268"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-672a4c8a-cdd8-4eef-93f9-f230a96946b0\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>id</th>\n",
              "      <th>text_en</th>\n",
              "      <th>text_pt</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>classi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Once again Mr. Costner has dragged out a movie...</td>\n",
              "      <td>Mais uma vez, o Sr. Costner arrumou um filme p...</td>\n",
              "      <td>neg</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>This is an example of why the majority of acti...</td>\n",
              "      <td>Este é um exemplo do motivo pelo qual a maiori...</td>\n",
              "      <td>neg</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>First of all I hate those moronic rappers, who...</td>\n",
              "      <td>Primeiro de tudo eu odeio esses raps imbecis, ...</td>\n",
              "      <td>neg</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Not even the Beatles could write songs everyon...</td>\n",
              "      <td>Nem mesmo os Beatles puderam escrever músicas ...</td>\n",
              "      <td>neg</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Brass pictures movies is not a fitting word fo...</td>\n",
              "      <td>Filmes de fotos de latão não é uma palavra apr...</td>\n",
              "      <td>neg</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-672a4c8a-cdd8-4eef-93f9-f230a96946b0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-672a4c8a-cdd8-4eef-93f9-f230a96946b0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-672a4c8a-cdd8-4eef-93f9-f230a96946b0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   id                                            text_en  ... sentiment classi\n",
              "0   1  Once again Mr. Costner has dragged out a movie...  ...       neg      0\n",
              "1   2  This is an example of why the majority of acti...  ...       neg      0\n",
              "2   3  First of all I hate those moronic rappers, who...  ...       neg      0\n",
              "3   4  Not even the Beatles could write songs everyon...  ...       neg      0\n",
              "4   5  Brass pictures movies is not a fitting word fo...  ...       neg      0\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "![Screenshot 2022-02-10 at 10-37-48 introducao-ao-pln-com-python Aula1 ipynb at master · alura-cursos introducao-ao-pln-com-p[...].png](data:image/png;base64,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)"
      ],
      "metadata": {
        "id": "KgggN3IP22lq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#O filme é muito muito bom."
      ],
      "metadata": {
        "id": "eHCKXFu710PZ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#O filme é péssimo."
      ],
      "metadata": {
        "id": "owkgNGLX3JDJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![Screenshot 2022-02-10 at 10-41-11 introducao-ao-pln-com-python Aula1 ipynb at master · alura-cursos 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)"
      ],
      "metadata": {
        "id": "8Ps2Z1kL3a2L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "\n",
        "duas_frases = [\"Assisti um filme ótimo\", \"Assisti um filme ruim\"]\n",
        "vet = CountVectorizer(lowercase=False)\n",
        "bw= vet.fit_transform(duas_frases)\n",
        "vet.get_feature_names_out()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mx_Z8TFT4dvf",
        "outputId": "1d30a016-8db9-46e2-fc93-debaf154dd6b"
      },
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Assisti', 'filme', 'ruim', 'um', 'ótimo'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "matriz = pd.DataFrame.sparse.from_spmatrix(bw, columns=vet.get_feature_names_out())\n",
        "matriz"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "CbzZUktPeyje",
        "outputId": "ca31458f-3b41-4b1d-aa68-4ceda1307d32"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <div>\n",
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              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-40654e26-3368-4fe5-81fc-7d39f82a968f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-40654e26-3368-4fe5-81fc-7d39f82a968f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   Assisti  filme  ruim  um  ótimo\n",
              "0        1      1     0   1      1\n",
              "1        1      1     1   1      0"
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "vet = CountVectorizer(lowercase=False)\n",
        "bw = vet.fit_transform(textos.text_pt)\n",
        "print(bw.shape) #Dimensões"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nsHDw8Nxp-rD",
        "outputId": "abefb1c2-3051-4eb5-c8bb-9c0ddbacb1b6"
      },
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(49459, 156923)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "vet = CountVectorizer(lowercase=False, max_features=50) #Palavras que mais aparecem no tamanho desejado\n",
        "bw = vet.fit_transform(textos.text_pt)\n",
        "print(bw.shape) #Dimensões"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y-4USOAzqnMt",
        "outputId": "3ed0f3c3-8127-42d3-a8e3-1819a08a6ad9"
      },
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(49459, 50)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "treino, teste, c_treino, c_teste = train_test_split(bw, textos.sentiment, random_state = 42)\n",
        "\n",
        "r_log = LogisticRegression()\n",
        "r_log.fit(treino, c_treino)\n",
        "ac = r_log.score(teste, c_teste)\n",
        "print(ac) #Previsão quase 66%"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H6bgi4z_rput",
        "outputId": "1747dfe4-ada1-4eea-9ec9-46d7f0e8306d"
      },
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.6583097452486858\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def c_t(texto, coluna_texto, coluna_classificacao):\n",
        "    vet = CountVectorizer(lowercase=False, max_features=50)\n",
        "    bw = vet.fit_transform(textos.text_pt)\n",
        "    treino, teste, c_treino, c_teste = train_test_split(bw, textos.sentiment, random_state = 42)\n",
        "\n",
        "    r_log = LogisticRegression()\n",
        "    r_log.fit(treino, c_treino)\n",
        "    return r_log.score(teste, c_teste)\n",
        "print(c_t(textos, \"text_pt\", \"classificacao\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U2D2sRavs2S_",
        "outputId": "7ca5ad8d-1297-404e-babf-a436b711a5ea"
      },
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.6583097452486858\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Como melhorar?"
      ],
      "metadata": {
        "id": "5O_uDCprux0U"
      }
    }
  ]
}