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        "# Imports\n",
        "\n",
        "# pandas\n",
        "import pandas as pd\n",
        "from pandas import Series,DataFrame\n",
        "\n",
        "# numpy, matplotlib, seaborn\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "sns.set_style('whitegrid')\n",
        "%matplotlib inline\n",
        "\n",
        "# machine learning\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.svm import SVC, LinearSVC\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.naive_bayes import GaussianNB\n",
        "## get titanic & test csv files as a DataFrame\n",
        "titanic_df = pd.read_csv(\"../input/train.csv\")\n",
        "test_df    = pd.read_csv(\"../input/test.csv\")\n",
        "\n",
        "# preview the data\n",
        "titanic_df.head()\n",
        "titanic_df.info()\n",
        "print(\"----------------------------\")\n",
        "test_df.info()\n",
        "import numpy as np\n",
        "from random import randint\n",
        "myMatrix=[]\n",
        "for i in range(418):\n",
        "    if (titanic_df[\"Sex\"][i+1]==\"female\"):\n",
        "        passengerLabel=1\n",
        "    else:\n",
        "        passengerLabel=0\n",
        "    myMatrix.append(passengerLabel)\n",
        "myArray=np.array(myMatrix)\n",
        "Y_pred=myArray.transpose()\n",
        "print(Y_pred)\n",
        "\n",
        "submission = pd.DataFrame({\n",
        "        \"PassengerId\": test_df[\"PassengerId\"],\n",
        "        \"Survived\": Y_pred\n",
        "    })\n",
        "submission.to_csv('titanic.csv', index=False)"
      ]
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