{
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "ee64eb9c-96df-4a1c-ce4f-336579929471"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "\n",
        "train_types = {'Agencia_ID':np.uint16, 'Ruta_SAK':np.uint16, 'Cliente_ID':np.uint32, \n",
        "               'Producto_ID':np.uint16, 'Demanda_uni_equil':np.uint32}\n",
        "\n",
        "test_types = {'Agencia_ID':np.uint16, 'Ruta_SAK':np.uint16, 'Cliente_ID':np.uint32, \n",
        "              'Producto_ID':np.uint16, 'id':np.uint32}\n",
        "\n",
        "df_train = pd.read_csv('../input/train.csv', usecols=train_types.keys(), dtype=train_types)\n",
        "df_test = pd.read_csv('../input/test.csv',usecols=test_types.keys(), dtype=test_types)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "815555af-2891-78a2-3bdf-5acd044208ca"
      },
      "outputs": [],
      "source": [
        "print('Train Data\\n', df_train.head(1), '\\n')\n",
        "print('Test Data\\n', df_test.head(1), '\\n')"
      ]
    }
  ],
  "metadata": {
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    "_is_fork": false,
    "kernelspec": {
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      "codemirror_mode": {
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      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.5.2"
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