Testing.ipynb

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  "metadata": {
    "colab": {
      "name": "Testing.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "mount_file_id": "15NgyuvZuA0VDUAm1lqA59Vmv93ky3fEF",
      "authorship_tag": "ABX9TyNSIH/u9SqZvIaylzW28+ax",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ddsprasad/NorthWind/blob/master/Testing.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rdCvLdH8fk1U",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vaxXvzFOf4rd",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "outputId": "d37b30b6-c3c2-4bba-8a8f-a2a82e895a35"
      },
      "source": [
        "df = pd.read_csv('/content/sample_data/mnist_test.csv')\n",
        "df.head()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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            "text/plain": [
              "   7  0  0.1  0.2  0.3  0.4  ...  0.662  0.663  0.664  0.665  0.666  0.667\n",
              "0  2  0    0    0    0    0  ...      0      0      0      0      0      0\n",
              "1  1  0    0    0    0    0  ...      0      0      0      0      0      0\n",
              "2  0  0    0    0    0    0  ...      0      0      0      0      0      0\n",
              "3  4  0    0    0    0    0  ...      0      0      0      0      0      0\n",
              "4  1  0    0    0    0    0  ...      0      0      0      0      0      0\n",
              "\n",
              "[5 rows x 785 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "flAvqsJ1gXjS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import os"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hay4k9Smgxh9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "d347b9c9-4afe-417f-8ead-6fb73ea001ef"
      },
      "source": [
        "os.path"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<module 'posixpath' from '/usr/lib/python3.6/posixpath.py'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xOZ0sHe9g9g5",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "x = [2,3,4,5]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r01sNQkYhZeX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "f8af6bc9-fb9c-41ae-dcfa-e672a5ac6af3"
      },
      "source": [
        "y = [4,5,6,7]\n",
        "\n",
        "plt.bar(x,y)\n",
        "plt.show()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "atbjAONIhgIM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}