Numpy_2d_arrays.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {
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      "source": [
        "<a href=\"https://colab.research.google.com/github/dbaweja/dbaweja.github.io/blob/main/Numpy_2d_arrays.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
      "metadata": {
        "id": "9k6Qh0xv35Zs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "w4kY5J1l1uE9"
      },
      "outputs": [],
      "source": [
        "a= np.array(range(16))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.shape"
      ],
      "metadata": {
        "colab": {
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        "id": "mTr4FcAM34Wh",
        "outputId": "0e761c4c-358f-4789-800e-fb68a0bc1e5e"
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      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(16,)"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.ndim"
      ],
      "metadata": {
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        "id": "4AZ32xsX4BG1",
        "outputId": "eb2eaa7e-1206-437c-fa0e-017aab1c0bd7"
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      "execution_count": null,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#reshape"
      ],
      "metadata": {
        "id": "nMKjpW0l4Csx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "b = a.reshape(8,2)"
      ],
      "metadata": {
        "id": "I-ezPQpV4ILS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(a)"
      ],
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          "base_uri": "https://localhost:8080/"
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        "id": "JOgZ-vu-4l_n",
        "outputId": "d07bc3be-90ce-45f0-a2f2-27bdbb08147b"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(b)"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/"
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        "id": "oGi7AaIm4iZi",
        "outputId": "ea606782-8260-4716-d299-253e5d7063b4"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  1]\n",
            " [ 2  3]\n",
            " [ 4  5]\n",
            " [ 6  7]\n",
            " [ 8  9]\n",
            " [10 11]\n",
            " [12 13]\n",
            " [14 15]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "b.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Uw-R5QVx4jPx",
        "outputId": "dd75b198-b463-41d8-e560-dd3a4e4a5738"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(8, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "b.ndim"
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        "id": "Se0exSw74rNt",
        "outputId": "d602836a-9b8b-438e-e4de-83f17c6137fd"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(4,4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-AsJ7_Ct4so7",
        "outputId": "f5b84a0e-881c-4ceb-a7bb-33e3752b3190"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0,  1,  2,  3],\n",
              "       [ 4,  5,  6,  7],\n",
              "       [ 8,  9, 10, 11],\n",
              "       [12, 13, 14, 15]])"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(4,5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 176
        },
        "id": "J9vtYtNt438m",
        "outputId": "39270728-2d4c-4a8d-cb13-a7ac2450e34e"
      },
      "execution_count": null,
      "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-13-ffcde1b0c695>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m: cannot reshape array of size 16 into shape (4,5)"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(8,-1)"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/"
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        "id": "heEwpmFb48aK",
        "outputId": "4e785fcf-289b-4c75-a226-b59205a0a7b8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0,  1],\n",
              "       [ 2,  3],\n",
              "       [ 4,  5],\n",
              "       [ 6,  7],\n",
              "       [ 8,  9],\n",
              "       [10, 11],\n",
              "       [12, 13],\n",
              "       [14, 15]])"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(4,-1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GyiN3ApX5O3w",
        "outputId": "021fe30c-51f1-47cb-9c90-87ab91e18f23"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0,  1,  2,  3],\n",
              "       [ 4,  5,  6,  7],\n",
              "       [ 8,  9, 10, 11],\n",
              "       [12, 13, 14, 15]])"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(a)"
      ],
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          "base_uri": "https://localhost:8080/"
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        "id": "P12XuRYd5ZUm",
        "outputId": "e53ef1b7-8be4-40a7-e7ab-178f43a91cd8"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(-1, 5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 176
        },
        "id": "kVWbQUT55dEU",
        "outputId": "377ee76a-2bbf-4af6-990b-fba7702245d6"
      },
      "execution_count": null,
      "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-17-a37ed369d8a8>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m: cannot reshape array of size 16 into shape (5)"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(-1,2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A_L0hkaI5j5i",
        "outputId": "03316a31-ab40-470b-d36a-00a2f3c2c6e8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0,  1],\n",
              "       [ 2,  3],\n",
              "       [ 4,  5],\n",
              "       [ 6,  7],\n",
              "       [ 8,  9],\n",
              "       [10, 11],\n",
              "       [12, 13],\n",
              "       [14, 15]])"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(2,-1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "URk3b5tl5rNR",
        "outputId": "7e631cdc-182a-45c3-a270-03660c66a6a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0,  1,  2,  3,  4,  5,  6,  7],\n",
              "       [ 8,  9, 10, 11, 12, 13, 14, 15]])"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(2,8)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jXIwnksq5tES",
        "outputId": "ed258833-119a-4dcf-97a1-258b55e22713"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0,  1,  2,  3,  4,  5,  6,  7],\n",
              "       [ 8,  9, 10, 11, 12, 13, 14, 15]])"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = a.reshape(8,2)"
      ],
      "metadata": {
        "id": "iYQ9Mmgv5vuY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7dtOSYCx53_m",
        "outputId": "a67500f0-1bc0-484d-e060-550703567b03"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  1]\n",
            " [ 2  3]\n",
            " [ 4  5]\n",
            " [ 6  7]\n",
            " [ 8  9]\n",
            " [10 11]\n",
            " [12 13]\n",
            " [14 15]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.ndim"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9Op61MQN54qc",
        "outputId": "9bcb9915-af7b-459e-ed86-2cf99454683f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0wCikJpn5-It",
        "outputId": "c9bf240f-916f-4d32-9d0d-c2f917054349"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(8, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(a) #rows"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ns4HJriF5_UH",
        "outputId": "1af74d2f-fac0-4143-bad8-07ecb61e80bc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(a[0]) #cols"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3YtBub6v6Kwz",
        "outputId": "691ce62f-998f-4314-d436-9883f5ab5d32"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.reshape(-1,-1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 176
        },
        "id": "b6OTXjSS6je0",
        "outputId": "001e34b1-2296-4c3e-d7a7-bde39236e593"
      },
      "execution_count": null,
      "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-29-aa43799da6cd>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m: can only specify one unknown dimension"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Transpose"
      ],
      "metadata": {
        "id": "pUeIgsI36Mgg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(12).reshape(3,4)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5MMrgArh6ciQ",
        "outputId": "6b9d84f0-7344-49cc-8ba0-786d1882c382"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  1  2  3]\n",
            " [ 4  5  6  7]\n",
            " [ 8  9 10 11]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ecu1g7PH6_oz",
        "outputId": "c7915bdb-8736-404f-e00d-a9505afe1eae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Transpose\n",
        "b= a.T"
      ],
      "metadata": {
        "id": "lyBN1Rcu7EVT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(b)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uVpjgDPf7LX1",
        "outputId": "014fa4cf-30d2-4979-8159-3a9800421e87"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  4  8]\n",
            " [ 1  5  9]\n",
            " [ 2  6 10]\n",
            " [ 3  7 11]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "b.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MUIBOXSN7WZG",
        "outputId": "a6e04430-fbb0-4d5d-8ded-04bd95a6ed73"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#n x m --> after transpose --> m x n"
      ],
      "metadata": {
        "id": "8ZB5sOXT7bdH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Quiz\n",
        "a = np.arange(1,10).reshape(3,3)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eRBNEKSy7hZD",
        "outputId": "bd9ac4f8-ccd0-4790-f951-b70b65c21199"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[1 2 3]\n",
            " [4 5 6]\n",
            " [7 8 9]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cT_gcmnE78RA",
        "outputId": "fd5bc775-89d9-4925-dfc0-85357144149f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([4, 5, 6])"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[1][2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Tgonlliv8Kdi",
        "outputId": "5d7607d7-6d00-4f48-b237-f4288d9dbc33"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[1,2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HDjCSXVo8TC5",
        "outputId": "aa290e67-395d-410e-ec69-00e6a7fa829a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[2,0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_IPx45-q8e4e",
        "outputId": "f72314e0-f7d2-4f91-c105-d9c789c5da1a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# a[row, col]"
      ],
      "metadata": {
        "id": "VHXreP7o8yfq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Multi-indexing in 2D Numpy Arrays"
      ],
      "metadata": {
        "id": "90uCog1082BG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.array([100,200,300,400,500,600])"
      ],
      "metadata": {
        "id": "8WEsrkQx88-z"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "um7uGhPb9Om6",
        "outputId": "6dd91d68-497f-48b6-e198-3b2ceb395365"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(6,)"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a.ndim"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KOmsx3oO9P9F",
        "outputId": "6b210042-1e3a-45fd-f705-4761c2f37dc2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[2,3]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 176
        },
        "id": "d6c7zA3k9RfQ",
        "outputId": "a77f1279-0532-4315-e7c1-192062e8e6a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "IndexError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-48-53553f6f922e>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m: too many indices for array: array is 1-dimensional, but 2 were indexed"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[[ 2, 5]] #multi-indexing"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AlVAU-8g9aKD",
        "outputId": "a93bb1d8-d0fa-48a9-cc79-3e22ad436b90"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([300, 600])"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cMHTSemh9f7E",
        "outputId": "ef13332f-e7f8-4619-931c-4ee94571c3ef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[100 200 300 400 500 600]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(a[[2,3,4,1,2,2]])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jlr0oBVv9lqw",
        "outputId": "059f1b9a-7979-4a18-db4a-76315e3b865e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[300 400 500 200 300 300]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#multi-indexing in 2D"
      ],
      "metadata": {
        "id": "6VM_xVvT9_DL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(9).reshape(3,3)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ktj3Dtl--GU8",
        "outputId": "e3e09695-26e0-4700-f97d-fdbe1fda358b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0 1 2]\n",
            " [3 4 5]\n",
            " [6 7 8]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[2,1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fTL29sLR-LNj",
        "outputId": "eb460b9e-16c3-4645-a89a-4df779134c30"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[0,2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qQbKCI1L-h7j",
        "outputId": "e0b57b83-f7db-4cdb-b378-c41eeda45199"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[[2, 0] , [1, 2]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jKdEqHHL-oVC",
        "outputId": "7427d819-7e98-4686-c454-7c6acfe773a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([7, 2])"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Task: Use multi-indexing in 2D to print the principal digonal elements of the above given np array\n",
        "\n",
        "\n",
        "a[[0, 1, 2] , [0, 1, 2]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vGt-4HGV-6P3",
        "outputId": "cdee3631-2192-49b6-a931-50bda92acebf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 4, 8])"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#slicing"
      ],
      "metadata": {
        "id": "k-NL_pAI_n0_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(12).reshape(3,4)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8ZB63qF6_1A6",
        "outputId": "64b5752a-ab9c-4e15-edfc-39b19b05b159"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  1  2  3]\n",
            " [ 4  5  6  7]\n",
            " [ 8  9 10 11]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[:2] #first 2 rows"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dzesGiE__6Cu",
        "outputId": "87bd1549-c25c-4cac-bbf2-48adef9f933c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0, 1, 2, 3],\n",
              "       [4, 5, 6, 7]])"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[: , :2] #first 2 columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ruQ9l1oDABX2",
        "outputId": "d2ec56ab-ada6-420d-debe-7f3465802950"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0, 1],\n",
              "       [4, 5],\n",
              "       [8, 9]])"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[: , 1:3]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VHe9F6ONALyD",
        "outputId": "394e7794-d79a-416f-bc29-c2000b1676a0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1,  2],\n",
              "       [ 5,  6],\n",
              "       [ 9, 10]])"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Fancy indexing in 2D"
      ],
      "metadata": {
        "id": "diftAAtoAzgQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(12).reshape(3,4)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nkown298Bjtc",
        "outputId": "8cad430a-768c-46bf-e12c-ac3b6cb6a330"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  1  2  3]\n",
            " [ 4  5  6  7]\n",
            " [ 8  9 10 11]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a < 6"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mzXVtv6oBqM2",
        "outputId": "848a4295-ce31-4661-af28-1d0f8f3cc476"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ True,  True,  True,  True],\n",
              "       [ True,  True, False, False],\n",
              "       [False, False, False, False]])"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[a<6]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KWppYiwcB5Ai",
        "outputId": "c4fd65f4-48e0-4605-877a-6a27d6616293"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1, 2, 3, 4, 5])"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Quiz\n",
        "\n",
        "a = np.array([7,1,2,3,4,5])\n",
        "mask = (a%2 == 0)\n",
        "a[mask] = -1"
      ],
      "metadata": {
        "id": "QN57kiE2CFIM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A2De14IJC1xt",
        "outputId": "49ec0fae-e748-46be-b8a6-59f4d6afe75e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[ 7  1 -1  3 -1  5]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "a = np.array([7,8,4,9,3,2])\n",
        "a[a%2 == 1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MM4hF9VGC3Wc",
        "outputId": "4fa7abbe-e9af-4df2-a17f-1dd901e86ea8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([7, 9, 3])"
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "a = np.array([7,8,4,9,3,2])\n",
        "a[a%2 == 1] = -1\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0liOLysUDgPZ",
        "outputId": "bc92931b-75c5-4158-bf5b-33d95dedd3fe"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[-1  8  4 -1 -1  2]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(14).reshape(2,7)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tMwS2w_IDjrv",
        "outputId": "224880f4-be9e-4fd8-ab5a-2e8c9c8d6576"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  1  2  3  4  5  6]\n",
            " [ 7  8  9 10 11 12 13]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[[0,0, 1] , [0,2,5]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CTogMft6EGY8",
        "outputId": "891d56d2-f08b-47cf-fcae-a3ef3d2969a5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0,  2, 12])"
            ]
          },
          "metadata": {},
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#resume at 10:13 sharp"
      ],
      "metadata": {
        "id": "TcxJe8nvEV22"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#aggregate functions"
      ],
      "metadata": {
        "id": "HValOW7nEfiH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(1, 11)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uTzJfOlaHJqX",
        "outputId": "a36bdce6-c523-4f7a-f4c9-380cf1e87dd6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[ 1  2  3  4  5  6  7  8  9 10]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.sum(a) #sum of all the values in a"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PzGzTbj8HQyD",
        "outputId": "5226ebfe-b127-4b83-9794-b37f5247ea9e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "55"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.mean(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MPtbGhALHWTg",
        "outputId": "e914f7ee-bd11-4aab-edea-6e1443b5f751"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5.5"
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.min(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SrCeBtYMHb2U",
        "outputId": "1e74637d-56b2-4f13-883c-67954bfb2821"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.max(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cUPtOx0pHfmt",
        "outputId": "5bca9fb5-7cba-4c31-e3e0-c2ae5e5e130b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#aggregate functions on 2D"
      ],
      "metadata": {
        "id": "GYvTYE7GHhDu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(12).reshape(3,4)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fI1VpsbiHmbc",
        "outputId": "371c7d2d-07a3-4a4f-c0e2-4574e45dd978"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  1  2  3]\n",
            " [ 4  5  6  7]\n",
            " [ 8  9 10 11]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 0 -> Vertical axis\n",
        "# 1 -> Horizontal axis"
      ],
      "metadata": {
        "id": "xV63OGgfHqwF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#row-wise sum: [6, 22, 38 ]"
      ],
      "metadata": {
        "id": "B8HkC3a0H7QT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "np.sum(a, axis = 1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ea1lCT__IOMc",
        "outputId": "5487c1d3-9e5d-4b56-dfb8-39ac30d47246"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 6, 22, 38])"
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# [12, 15, 18, 21]\n",
        "np.sum(a, axis = 0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7PVqJUz-IUW2",
        "outputId": "28b9495d-0143-461d-c620-177361b11ea7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([12, 15, 18, 21])"
            ]
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Logical operations"
      ],
      "metadata": {
        "id": "WDw3L-F3Ir8m"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.array([5,7,2, 8, 1])\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1_FDGaDYI449",
        "outputId": "1bdadb89-85b5-4e82-a168-00b87523cc71"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[5 7 2 8 1]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(a < 3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZyyKY3oXJIS3",
        "outputId": "a16f237f-7b62-45f2-be56-5e93d1627c64"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[False False  True False  True]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#np.all() np.any()"
      ],
      "metadata": {
        "id": "nEGV-mSWJWAU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "np.all(a < 3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nyJ1SbKAJfbX",
        "outputId": "cb4aa43f-87ce-4acc-df17-ef7798c4004e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.all(a < 30)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gq_8U1vGJnFl",
        "outputId": "aea37b33-8b4d-42b7-93df-29d7d86b1e39"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.any(a < 3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QPmK9naYJylk",
        "outputId": "341d3473-a897-487e-bcad-9acbef01ef9c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.any(a > 30)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2v50Qtk7J6lK",
        "outputId": "c237a5df-a419-4116-bde3-a357cd8fa95a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Quiz\n",
        "\n",
        "a = np.array([0,2,3])\n",
        "b = np.array([1,3,5])\n"
      ],
      "metadata": {
        "id": "-S6S8bDFJ-nv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fT4IwOYIKZJR",
        "outputId": "3a21bf9a-166c-459b-d903-c52defece1e0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0 2 3]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(b)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mioedh2jKZoO",
        "outputId": "317871b0-482a-4129-eb83-c825c48fb1d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1 3 5]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#element-wise operation/comparison\n",
        "a >= b"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b80xrnIOKaDq",
        "outputId": "d7aa29c7-c365-44d4-cf9c-f4718ba63ed5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([False, False, False])"
            ]
          },
          "metadata": {},
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(a + b)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y3Fnmx2XKjSi",
        "outputId": "759948be-5843-4e5b-af11-ea039f2508f6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1 5 8]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "arr = np.array([-3,4,27,34,-2, 10, -45,-11,4, 9 ])\n",
        "arr"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kfJl5-skKzV4",
        "outputId": "5a621d09-3c52-4289-b03d-1cdade368f7c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ -3,   4,  27,  34,  -2,  10, -45, -11,   4,   9])"
            ]
          },
          "metadata": {},
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### What if we want to update an array based on condition?\n",
        "\n",
        "Suppose you are given an array of integers and you want to update it based on following condition:\n",
        "- if element is > 0, change it to +1\n",
        "- if element < 0, change it to -1.\n",
        "\n",
        "> **How will you do it?**\n"
      ],
      "metadata": {
        "id": "BsgCmCXPLFTT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(arr)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O_o2EFXqLBi0",
        "outputId": "5ee1e4ba-b353-49bf-9c93-d95f6cba76af"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[ -3   4  27  34  -2  10 -45 -11   4   9]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "arr[arr < 0] = -1\n",
        "arr[arr > 0] = 1\n",
        "print(arr)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RqVm7qHdLQyC",
        "outputId": "58026e7b-284a-41c3-aeb9-96ca46fe0bc5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[-1  1  1  1 -1  1 -1 -1  1  1]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#where()"
      ],
      "metadata": {
        "id": "PGE4YTEBLaSN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Function signature:\n",
        "`np.where(condition, x, y)`\n",
        "\n",
        "This functions returns an ndarray whose elements are chosen from `x` or `y` depending on condition.\n",
        "\n"
      ],
      "metadata": {
        "id": "JFTujxfgLjyU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "arr = np.array([-3,4,27,34,-2, 10, -45,-11,4, 9 ])\n",
        "arr"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AG-STr7bLgIw",
        "outputId": "6df1ba47-a453-4d1f-9772-692a87676aaa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ -3,   4,  27,  34,  -2,  10, -45, -11,   4,   9])"
            ]
          },
          "metadata": {},
          "execution_count": 115
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "b = np.where(arr > 0, 1, -1)"
      ],
      "metadata": {
        "id": "EWvIpTJKLtnw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(b)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E0I08n8uMAFE",
        "outputId": "8fcfac0a-3f00-4c37-9a8f-948ca927d6ba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[-1  1  1  1 -1  1 -1 -1  1  1]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "arr = np.array([-3,4,27,34,-2, 0, -45,-11,4, 0])\n",
        "print(np.where(arr))\n",
        "#HW --> Try to understand this on your own"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "920lsIO9MH0e",
        "outputId": "e93c3b6e-9e62-4d45-b53c-64c7360ab003"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(array([0, 1, 2, 3, 4, 6, 7, 8]),)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Use-case using case-study"
      ],
      "metadata": {
        "id": "xgK4_IaAM1UF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data = np.loadtxt(\"fit.txt\", dtype = \"str\")"
      ],
      "metadata": {
        "id": "2Ip98sYANO4s"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7JueLUzQNk8r",
        "outputId": "dc4139ab-c914-462b-b0de-12237329a6db"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[['06-10-2017' '5464' 'Neutral' '181' '5' 'Inactive']\n",
            " ['07-10-2017' '6041' 'Sad' '197' '8' 'Inactive']\n",
            " ['08-10-2017' '25' 'Sad' '0' '5' 'Inactive']\n",
            " ['09-10-2017' '5461' 'Sad' '174' '4' 'Inactive']\n",
            " ['10-10-2017' '6915' 'Neutral' '223' '5' 'Active']\n",
            " ['11-10-2017' '4545' 'Sad' '149' '6' 'Inactive']\n",
            " ['12-10-2017' '4340' 'Sad' '140' '6' 'Inactive']\n",
            " ['13-10-2017' '1230' 'Sad' '38' '7' 'Inactive']\n",
            " ['14-10-2017' '61' 'Sad' '1' '5' 'Inactive']\n",
            " ['15-10-2017' '1258' 'Sad' '40' '6' 'Inactive']\n",
            " ['16-10-2017' '3148' 'Sad' '101' '8' 'Inactive']\n",
            " ['17-10-2017' '4687' 'Sad' '152' '5' 'Inactive']\n",
            " ['18-10-2017' '4732' 'Happy' '150' '6' 'Active']\n",
            " ['19-10-2017' '3519' 'Sad' '113' '7' 'Inactive']\n",
            " ['20-10-2017' '1580' 'Sad' '49' '5' 'Inactive']\n",
            " ['21-10-2017' '2822' 'Sad' '86' '6' 'Inactive']\n",
            " ['22-10-2017' '181' 'Sad' '6' '8' 'Inactive']\n",
            " ['23-10-2017' '3158' 'Neutral' '99' '5' 'Inactive']\n",
            " ['24-10-2017' '4383' 'Neutral' '143' '4' 'Inactive']\n",
            " ['25-10-2017' '3881' 'Neutral' '125' '5' 'Inactive']\n",
            " ['26-10-2017' '4037' 'Neutral' '129' '6' 'Inactive']\n",
            " ['27-10-2017' '202' 'Neutral' '6' '8' 'Inactive']\n",
            " ['28-10-2017' '292' 'Neutral' '9' '5' 'Inactive']\n",
            " ['29-10-2017' '330' 'Happy' '10' '6' 'Inactive']\n",
            " ['30-10-2017' '2209' 'Neutral' '72' '5' 'Inactive']\n",
            " ['31-10-2017' '4550' 'Happy' '150' '8' 'Active']\n",
            " ['01-11-2017' '4435' 'Happy' '141' '5' 'Inactive']\n",
            " ['02-11-2017' '4779' 'Happy' '156' '4' 'Inactive']\n",
            " ['03-11-2017' '1831' 'Happy' '57' '5' 'Inactive']\n",
            " ['04-11-2017' '2255' 'Happy' '72' '4' 'Inactive']\n",
            " ['05-11-2017' '539' 'Happy' '17' '5' 'Active']\n",
            " ['06-11-2017' '5464' 'Happy' '181' '4' 'Inactive']\n",
            " ['07-11-2017' '6041' 'Neutral' '197' '3' 'Inactive']\n",
            " ['08-11-2017' '4068' 'Happy' '131' '2' 'Inactive']\n",
            " ['09-11-2017' '4683' 'Happy' '154' '9' 'Inactive']\n",
            " ['10-11-2017' '4033' 'Happy' '137' '5' 'Inactive']\n",
            " ['11-11-2017' '6314' 'Happy' '193' '6' 'Active']\n",
            " ['12-11-2017' '614' 'Happy' '19' '4' 'Active']\n",
            " ['13-11-2017' '3149' 'Happy' '101' '5' 'Active']\n",
            " ['14-11-2017' '4005' 'Happy' '139' '8' 'Active']\n",
            " ['15-11-2017' '4880' 'Happy' '164' '4' 'Active']\n",
            " ['16-11-2017' '4136' 'Happy' '137' '5' 'Active']\n",
            " ['17-11-2017' '705' 'Happy' '22' '6' 'Active']\n",
            " ['18-11-2017' '570' 'Neutral' '17' '5' 'Active']\n",
            " ['19-11-2017' '269' 'Happy' '9' '6' 'Active']\n",
            " ['20-11-2017' '4275' 'Happy' '145' '5' 'Inactive']\n",
            " ['21-11-2017' '5999' 'Happy' '192' '6' 'Inactive']\n",
            " ['22-11-2017' '4421' 'Happy' '146' '5' 'Inactive']\n",
            " ['23-11-2017' '6930' 'Happy' '234' '6' 'Inactive']\n",
            " ['24-11-2017' '5195' 'Happy' '167' '5' 'Inactive']\n",
            " ['25-11-2017' '546' 'Happy' '16' '6' 'Inactive']\n",
            " ['26-11-2017' '493' 'Happy' '17' '7' 'Active']\n",
            " ['27-11-2017' '995' 'Happy' '32' '6' 'Active']\n",
            " ['28-11-2017' '1163' 'Neutral' '35' '7' 'Active']\n",
            " ['29-11-2017' '6676' 'Sad' '220' '6' 'Active']\n",
            " ['30-11-2017' '3608' 'Happy' '116' '5' 'Active']\n",
            " ['01-12-2017' '774' 'Happy' '23' '6' 'Active']\n",
            " ['02-12-2017' '1421' 'Happy' '44' '7' 'Active']\n",
            " ['03-12-2017' '4064' 'Happy' '131' '8' 'Active']\n",
            " ['04-12-2017' '2725' 'Happy' '86' '8' 'Active']\n",
            " ['05-12-2017' '5934' 'Happy' '194' '7' 'Active']\n",
            " ['06-12-2017' '1867' 'Happy' '60' '8' 'Active']\n",
            " ['07-12-2017' '3721' 'Sad' '121' '5' 'Active']\n",
            " ['08-12-2017' '2374' 'Neutral' '76' '4' 'Inactive']\n",
            " ['09-12-2017' '2909' 'Neutral' '93' '3' 'Active']\n",
            " ['10-12-2017' '1648' 'Sad' '53' '3' 'Active']\n",
            " ['11-12-2017' '799' 'Sad' '25' '4' 'Inactive']\n",
            " ['12-12-2017' '7102' 'Neutral' '227' '5' 'Active']\n",
            " ['13-12-2017' '3941' 'Neutral' '125' '5' 'Active']\n",
            " ['14-12-2017' '7422' 'Happy' '243' '5' 'Active']\n",
            " ['15-12-2017' '437' 'Neutral' '14' '3' 'Active']\n",
            " ['16-12-2017' '1231' 'Neutral' '39' '4' 'Active']\n",
            " ['17-12-2017' '1696' 'Sad' '55' '4' 'Inactive']\n",
            " ['18-12-2017' '4921' 'Neutral' '158' '5' 'Active']\n",
            " ['19-12-2017' '221' 'Sad' '7' '5' 'Active']\n",
            " ['20-12-2017' '6500' 'Neutral' '213' '5' 'Active']\n",
            " ['21-12-2017' '3575' 'Neutral' '116' '5' 'Active']\n",
            " ['22-12-2017' '4061' 'Sad' '129' '5' 'Inactive']\n",
            " ['23-12-2017' '651' 'Sad' '21' '5' 'Inactive']\n",
            " ['24-12-2017' '753' 'Sad' '28' '4' 'Inactive']\n",
            " ['25-12-2017' '518' 'Sad' '16' '3' 'Inactive']\n",
            " ['26-12-2017' '5537' 'Happy' '180' '4' 'Active']\n",
            " ['27-12-2017' '4108' 'Neutral' '138' '5' 'Active']\n",
            " ['28-12-2017' '5376' 'Happy' '176' '5' 'Active']\n",
            " ['29-12-2017' '3066' 'Neutral' '99' '4' 'Active']\n",
            " ['30-12-2017' '177' 'Sad' '5' '5' 'Inactive']\n",
            " ['31-12-2017' '36' 'Sad' '1' '3' 'Inactive']\n",
            " ['01-01-2018' '299' 'Sad' '10' '3' 'Inactive']\n",
            " ['02-01-2018' '1447' 'Neutral' '47' '3' 'Inactive']\n",
            " ['03-01-2018' '2599' 'Neutral' '84' '2' 'Inactive']\n",
            " ['04-01-2018' '702' 'Sad' '23' '3' 'Inactive']\n",
            " ['05-01-2018' '133' 'Sad' '4' '2' 'Inactive']\n",
            " ['06-01-2018' '153' 'Happy' '0' '8' 'Inactive']\n",
            " ['07-01-2018' '500' 'Neutral' '0' '5' 'Active']\n",
            " ['08-01-2018' '2127' 'Neutral' '0' '5' 'Inactive']\n",
            " ['09-01-2018' '2203' 'Happy' '0' '5' 'Active']]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PYG95VcyNmJ-",
        "outputId": "abca3e3a-43eb-49ab-8a98-6be5bbc8a903"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(96, 6)"
            ]
          },
          "metadata": {},
          "execution_count": 125
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "There are 96 records and each record has 6 features. </br>\n",
        "These features are:\n",
        "- Date\n",
        "- Step count\n",
        "- Mood\n",
        "- Calories Burned\n",
        "- Hours of sleep\n",
        "- activity status"
      ],
      "metadata": {
        "id": "TRmPEMQEN8HF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(data[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L1-k4SwmN4kg",
        "outputId": "7bb27137-671d-41d3-b255-f9f3645a1577"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['06-10-2017' '5464' 'Neutral' '181' '5' 'Inactive']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(data[:5])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e-vByWoxOKhy",
        "outputId": "bb80432d-72a6-4dfd-af3e-dcad16acb087"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[['06-10-2017' '5464' 'Neutral' '181' '5' 'Inactive']\n",
            " ['07-10-2017' '6041' 'Sad' '197' '8' 'Inactive']\n",
            " ['08-10-2017' '25' 'Sad' '0' '5' 'Inactive']\n",
            " ['09-10-2017' '5461' 'Sad' '174' '4' 'Inactive']\n",
            " ['10-10-2017' '6915' 'Neutral' '223' '5' 'Active']]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(data[:, 0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5LQgmFnTORTd",
        "outputId": "84a87479-3353-4811-af1b-3a35fadaffee"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['06-10-2017' '07-10-2017' '08-10-2017' '09-10-2017' '10-10-2017'\n",
            " '11-10-2017' '12-10-2017' '13-10-2017' '14-10-2017' '15-10-2017'\n",
            " '16-10-2017' '17-10-2017' '18-10-2017' '19-10-2017' '20-10-2017'\n",
            " '21-10-2017' '22-10-2017' '23-10-2017' '24-10-2017' '25-10-2017'\n",
            " '26-10-2017' '27-10-2017' '28-10-2017' '29-10-2017' '30-10-2017'\n",
            " '31-10-2017' '01-11-2017' '02-11-2017' '03-11-2017' '04-11-2017'\n",
            " '05-11-2017' '06-11-2017' '07-11-2017' '08-11-2017' '09-11-2017'\n",
            " '10-11-2017' '11-11-2017' '12-11-2017' '13-11-2017' '14-11-2017'\n",
            " '15-11-2017' '16-11-2017' '17-11-2017' '18-11-2017' '19-11-2017'\n",
            " '20-11-2017' '21-11-2017' '22-11-2017' '23-11-2017' '24-11-2017'\n",
            " '25-11-2017' '26-11-2017' '27-11-2017' '28-11-2017' '29-11-2017'\n",
            " '30-11-2017' '01-12-2017' '02-12-2017' '03-12-2017' '04-12-2017'\n",
            " '05-12-2017' '06-12-2017' '07-12-2017' '08-12-2017' '09-12-2017'\n",
            " '10-12-2017' '11-12-2017' '12-12-2017' '13-12-2017' '14-12-2017'\n",
            " '15-12-2017' '16-12-2017' '17-12-2017' '18-12-2017' '19-12-2017'\n",
            " '20-12-2017' '21-12-2017' '22-12-2017' '23-12-2017' '24-12-2017'\n",
            " '25-12-2017' '26-12-2017' '27-12-2017' '28-12-2017' '29-12-2017'\n",
            " '30-12-2017' '31-12-2017' '01-01-2018' '02-01-2018' '03-01-2018'\n",
            " '04-01-2018' '05-01-2018' '06-01-2018' '07-01-2018' '08-01-2018'\n",
            " '09-01-2018']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_t = data.T\n",
        "print(data_t)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6hGT1aL2Of_R",
        "outputId": "fa661860-22ce-4fe8-bd34-01337a7e5f82"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[['06-10-2017' '07-10-2017' '08-10-2017' '09-10-2017' '10-10-2017'\n",
            "  '11-10-2017' '12-10-2017' '13-10-2017' '14-10-2017' '15-10-2017'\n",
            "  '16-10-2017' '17-10-2017' '18-10-2017' '19-10-2017' '20-10-2017'\n",
            "  '21-10-2017' '22-10-2017' '23-10-2017' '24-10-2017' '25-10-2017'\n",
            "  '26-10-2017' '27-10-2017' '28-10-2017' '29-10-2017' '30-10-2017'\n",
            "  '31-10-2017' '01-11-2017' '02-11-2017' '03-11-2017' '04-11-2017'\n",
            "  '05-11-2017' '06-11-2017' '07-11-2017' '08-11-2017' '09-11-2017'\n",
            "  '10-11-2017' '11-11-2017' '12-11-2017' '13-11-2017' '14-11-2017'\n",
            "  '15-11-2017' '16-11-2017' '17-11-2017' '18-11-2017' '19-11-2017'\n",
            "  '20-11-2017' '21-11-2017' '22-11-2017' '23-11-2017' '24-11-2017'\n",
            "  '25-11-2017' '26-11-2017' '27-11-2017' '28-11-2017' '29-11-2017'\n",
            "  '30-11-2017' '01-12-2017' '02-12-2017' '03-12-2017' '04-12-2017'\n",
            "  '05-12-2017' '06-12-2017' '07-12-2017' '08-12-2017' '09-12-2017'\n",
            "  '10-12-2017' '11-12-2017' '12-12-2017' '13-12-2017' '14-12-2017'\n",
            "  '15-12-2017' '16-12-2017' '17-12-2017' '18-12-2017' '19-12-2017'\n",
            "  '20-12-2017' '21-12-2017' '22-12-2017' '23-12-2017' '24-12-2017'\n",
            "  '25-12-2017' '26-12-2017' '27-12-2017' '28-12-2017' '29-12-2017'\n",
            "  '30-12-2017' '31-12-2017' '01-01-2018' '02-01-2018' '03-01-2018'\n",
            "  '04-01-2018' '05-01-2018' '06-01-2018' '07-01-2018' '08-01-2018'\n",
            "  '09-01-2018']\n",
            " ['5464' '6041' '25' '5461' '6915' '4545' '4340' '1230' '61' '1258'\n",
            "  '3148' '4687' '4732' '3519' '1580' '2822' '181' '3158' '4383' '3881'\n",
            "  '4037' '202' '292' '330' '2209' '4550' '4435' '4779' '1831' '2255'\n",
            "  '539' '5464' '6041' '4068' '4683' '4033' '6314' '614' '3149' '4005'\n",
            "  '4880' '4136' '705' '570' '269' '4275' '5999' '4421' '6930' '5195'\n",
            "  '546' '493' '995' '1163' '6676' '3608' '774' '1421' '4064' '2725'\n",
            "  '5934' '1867' '3721' '2374' '2909' '1648' '799' '7102' '3941' '7422'\n",
            "  '437' '1231' '1696' '4921' '221' '6500' '3575' '4061' '651' '753' '518'\n",
            "  '5537' '4108' '5376' '3066' '177' '36' '299' '1447' '2599' '702' '133'\n",
            "  '153' '500' '2127' '2203']\n",
            " ['Neutral' 'Sad' 'Sad' 'Sad' 'Neutral' 'Sad' 'Sad' 'Sad' 'Sad' 'Sad'\n",
            "  'Sad' 'Sad' 'Happy' 'Sad' 'Sad' 'Sad' 'Sad' 'Neutral' 'Neutral'\n",
            "  'Neutral' 'Neutral' 'Neutral' 'Neutral' 'Happy' 'Neutral' 'Happy'\n",
            "  'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Neutral' 'Happy'\n",
            "  'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy'\n",
            "  'Neutral' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy'\n",
            "  'Happy' 'Happy' 'Neutral' 'Sad' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy'\n",
            "  'Happy' 'Happy' 'Sad' 'Neutral' 'Neutral' 'Sad' 'Sad' 'Neutral'\n",
            "  'Neutral' 'Happy' 'Neutral' 'Neutral' 'Sad' 'Neutral' 'Sad' 'Neutral'\n",
            "  'Neutral' 'Sad' 'Sad' 'Sad' 'Sad' 'Happy' 'Neutral' 'Happy' 'Neutral'\n",
            "  'Sad' 'Sad' 'Sad' 'Neutral' 'Neutral' 'Sad' 'Sad' 'Happy' 'Neutral'\n",
            "  'Neutral' 'Happy']\n",
            " ['181' '197' '0' '174' '223' '149' '140' '38' '1' '40' '101' '152' '150'\n",
            "  '113' '49' '86' '6' '99' '143' '125' '129' '6' '9' '10' '72' '150'\n",
            "  '141' '156' '57' '72' '17' '181' '197' '131' '154' '137' '193' '19'\n",
            "  '101' '139' '164' '137' '22' '17' '9' '145' '192' '146' '234' '167'\n",
            "  '16' '17' '32' '35' '220' '116' '23' '44' '131' '86' '194' '60' '121'\n",
            "  '76' '93' '53' '25' '227' '125' '243' '14' '39' '55' '158' '7' '213'\n",
            "  '116' '129' '21' '28' '16' '180' '138' '176' '99' '5' '1' '10' '47'\n",
            "  '84' '23' '4' '0' '0' '0' '0']\n",
            " ['5' '8' '5' '4' '5' '6' '6' '7' '5' '6' '8' '5' '6' '7' '5' '6' '8' '5'\n",
            "  '4' '5' '6' '8' '5' '6' '5' '8' '5' '4' '5' '4' '5' '4' '3' '2' '9' '5'\n",
            "  '6' '4' '5' '8' '4' '5' '6' '5' '6' '5' '6' '5' '6' '5' '6' '7' '6' '7'\n",
            "  '6' '5' '6' '7' '8' '8' '7' '8' '5' '4' '3' '3' '4' '5' '5' '5' '3' '4'\n",
            "  '4' '5' '5' '5' '5' '5' '5' '4' '3' '4' '5' '5' '4' '5' '3' '3' '3' '2'\n",
            "  '3' '2' '8' '5' '5' '5']\n",
            " ['Inactive' 'Inactive' 'Inactive' 'Inactive' 'Active' 'Inactive'\n",
            "  'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive'\n",
            "  'Active' 'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive'\n",
            "  'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive'\n",
            "  'Inactive' 'Active' 'Inactive' 'Inactive' 'Inactive' 'Inactive'\n",
            "  'Active' 'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive'\n",
            "  'Active' 'Active' 'Active' 'Active' 'Active' 'Active' 'Active' 'Active'\n",
            "  'Active' 'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive'\n",
            "  'Inactive' 'Active' 'Active' 'Active' 'Active' 'Active' 'Active'\n",
            "  'Active' 'Active' 'Active' 'Active' 'Active' 'Active' 'Inactive'\n",
            "  'Active' 'Active' 'Inactive' 'Active' 'Active' 'Active' 'Active'\n",
            "  'Active' 'Inactive' 'Active' 'Active' 'Active' 'Active' 'Inactive'\n",
            "  'Inactive' 'Inactive' 'Inactive' 'Active' 'Active' 'Active' 'Active'\n",
            "  'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive' 'Inactive'\n",
            "  'Inactive' 'Inactive' 'Active' 'Inactive' 'Active']]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "step_count = data_t[1]\n",
        "print(step_count)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FRVplYsqOuba",
        "outputId": "ee08fc26-48ca-49a5-c5e6-dc89c87df31e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['5464' '6041' '25' '5461' '6915' '4545' '4340' '1230' '61' '1258' '3148'\n",
            " '4687' '4732' '3519' '1580' '2822' '181' '3158' '4383' '3881' '4037'\n",
            " '202' '292' '330' '2209' '4550' '4435' '4779' '1831' '2255' '539' '5464'\n",
            " '6041' '4068' '4683' '4033' '6314' '614' '3149' '4005' '4880' '4136'\n",
            " '705' '570' '269' '4275' '5999' '4421' '6930' '5195' '546' '493' '995'\n",
            " '1163' '6676' '3608' '774' '1421' '4064' '2725' '5934' '1867' '3721'\n",
            " '2374' '2909' '1648' '799' '7102' '3941' '7422' '437' '1231' '1696'\n",
            " '4921' '221' '6500' '3575' '4061' '651' '753' '518' '5537' '4108' '5376'\n",
            " '3066' '177' '36' '299' '1447' '2599' '702' '133' '153' '500' '2127'\n",
            " '2203']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "step_count = np.array(step_count, dtype = \"int\")\n",
        "step_count"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jToTIReoPED7",
        "outputId": "a27895a8-1717-4f45-961d-6077125e3c13"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([5464, 6041,   25, 5461, 6915, 4545, 4340, 1230,   61, 1258, 3148,\n",
              "       4687, 4732, 3519, 1580, 2822,  181, 3158, 4383, 3881, 4037,  202,\n",
              "        292,  330, 2209, 4550, 4435, 4779, 1831, 2255,  539, 5464, 6041,\n",
              "       4068, 4683, 4033, 6314,  614, 3149, 4005, 4880, 4136,  705,  570,\n",
              "        269, 4275, 5999, 4421, 6930, 5195,  546,  493,  995, 1163, 6676,\n",
              "       3608,  774, 1421, 4064, 2725, 5934, 1867, 3721, 2374, 2909, 1648,\n",
              "        799, 7102, 3941, 7422,  437, 1231, 1696, 4921,  221, 6500, 3575,\n",
              "       4061,  651,  753,  518, 5537, 4108, 5376, 3066,  177,   36,  299,\n",
              "       1447, 2599,  702,  133,  153,  500, 2127, 2203])"
            ]
          },
          "metadata": {},
          "execution_count": 133
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mood = data_t[2]\n",
        "print(mood)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rip8NB7rPLoj",
        "outputId": "7eebf6e5-995c-48c0-ab06-dc4fb00e010e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['Neutral' 'Sad' 'Sad' 'Sad' 'Neutral' 'Sad' 'Sad' 'Sad' 'Sad' 'Sad' 'Sad'\n",
            " 'Sad' 'Happy' 'Sad' 'Sad' 'Sad' 'Sad' 'Neutral' 'Neutral' 'Neutral'\n",
            " 'Neutral' 'Neutral' 'Neutral' 'Happy' 'Neutral' 'Happy' 'Happy' 'Happy'\n",
            " 'Happy' 'Happy' 'Happy' 'Happy' 'Neutral' 'Happy' 'Happy' 'Happy' 'Happy'\n",
            " 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Neutral' 'Happy' 'Happy'\n",
            " 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Neutral' 'Sad'\n",
            " 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Happy' 'Sad' 'Neutral'\n",
            " 'Neutral' 'Sad' 'Sad' 'Neutral' 'Neutral' 'Happy' 'Neutral' 'Neutral'\n",
            " 'Sad' 'Neutral' 'Sad' 'Neutral' 'Neutral' 'Sad' 'Sad' 'Sad' 'Sad' 'Happy'\n",
            " 'Neutral' 'Happy' 'Neutral' 'Sad' 'Sad' 'Sad' 'Neutral' 'Neutral' 'Sad'\n",
            " 'Sad' 'Happy' 'Neutral' 'Neutral' 'Happy']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "b = np.unique(mood)"
      ],
      "metadata": {
        "id": "Kglwww_kPXrS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(b)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p9M39_8MPfTK",
        "outputId": "4d2f2fbc-0cef-4582-c12c-de0e02ab3d67"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['Happy' 'Neutral' 'Sad']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#avg step counts that you take when your mood is Happy"
      ],
      "metadata": {
        "id": "K4CY5B5TPhoa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mood == \"Happy\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uyStccWKP8i2",
        "outputId": "5826f358-c36d-4a31-abbc-9f8506aa683a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([False, False, False, False, False, False, False, False, False,\n",
              "       False, False, False,  True, False, False, False, False, False,\n",
              "       False, False, False, False, False,  True, False,  True,  True,\n",
              "        True,  True,  True,  True,  True, False,  True,  True,  True,\n",
              "        True,  True,  True,  True,  True,  True,  True, False,  True,\n",
              "        True,  True,  True,  True,  True,  True,  True,  True, False,\n",
              "       False,  True,  True,  True,  True,  True,  True,  True, False,\n",
              "       False, False, False, False, False, False,  True, False, False,\n",
              "       False, False, False, False, False, False, False, False, False,\n",
              "        True, False,  True, False, False, False, False, False, False,\n",
              "       False, False,  True, False, False,  True])"
            ]
          },
          "metadata": {},
          "execution_count": 140
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "happy_step_count = step_count[mood == \"Happy\"]\n",
        "print(happy_step_count)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "De8Yu771Pt5A",
        "outputId": "d3a4e70b-e4ee-4cf7-a3cf-c1ec1a593454"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[4732  330 4550 4435 4779 1831 2255  539 5464 4068 4683 4033 6314  614\n",
            " 3149 4005 4880 4136  705  269 4275 5999 4421 6930 5195  546  493  995\n",
            " 3608  774 1421 4064 2725 5934 1867 7422 5537 5376  153 2203]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#step counts when mood is sad\n",
        "sad_step_count = step_count[mood == \"Sad\"]\n",
        "print(sad_step_count)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3SX522RBP5Th",
        "outputId": "17a021a8-b574-4ec6-fbc4-11fbe4aaa925"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[6041   25 5461 4545 4340 1230   61 1258 3148 4687 3519 1580 2822  181\n",
            " 6676 3721 1648  799 1696  221 4061  651  753  518  177   36  299  702\n",
            "  133]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "happy_step_count = step_count[mood == \"Happy\"]\n",
        "print(happy_step_count)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GZg-zSyqQNQo",
        "outputId": "5100609c-349e-4931-cc7f-bfc5ae9a2ce4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[4732  330 4550 4435 4779 1831 2255  539 5464 4068 4683 4033 6314  614\n",
            " 3149 4005 4880 4136  705  269 4275 5999 4421 6930 5195  546  493  995\n",
            " 3608  774 1421 4064 2725 5934 1867 7422 5537 5376  153 2203]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "avg_happy = np.mean(happy_step_count)\n",
        "print(avg_happy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dk4d0BzUQSQK",
        "outputId": "c9c5ef2a-24a9-4a15-fed3-1daf7a8b987f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3392.725\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#give me step counts when the mood was either Happy or Neutral"
      ],
      "metadata": {
        "id": "NqB_po6IQYjp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "happy_neutral_steps = step_count[(mood == \"Happy\") | (mood == \"Neutral\")]\n"
      ],
      "metadata": {
        "id": "4CHpQ3pwQi8M"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(happy_neutral_steps)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vzV02OMMRFHs",
        "outputId": "f115982a-84c6-4be9-fc56-ce1a14844a4d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[5464 6915 4732 3158 4383 3881 4037  202  292  330 2209 4550 4435 4779\n",
            " 1831 2255  539 5464 6041 4068 4683 4033 6314  614 3149 4005 4880 4136\n",
            "  705  570  269 4275 5999 4421 6930 5195  546  493  995 1163 3608  774\n",
            " 1421 4064 2725 5934 1867 2374 2909 7102 3941 7422  437 1231 4921 6500\n",
            " 3575 5537 4108 5376 3066 1447 2599  153  500 2127 2203]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "'''\n",
        "or --> |\n",
        "and --> &\n",
        "'''"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "rjWDr-BrRBzC",
        "outputId": "ef5209b8-5a26-4358-e8af-9b0d85db53b2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'\\nor --> |\\nand --> &\\n'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 148
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#HW -> Try to compare the avg steps the user takes when mood is Happy and when mood is Sad"
      ],
      "metadata": {
        "id": "4akrsz1QREB5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#HW --> Explore linspace()"
      ],
      "metadata": {
        "id": "l7u1xMkpRUU6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#doubt\n",
        "a=np.arange(12).reshape(3,4)\n",
        "print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cGTCwkz7ShAt",
        "outputId": "3b0c3ff0-6e8a-4639-f0aa-bc33feb730a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  1  2  3]\n",
            " [ 4  5  6  7]\n",
            " [ 8  9 10 11]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[:2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jPAWrDrHStX3",
        "outputId": "a2167c94-02c0-409e-996a-4f46d4d5424d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0, 1, 2, 3],\n",
              "       [4, 5, 6, 7]])"
            ]
          },
          "metadata": {},
          "execution_count": 153
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[2:]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FJtpd3poSyu8",
        "outputId": "997f2972-4b71-499b-bde0-fdca2e1c7a31"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 8,  9, 10, 11]])"
            ]
          },
          "metadata": {},
          "execution_count": 154
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = [4,7,2]\n",
        "a1= np.array(a)\n",
        "print(a1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QKXHhtUfS1uM",
        "outputId": "046a9f05-7367-4439-d86f-ac06379c8aa8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[4 7 2]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = [[1,4], [6,7]]\n",
        "a1 = np.array(a)\n",
        "print(a1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8EmNq3RmTAPn",
        "outputId": "b04d44ee-e86d-4525-ee05-a2c283e1aed1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[1 4]\n",
            " [6 7]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(4)\n",
        "b = np.arange(5)\n",
        "a+b"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 211
        },
        "id": "Hpzx8pm-TKQR",
        "outputId": "68e84491-e26a-4eb9-b17d-249fb3d93eff"
      },
      "execution_count": null,
      "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-157-11b6044bd194>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (4,) (5,) "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.array([100,200,300,400,500,600])\n",
        "a[2,3]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        },
        "id": "1pfS5wLvTT2w",
        "outputId": "3b15e629-deb3-4aa8-b9a2-9916cf710ae3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "IndexError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-158-bb8584b10786>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m400\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m500\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m600\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----> 2\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m: too many indices for array: array is 1-dimensional, but 2 were indexed"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a[ [2, 5] ]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e4eF8R8DTiwo",
        "outputId": "314d6e73-696d-45ce-81ba-73edd656b8fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([300, 600])"
            ]
          },
          "metadata": {},
          "execution_count": 159
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "3k6Eejo4Tmnq"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}