colab_d12_02.ipynb

{
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  "metadata": {
    "colab": {
      "name": "colab_d12_02.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMvuR+tLjTfOryRHODB75Al",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/OHTORO87/ai_class/blob/main/colab_d12_02.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "69FRw-qGNACR"
      },
      "source": [
        "## 시작하기전에 해야할일"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LIKaB2gWMmBm"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "#시작하면 항상 이거 2개 치고 시작"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aUD52VhvNLrh"
      },
      "source": [
        "n1 = numpy 1차원,\n",
        "s1 = series,\n",
        "d1 = dataframe.\n",
        "\n",
        "이런식으로 이름 지어주자\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ArbAA_acMx_E"
      },
      "source": [
        "n1 = np.random.randint(0, 100, 10)"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i3XUj8xmNpC6",
        "outputId": "dee8cce0-303d-40a7-9344-cd450362b9f6"
      },
      "source": [
        "type(n1)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "numpy.ndarray"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UykRbRbZNrPZ",
        "outputId": "fb68c013-2b57-4278-cdf6-b91f406f9662"
      },
      "source": [
        "n1.shape"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wKxRpOl8Nspr",
        "outputId": "64ea9685-9dae-4c4f-bc44-32803fd5a299"
      },
      "source": [
        "n1.ndim"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pa9wmZOMNuCL",
        "outputId": "c8458797-7dfc-46cd-a670-c2de8adfa611"
      },
      "source": [
        "n1.size"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ufwwNY49NvoA",
        "outputId": "691c3e3b-a016-4a72-c94f-8417d2ae7348"
      },
      "source": [
        "n1.nbytes"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "80"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NfD69FJ2NxG8",
        "outputId": "7b1c09bf-6a27-4a35-943e-da6f9129b852"
      },
      "source": [
        "n1.itemsize"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sCBNRkRHN-oq"
      },
      "source": [
        "n = n1.copy()"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "weG3RQbWOB-Y",
        "outputId": "c687eb0f-ea0b-4821-89d3-b8558bfcbddb"
      },
      "source": [
        "n[:]"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([21, 39, 26, 77, 26, 30, 42, 61, 94, 73])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DfDXR-0NOFzQ",
        "outputId": "91b8bf70-9e1b-4aea-9b8c-b6bb5fcaf417"
      },
      "source": [
        "n[0:10]"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([21, 39, 26, 77, 26, 30, 42, 61, 94, 73])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "khtUc2qoOHsh",
        "outputId": "77b71920-9245-4e81-94bb-28b7ffda2af8"
      },
      "source": [
        "n[0:10:2]"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([21, 26, 26, 42, 94])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sy8wgyVHOJ0I",
        "outputId": "4dc232ea-ebce-4f0f-e094-df80117ad532"
      },
      "source": [
        "n[0:10:3]"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([21, 77, 42, 73])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZO58ULL0OMLx",
        "outputId": "3f9f39ce-08b9-4393-8144-5398a46f43e2"
      },
      "source": [
        "n[::-1]"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([73, 94, 61, 42, 30, 26, 77, 26, 39, 21])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3qKh-XPfONoA",
        "outputId": "76e2722e-6c9f-40fa-f369-03e1fa2e89fe"
      },
      "source": [
        "n[::-2]"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([73, 61, 30, 77, 39])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LLNBRUHwOOtg",
        "outputId": "86d1ab66-5765-40b3-d3c8-25133addda9b"
      },
      "source": [
        "n.reshape(2, 5)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[21, 39, 26, 77, 26],\n",
              "       [30, 42, 61, 94, 73]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ng0RmcstOY0Y",
        "outputId": "9f8ca3e0-b228-4f4f-bed6-e5e3feab3102"
      },
      "source": [
        "n.reshape(5, 2)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[21, 39],\n",
              "       [26, 77],\n",
              "       [26, 30],\n",
              "       [42, 61],\n",
              "       [94, 73]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 176
        },
        "id": "yWnYoxRNOecQ",
        "outputId": "c56b1d46-3a51-49cb-8512-969ba393bc57"
      },
      "source": [
        "n.reshape(3, 3)\n",
        "#n이 10개여서 3x3으로 출력 불가"
      ],
      "execution_count": 26,
      "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-26-b72301a57d37>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3\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;31mValueError\u001b[0m: cannot reshape array of size 10 into shape (3,3)"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ddeHiDLOhjV"
      },
      "source": [
        "n1.sort()"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZVw9UiWQOt0B",
        "outputId": "1134b8f8-1891-41a3-8036-0c61ce1cd030"
      },
      "source": [
        "n1"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([21, 26, 26, 30, 39, 42, 61, 73, 77, 94])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 176
        },
        "id": "AekPqjsyOyj5",
        "outputId": "c4948b87-b044-41c7-bf08-ddd322f59108"
      },
      "source": [
        "n1.sort(axis=1)\n",
        "#1차원이라 axis가 없어서 에러남"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AxisError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAxisError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-31-66fe5a22191e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mn1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\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;31mAxisError\u001b[0m: axis 1 is out of bounds for array of dimension 1"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aU66Y9y2O70R"
      },
      "source": [
        "n1.sort?\n",
        "# ? 도움말"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BTy8n-YpPIao"
      },
      "source": [
        "n2 = np.random.randint(1, 100, 12)"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n04DOPGFP36n",
        "outputId": "14e84df3-93d4-4ba3-d5a7-c06109bd7e29"
      },
      "source": [
        "n2"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([45, 88, 87, 10, 84, 31,  2, 55,  8, 31, 89, 38])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c_KwDN01P4o4",
        "outputId": "9a7d75c7-3cb9-4fd7-fcdd-db380fbb0973"
      },
      "source": [
        "n2.reshape(3, 4)"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[45, 88, 87, 10],\n",
              "       [84, 31,  2, 55],\n",
              "       [ 8, 31, 89, 38]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3V20Z1BSP8PZ",
        "outputId": "de98de6b-2d52-4072-b3d9-1d85a5232f7c"
      },
      "source": [
        "n2.reshape(2, 6)"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[45, 88, 87, 10, 84, 31],\n",
              "       [ 2, 55,  8, 31, 89, 38]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zg9JQXQNQDbt",
        "outputId": "aedaff6b-d576-41cd-f6b4-124fd4892a45"
      },
      "source": [
        "n2.reshape(4, 3)"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[45, 88, 87],\n",
              "       [10, 84, 31],\n",
              "       [ 2, 55,  8],\n",
              "       [31, 89, 38]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eiurpNMXQvFS"
      },
      "source": [
        "# 아 이거 기억 잘해놓자\n",
        "\n",
        "# int16 = 2byte"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_rpwGbnKQKxw"
      },
      "source": [
        "n21 = np.arange(1, 17, dtype=np.int16)"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gFUXWi7IQchq",
        "outputId": "00508801-20ed-44e5-cebf-841d2fe4c458"
      },
      "source": [
        "n21"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16],\n",
              "      dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "30XxZMIDQjwf"
      },
      "source": [
        "n = n21.reshape(4, 4)"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J4E5wBSUQo9v",
        "outputId": "7498e502-0f19-4f60-f3ad-5926c9f78c81"
      },
      "source": [
        "n"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1,  2,  3,  4],\n",
              "       [ 5,  6,  7,  8],\n",
              "       [ 9, 10, 11, 12],\n",
              "       [13, 14, 15, 16]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IWi_Aoj0QsFL",
        "outputId": "91c08e58-f4a2-4657-99df-66cc4244f040"
      },
      "source": [
        "n[:]"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1,  2,  3,  4],\n",
              "       [ 5,  6,  7,  8],\n",
              "       [ 9, 10, 11, 12],\n",
              "       [13, 14, 15, 16]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pTaSsNBLQ-y9",
        "outputId": "0b968b3a-a0b4-4f6e-9fea-15d9b8b0e4cc"
      },
      "source": [
        "n[ : , : ]"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1,  2,  3,  4],\n",
              "       [ 5,  6,  7,  8],\n",
              "       [ 9, 10, 11, 12],\n",
              "       [13, 14, 15, 16]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rjr53ZYYRDAw",
        "outputId": "35696aef-3938-433c-d322-f0f1192595bc"
      },
      "source": [
        "n[0,3]"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "layYt1TbRK8A",
        "outputId": "513b4b73-661e-4b2a-ef83-f67a37b94aaa"
      },
      "source": [
        "n[0:2,1:3]"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[2, 3],\n",
              "       [6, 7]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HZ8ItYRgRVnq",
        "outputId": "9b7bbe99-ffaf-4ae9-8b30-995fcd482af0"
      },
      "source": [
        "n[1:5, 2:5]"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 7,  8],\n",
              "       [11, 12],\n",
              "       [15, 16]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ctSLza_7RhFp",
        "outputId": "6a8f06f1-8891-40f1-a9cd-23b7e242cf7b"
      },
      "source": [
        "n[2:,0:2]"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 9, 10],\n",
              "       [13, 14]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8MqZkT7KRpcq",
        "outputId": "750a0dfe-96c4-4049-bda3-c4320bafc9cc"
      },
      "source": [
        "n[0,1:3]"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2, 3], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iAHjgEudRx5X",
        "outputId": "5779492f-0114-478f-ed2d-d6b7abd1740e"
      },
      "source": [
        "n[2:,1:3]"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[10, 11],\n",
              "       [14, 15]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wLdUwQ-oR99_"
      },
      "source": [
        "a = [2, 3, 5]"
      ],
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0DeFq6_2SBQX"
      },
      "source": [
        "S = 0"
      ],
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qi2g_TatSy-v"
      },
      "source": [
        "# 특정 데이터에 연산이 가능하다"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K0S9WsxZSC3f",
        "outputId": "f261d1ee-4454-4cba-809a-f24aed296c12"
      },
      "source": [
        "n[2:4, 1:3]*3\n",
        "# 특정 데이터에 연산이 가능하다"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[30, 33],\n",
              "       [42, 45]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EmHRVCIcSgv0",
        "outputId": "9bc508d8-dd33-431f-8297-034a4866d705"
      },
      "source": [
        "n[2:4, 1:3] == 0\n"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[False, False],\n",
              "       [False, False]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4aZMQ1WVSoE_",
        "outputId": "d21b6b02-4ce6-48b6-e111-8354f6402b0f"
      },
      "source": [
        "n[0]"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 2, 3, 4], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tCG22MAfSp7A",
        "outputId": "949e39ca-0072-4412-a2bc-1d90a99fa8d0"
      },
      "source": [
        "n[0] < 5"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ True,  True,  True,  True])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Oe8lwUsASuri",
        "outputId": "b6cf9a9c-4e39-43f3-df99-046b33f0c223"
      },
      "source": [
        "n > 10"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[False, False, False, False],\n",
              "       [False, False, False, False],\n",
              "       [False, False,  True,  True],\n",
              "       [ True,  True,  True,  True]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9iO65rdaS5rv",
        "outputId": "8a1b7b48-ad58-4db7-d722-1bef125754be"
      },
      "source": [
        "n[0][0] == 100"
      ],
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LkhZjNlgS84e",
        "outputId": "3d77ccae-3726-4210-ed4c-7d940df0e415"
      },
      "source": [
        "n[:,0:1]\n",
        "# n[:, 0] 하고 결과가 다르다"
      ],
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1],\n",
              "       [ 5],\n",
              "       [ 9],\n",
              "       [13]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3LEgIXs8TTdq"
      },
      "source": [
        "n[0][3] = 44"
      ],
      "execution_count": 73,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gHrVWhPzTvM4",
        "outputId": "38665bbb-116f-4b05-cd40-b578163da28f"
      },
      "source": [
        "n"
      ],
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1,  2,  3, 44],\n",
              "       [ 5,  6,  7,  8],\n",
              "       [ 9, 10, 11, 12],\n",
              "       [13, 14, 15, 16]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "toC8V3wjTwU2"
      },
      "source": [
        "n[:, 3] = 100\n",
        "# n[:, -1] 도 같은 결과 나옴"
      ],
      "execution_count": 75,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DjCyF9YKT7e3",
        "outputId": "1d2c46ea-5f8f-466d-82c7-97fb9e498d59"
      },
      "source": [
        "n"
      ],
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[  1,   2,   3, 100],\n",
              "       [  5,   6,   7, 100],\n",
              "       [  9,  10,  11, 100],\n",
              "       [ 13,  14,  15, 100]], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3c2-j7eKULZc"
      },
      "source": [
        "# 합계 구하기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "umLKM37bT8JM",
        "outputId": "bcb13bf4-86e9-456e-e662-ef0180043b7e"
      },
      "source": [
        "n[0].sum()\n",
        "# 0행의 총합"
      ],
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "106"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tr4D20YsURwA",
        "outputId": "eee494c7-56fb-4222-93bf-faba7c50d2a6"
      },
      "source": [
        "n.max()"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "100"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Au7OgZVMUXBe",
        "outputId": "cef2555d-3a2a-4637-a9fa-cf4d95048e38"
      },
      "source": [
        "n.max(axis=1)"
      ],
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([100, 100, 100, 100], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xNtp64jDUdQj",
        "outputId": "b8c24be4-93de-4a70-8813-55f52719e9b8"
      },
      "source": [
        "n.max(axis=0)"
      ],
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 13,  14,  15, 100], dtype=int16)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hK_eXGLdUlfI",
        "outputId": "582f7d91-cc8e-4670-fdfc-25bd8db802a7"
      },
      "source": [
        "n.mean()"
      ],
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "31.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I5jzNGKeUwSA",
        "outputId": "7d2dccf3-af90-4d07-9ebf-88a357a32dbc"
      },
      "source": [
        "n.std()"
      ],
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "40.03123780249619"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KndaXV-eUx1Q",
        "outputId": "28434403-13f1-4afb-cd3f-ae2a9bebb9fe"
      },
      "source": [
        "n.var()"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1602.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yeSUpUUtU2Ib",
        "outputId": "22f25637-f9df-448c-996b-6abf954411cc"
      },
      "source": [
        "np.median(n)"
      ],
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XlJVCUYiU-WE",
        "outputId": "e9aeda63-b41f-4d0a-cc6d-97567604f230"
      },
      "source": [
        "np.median(n[0])\n",
        "# 0행에서의 중앙값"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JMjaZNsqVL7B",
        "outputId": "afd1ef06-1f76-4dfb-98e6-bf95b37968a3"
      },
      "source": [
        "np.zeros(5)"
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0., 0., 0., 0., 0.])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "roHx_Fr3Wk5a",
        "outputId": "a64e5736-05e5-4f8f-c4c1-afbcdb0cf85e"
      },
      "source": [
        "np.ones(5)\n",
        "# 제로하고 원스만 있따"
      ],
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1., 1., 1., 1., 1.])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QrnrcwONWq0F",
        "outputId": "9832438f-d259-4a7c-8f70-fff6198ebd5e"
      },
      "source": [
        "np.tri(10)"
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
              "       [1., 1., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
              "       [1., 1., 1., 0., 0., 0., 0., 0., 0., 0.],\n",
              "       [1., 1., 1., 1., 0., 0., 0., 0., 0., 0.],\n",
              "       [1., 1., 1., 1., 1., 0., 0., 0., 0., 0.],\n",
              "       [1., 1., 1., 1., 1., 1., 0., 0., 0., 0.],\n",
              "       [1., 1., 1., 1., 1., 1., 1., 0., 0., 0.],\n",
              "       [1., 1., 1., 1., 1., 1., 1., 1., 0., 0.],\n",
              "       [1., 1., 1., 1., 1., 1., 1., 1., 1., 0.],\n",
              "       [1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w1_K7rJBWuoG",
        "outputId": "161cb0eb-b5ac-4010-a3e3-d247e6ef4803"
      },
      "source": [
        "np.empty(6)\n",
        "# 비어있는 공간을 6개 가지고 온거임\n",
        "# 나중에 채우려고 빈 공간을 만들어낸것"
      ],
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([4.68887684e-310, 0.00000000e+000, 0.00000000e+000, 0.00000000e+000,\n",
              "       0.00000000e+000, 0.00000000e+000])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Utk-AOKsW85m",
        "outputId": "58bcae48-508a-4cf8-9d7c-d3fad68780fa"
      },
      "source": [
        "np.zeros((2,6))"
      ],
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0., 0., 0., 0., 0., 0.],\n",
              "       [0., 0., 0., 0., 0., 0.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y26jLscFXN4y",
        "outputId": "53c53c66-9779-427d-8a03-8f56891de618"
      },
      "source": [
        "np.ones((3,4))"
      ],
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1., 1., 1., 1.],\n",
              "       [1., 1., 1., 1.],\n",
              "       [1., 1., 1., 1.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y9srqyE6Xwz8"
      },
      "source": [
        "## bytes 알아보는법"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FiGr6rnUXRog"
      },
      "source": [
        "n7 = np.array([4,5,6,7])"
      ],
      "execution_count": 103,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9MWy8Q61XY4T",
        "outputId": "0c999f22-0dcd-44b2-8156-7eb51987f442"
      },
      "source": [
        "n7.nbytes"
      ],
      "execution_count": 106,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "32"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 106
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z0ER84SnXcK2"
      },
      "source": [
        "n8 = np.array([4,5,6,7], np.int32)"
      ],
      "execution_count": 107,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cbjvfFcvXqZW",
        "outputId": "5e3dee28-1daf-43dc-fdbd-0252a245557c"
      },
      "source": [
        "n8.nbytes"
      ],
      "execution_count": 108,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sDj_Q2PqXs6V"
      },
      "source": [
        "k = [i for i in range(5, 51, 5)]"
      ],
      "execution_count": 109,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ruvEPpiEX4nP",
        "outputId": "a63c447f-1656-48d0-ca67-13a211970229"
      },
      "source": [
        "k"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[5, 10, 15, 20, 25, 30, 35, 40, 45, 50]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Nm-mxOKX5ym",
        "outputId": "e8bf9db0-34d3-4f26-ffe0-caa027eb1b97"
      },
      "source": [
        "type(k)"
      ],
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LSwKelqlX7OM"
      },
      "source": [
        "t = (i for i in range(10, 101, 10))"
      ],
      "execution_count": 112,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y1xUeoORYFMu",
        "outputId": "0c15428f-7bf8-4717-97aa-6ef2fdce935a"
      },
      "source": [
        "t"
      ],
      "execution_count": 113,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<generator object <genexpr> at 0x7fbecbb5ea50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EpJDATLSYGOc",
        "outputId": "db563a0a-19b5-4cf6-fdc4-bef229422f22"
      },
      "source": [
        "type(t)\n",
        "# list가 가지고 있는 주소값을 알려줌?\n",
        "# generator"
      ],
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "generator"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 120
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IhI8NQgJYHip"
      },
      "source": [
        "n10 = np.array(k)"
      ],
      "execution_count": 115,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YtHxXSU-YM8z",
        "outputId": "e8d066df-1a44-43bd-f661-253932f833f2"
      },
      "source": [
        "n10"
      ],
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 5, 10, 15, 20, 25, 30, 35, 40, 45, 50])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "578emdMuYO-K",
        "outputId": "66eb6f36-b152-4225-fa0c-aaa93d30851a"
      },
      "source": [
        "np.array(t)"
      ],
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(<generator object <genexpr> at 0x7fbecbb5ea50>, dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HZnSTo9YYWfJ",
        "outputId": "9c021fdd-1f46-4cb5-a63a-cdc04d91017d"
      },
      "source": [
        "t"
      ],
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<generator object <genexpr> at 0x7fbecbb5ea50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OdKc5GQCYYZF"
      },
      "source": [
        "n12 = np.array(k)"
      ],
      "execution_count": 126,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7LXw-rs8Zh1O"
      },
      "source": [
        "# 시리즈 시작"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RopvrufJZAY2"
      },
      "source": [
        "s1 = pd.Series([2, 4, 6, 8])"
      ],
      "execution_count": 127,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_pJGoLhoZrUE",
        "outputId": "21e83598-074f-4d42-925a-6a3caa63a972"
      },
      "source": [
        "type(s1)\n",
        "# 데이터의 구조를 먼저 파악하라"
      ],
      "execution_count": 129,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.series.Series"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 129
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lIyu__nbZtO3",
        "outputId": "a86c8ac0-e4e1-4099-ba8f-1b42c0c056be"
      },
      "source": [
        "s1.shape"
      ],
      "execution_count": 130,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 130
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8TI-NTCNZxkD",
        "outputId": "4fd1a16b-6892-42eb-d7d3-4770b7f2d108"
      },
      "source": [
        "s1.ndim"
      ],
      "execution_count": 131,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 131
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D6YF_SyEZz2W",
        "outputId": "877e3857-bd3e-48f3-a925-b813c7d80cca"
      },
      "source": [
        "s1.nbytes"
      ],
      "execution_count": 132,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "32"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 132
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IIi1K_4cZ50P",
        "outputId": "c7277540-e636-459c-d523-d995b6e2b478"
      },
      "source": [
        "s1.items"
      ],
      "execution_count": 133,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method Series.items of 0    2\n",
              "1    4\n",
              "2    6\n",
              "3    8\n",
              "dtype: int64>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 133
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "14zqQHIDZ-zW",
        "outputId": "f83e136c-af5d-4b65-9a18-33e8324a04c7"
      },
      "source": [
        "s1.index"
      ],
      "execution_count": 134,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RangeIndex(start=0, stop=4, step=1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 134
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u_YekycGaBzs",
        "outputId": "c8015fdd-2960-4f88-aade-3d1280bd65a4"
      },
      "source": [
        "s1\n",
        "# 좌측 인덱스, 우측이 값\n",
        "# 인덱스 묵시적으로 0,1,2,3으로 지정됨(디폴트값)"
      ],
      "execution_count": 136,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    2\n",
              "1    4\n",
              "2    6\n",
              "3    8\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 136
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X4gboWgIaL1e"
      },
      "source": [
        "s1.index=[['T', 'K', 'B', 'Q']]\n",
        "# 인덱스 명시적 지정"
      ],
      "execution_count": 140,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "99fPSpziafbM",
        "outputId": "96f908a7-5d93-4d57-a3e3-5a8d1d4aec3e"
      },
      "source": [
        "s1\n",
        "# 인덱스를 지정할수 있따."
      ],
      "execution_count": 141,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "T    2\n",
              "K    4\n",
              "B    6\n",
              "Q    8\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 141
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "si_-S5tfatkj"
      },
      "source": [
        "s1.index=[['류현진', '추신수', '투머치토커', '세리박']]"
      ],
      "execution_count": 142,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YS2BCMyobfQb",
        "outputId": "a90c4e91-30fd-4489-9e4e-743b0b90e1f6"
      },
      "source": [
        "s1"
      ],
      "execution_count": 143,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "류현진      2\n",
              "추신수      4\n",
              "투머치토커    6\n",
              "세리박      8\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 143
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Go37WAQTbgJs",
        "outputId": "99d73a88-fc91-4ff2-cb43-1898b0db1dd8"
      },
      "source": [
        "s1[0]"
      ],
      "execution_count": 144,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 144
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TYzYuy_HbilD",
        "outputId": "4416cc4d-3180-4397-f912-ce739e24b1f1"
      },
      "source": [
        "s1[2]"
      ],
      "execution_count": 145,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 145
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kim9hmE1bjwJ",
        "outputId": "a04d8020-bf09-4791-d9f2-c08560ae9d0c"
      },
      "source": [
        "s1['류현진']\n",
        "# 인덱스값에 접근할수있따"
      ],
      "execution_count": 147,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "류현진    2\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 147
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U3-J74LvbqjV",
        "outputId": "1f2ea193-22d5-4aa6-9175-dc0f4cd06c2b"
      },
      "source": [
        "s1.iloc[2]\n",
        "# loc 앞에 i가 index를 뜻한다.\n",
        "# loc = location"
      ],
      "execution_count": 152,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 152
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QviJB4mDb3aM",
        "outputId": "ed99b8a8-f9a3-4fef-c6d0-0e5cb5679780"
      },
      "source": [
        "s1.loc['추신수']"
      ],
      "execution_count": 153,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "추신수    4\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 153
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OJRk06Swip5f"
      },
      "source": [
        "## 샘플데이터 활용"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y3ZT6VNPcujC"
      },
      "source": [
        "pd1 = pd.read_csv('/content/sample_data/california_housing_test.csv')"
      ],
      "execution_count": 154,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iC4rGNoAiy6L",
        "outputId": "91acade6-3558-46a2-fbb7-4f26db834efb"
      },
      "source": [
        "type(pd1)"
      ],
      "execution_count": 156,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.frame.DataFrame"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 156
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tmxjyJCYizyv",
        "outputId": "c39ef841-3383-4c93-de98-594212b3e4cb"
      },
      "source": [
        "pd1.shape"
      ],
      "execution_count": 157,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3000, 9)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 157
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-NE37v3Mi9Il"
      },
      "source": [
        "p = pd1.copy()"
      ],
      "execution_count": 158,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "yvRbe6KkjDlV",
        "outputId": "1bd385c7-aa87-4d2c-e046-589f4cbf2c2c"
      },
      "source": [
        "p\n",
        "# 기본값 10개만 출력"
      ],
      "execution_count": 160,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-122.05</td>\n",
              "      <td>37.37</td>\n",
              "      <td>27.0</td>\n",
              "      <td>3885.0</td>\n",
              "      <td>661.0</td>\n",
              "      <td>1537.0</td>\n",
              "      <td>606.0</td>\n",
              "      <td>6.6085</td>\n",
              "      <td>344700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-118.30</td>\n",
              "      <td>34.26</td>\n",
              "      <td>43.0</td>\n",
              "      <td>1510.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>809.0</td>\n",
              "      <td>277.0</td>\n",
              "      <td>3.5990</td>\n",
              "      <td>176500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-117.81</td>\n",
              "      <td>33.78</td>\n",
              "      <td>27.0</td>\n",
              "      <td>3589.0</td>\n",
              "      <td>507.0</td>\n",
              "      <td>1484.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>5.7934</td>\n",
              "      <td>270500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-118.36</td>\n",
              "      <td>33.82</td>\n",
              "      <td>28.0</td>\n",
              "      <td>67.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>6.1359</td>\n",
              "      <td>330000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-119.67</td>\n",
              "      <td>36.33</td>\n",
              "      <td>19.0</td>\n",
              "      <td>1241.0</td>\n",
              "      <td>244.0</td>\n",
              "      <td>850.0</td>\n",
              "      <td>237.0</td>\n",
              "      <td>2.9375</td>\n",
              "      <td>81700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2995</th>\n",
              "      <td>-119.86</td>\n",
              "      <td>34.42</td>\n",
              "      <td>23.0</td>\n",
              "      <td>1450.0</td>\n",
              "      <td>642.0</td>\n",
              "      <td>1258.0</td>\n",
              "      <td>607.0</td>\n",
              "      <td>1.1790</td>\n",
              "      <td>225000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2996</th>\n",
              "      <td>-118.14</td>\n",
              "      <td>34.06</td>\n",
              "      <td>27.0</td>\n",
              "      <td>5257.0</td>\n",
              "      <td>1082.0</td>\n",
              "      <td>3496.0</td>\n",
              "      <td>1036.0</td>\n",
              "      <td>3.3906</td>\n",
              "      <td>237200.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2997</th>\n",
              "      <td>-119.70</td>\n",
              "      <td>36.30</td>\n",
              "      <td>10.0</td>\n",
              "      <td>956.0</td>\n",
              "      <td>201.0</td>\n",
              "      <td>693.0</td>\n",
              "      <td>220.0</td>\n",
              "      <td>2.2895</td>\n",
              "      <td>62000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2998</th>\n",
              "      <td>-117.12</td>\n",
              "      <td>34.10</td>\n",
              "      <td>40.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3.2708</td>\n",
              "      <td>162500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2999</th>\n",
              "      <td>-119.63</td>\n",
              "      <td>34.42</td>\n",
              "      <td>42.0</td>\n",
              "      <td>1765.0</td>\n",
              "      <td>263.0</td>\n",
              "      <td>753.0</td>\n",
              "      <td>260.0</td>\n",
              "      <td>8.5608</td>\n",
              "      <td>500001.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3000 rows × 9 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      longitude  latitude  ...  median_income  median_house_value\n",
              "0       -122.05     37.37  ...         6.6085            344700.0\n",
              "1       -118.30     34.26  ...         3.5990            176500.0\n",
              "2       -117.81     33.78  ...         5.7934            270500.0\n",
              "3       -118.36     33.82  ...         6.1359            330000.0\n",
              "4       -119.67     36.33  ...         2.9375             81700.0\n",
              "...         ...       ...  ...            ...                 ...\n",
              "2995    -119.86     34.42  ...         1.1790            225000.0\n",
              "2996    -118.14     34.06  ...         3.3906            237200.0\n",
              "2997    -119.70     36.30  ...         2.2895             62000.0\n",
              "2998    -117.12     34.10  ...         3.2708            162500.0\n",
              "2999    -119.63     34.42  ...         8.5608            500001.0\n",
              "\n",
              "[3000 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 160
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "id": "urKOadadjEh3",
        "outputId": "c2053dec-dfe6-44ff-fe63-c4b8843f15b8"
      },
      "source": [
        "p.head(3)\n",
        "#앞에서 3개만 보기"
      ],
      "execution_count": 161,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-122.05</td>\n",
              "      <td>37.37</td>\n",
              "      <td>27.0</td>\n",
              "      <td>3885.0</td>\n",
              "      <td>661.0</td>\n",
              "      <td>1537.0</td>\n",
              "      <td>606.0</td>\n",
              "      <td>6.6085</td>\n",
              "      <td>344700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-118.30</td>\n",
              "      <td>34.26</td>\n",
              "      <td>43.0</td>\n",
              "      <td>1510.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>809.0</td>\n",
              "      <td>277.0</td>\n",
              "      <td>3.5990</td>\n",
              "      <td>176500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-117.81</td>\n",
              "      <td>33.78</td>\n",
              "      <td>27.0</td>\n",
              "      <td>3589.0</td>\n",
              "      <td>507.0</td>\n",
              "      <td>1484.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>5.7934</td>\n",
              "      <td>270500.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   longitude  latitude  ...  median_income  median_house_value\n",
              "0    -122.05     37.37  ...         6.6085            344700.0\n",
              "1    -118.30     34.26  ...         3.5990            176500.0\n",
              "2    -117.81     33.78  ...         5.7934            270500.0\n",
              "\n",
              "[3 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 161
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "id": "M10MoGCrjdZ9",
        "outputId": "63918e18-2053-4c2c-f87a-6fc5c80b1f04"
      },
      "source": [
        "p.tail(3)\n",
        "#뒤에서 3개만 보기"
      ],
      "execution_count": 162,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2997</th>\n",
              "      <td>-119.70</td>\n",
              "      <td>36.30</td>\n",
              "      <td>10.0</td>\n",
              "      <td>956.0</td>\n",
              "      <td>201.0</td>\n",
              "      <td>693.0</td>\n",
              "      <td>220.0</td>\n",
              "      <td>2.2895</td>\n",
              "      <td>62000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2998</th>\n",
              "      <td>-117.12</td>\n",
              "      <td>34.10</td>\n",
              "      <td>40.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3.2708</td>\n",
              "      <td>162500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2999</th>\n",
              "      <td>-119.63</td>\n",
              "      <td>34.42</td>\n",
              "      <td>42.0</td>\n",
              "      <td>1765.0</td>\n",
              "      <td>263.0</td>\n",
              "      <td>753.0</td>\n",
              "      <td>260.0</td>\n",
              "      <td>8.5608</td>\n",
              "      <td>500001.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      longitude  latitude  ...  median_income  median_house_value\n",
              "2997    -119.70     36.30  ...         2.2895             62000.0\n",
              "2998    -117.12     34.10  ...         3.2708            162500.0\n",
              "2999    -119.63     34.42  ...         8.5608            500001.0\n",
              "\n",
              "[3 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 162
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qg7EPdtNjf-r"
      },
      "source": [
        "pd2 = pd.read_csv('/content/sample_data/se.csv',encoding='cp949')"
      ],
      "execution_count": 196,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 325
        },
        "id": "vc3Bv9oTmXD-",
        "outputId": "38ff99f6-911f-49a3-b277-a24fc1e193c8"
      },
      "source": [
        "pd2"
      ],
      "execution_count": 197,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>이순신</th>\n",
              "      <th>85</th>\n",
              "      <th>87</th>\n",
              "      <th>90</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>강감찬</td>\n",
              "      <td>75</td>\n",
              "      <td>80</td>\n",
              "      <td>95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>한석봉</td>\n",
              "      <td>99</td>\n",
              "      <td>98</td>\n",
              "      <td>99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>황진이</td>\n",
              "      <td>35</td>\n",
              "      <td>45</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>안중근</td>\n",
              "      <td>90</td>\n",
              "      <td>85</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>박문수</td>\n",
              "      <td>95</td>\n",
              "      <td>98</td>\n",
              "      <td>96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>임꺽정</td>\n",
              "      <td>15</td>\n",
              "      <td>35</td>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>김정호</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "      <td>80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>정몽주</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>오우석</td>\n",
              "      <td>50</td>\n",
              "      <td>45</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   이순신  85  87  90\n",
              "0  강감찬  75  80  95\n",
              "1  한석봉  99  98  99\n",
              "2  황진이  35  45  20\n",
              "3  안중근  90  85  90\n",
              "4  박문수  95  98  96\n",
              "5  임꺽정  15  35  45\n",
              "6  김정호  90  95  80\n",
              "7  정몽주  90  90  95\n",
              "8  오우석  50  45  60"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 197
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dl6s1NtHm8Rs"
      },
      "source": [
        "# 일단 구했다 치고"
      ],
      "execution_count": 179,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M4Z6BBHinCE1"
      },
      "source": [
        "p.shape\n",
        "\n",
        "type(p)\n",
        "\n",
        "p.ndim\n",
        "\n",
        "p,size\n",
        "\n",
        "p.info()\n",
        "\n",
        "p.describe()\n",
        "\n",
        "p.index\n",
        "\n",
        "p.columns\n",
        "\n",
        "p['총점'] = p['국어']+ p['영어'] + p['수학']\n",
        "\n",
        "p['평균'] = p['총점'] / 3\n",
        "\n",
        "p"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jUhjKmv9nBaq",
        "outputId": "9394c482-98f2-4713-b6d6-cc1e040d7348"
      },
      "source": [
        "pd2.shape"
      ],
      "execution_count": 188,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(9, 4)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 188
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D1ANOeSxqcp2"
      },
      "source": [
        "pd3 = pd.read_csv('/content/sample_data/sc.csv',encoding='cp949')"
      ],
      "execution_count": 211,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 325
        },
        "id": "08zLgbjWqxaO",
        "outputId": "20875a2d-31ac-49c6-8e95-2f8d6a245305"
      },
      "source": [
        "pd3"
      ],
      "execution_count": 212,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>이순신</th>\n",
              "      <th>85</th>\n",
              "      <th>87</th>\n",
              "      <th>90</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <td>강감찬</td>\n",
              "      <td>75</td>\n",
              "      <td>80</td>\n",
              "      <td>95</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>한석봉</td>\n",
              "      <td>99</td>\n",
              "      <td>98</td>\n",
              "      <td>99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>황진이</td>\n",
              "      <td>35</td>\n",
              "      <td>45</td>\n",
              "      <td>20</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>안중근</td>\n",
              "      <td>90</td>\n",
              "      <td>85</td>\n",
              "      <td>90</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>박문수</td>\n",
              "      <td>95</td>\n",
              "      <td>98</td>\n",
              "      <td>96</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>임꺽정</td>\n",
              "      <td>15</td>\n",
              "      <td>35</td>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>김정호</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "      <td>80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>정몽주</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>오우석</td>\n",
              "      <td>50</td>\n",
              "      <td>45</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   이순신  85  87  90\n",
              "0  강감찬  75  80  95\n",
              "1  한석봉  99  98  99\n",
              "2  황진이  35  45  20\n",
              "3  안중근  90  85  90\n",
              "4  박문수  95  98  96\n",
              "5  임꺽정  15  35  45\n",
              "6  김정호  90  95  80\n",
              "7  정몽주  90  90  95\n",
              "8  오우석  50  45  60"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 212
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wJKhG3YnuY1I"
      },
      "source": [
        "# 0행을 새로 추가하면서 파일을 불러온다.\n",
        "#이후에 칼럼을 넣어줌"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YwZIhH_frcvH"
      },
      "source": [
        "pd5 = pd.read_csv('/content/sample_data/sc.csv',encoding='cp949',header = None)"
      ],
      "execution_count": 222,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "2isiuBAvq1pN",
        "outputId": "dc66d9cb-702d-4525-c797-ddd487f8f3bc"
      },
      "source": [
        "pd5"
      ],
      "execution_count": 223,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <td>45</td>\n",
              "      <td>20</td>\n",
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              "    <tr>\n",
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              "      <td>15</td>\n",
              "      <td>35</td>\n",
              "      <td>45</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>김정호</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "      <td>80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>정몽주</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>오우석</td>\n",
              "      <td>50</td>\n",
              "      <td>45</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     0   1   2   3\n",
              "0  이순신  85  87  90\n",
              "1  강감찬  75  80  95\n",
              "2  한석봉  99  98  99\n",
              "3  황진이  35  45  20\n",
              "4  안중근  90  85  90\n",
              "5  박문수  95  98  96\n",
              "6  임꺽정  15  35  45\n",
              "7  김정호  90  95  80\n",
              "8  정몽주  90  90  95\n",
              "9  오우석  50  45  60"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 223
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ES7r7C_Mr9b7"
      },
      "source": [
        "pd5.columns=['이름','국어','영어','수학']"
      ],
      "execution_count": 224,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "xC-Et-IKunku",
        "outputId": "caac19e6-c79d-4e8a-aa3e-386f037ee986"
      },
      "source": [
        "pd5"
      ],
      "execution_count": 225,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <td>87</td>\n",
              "      <td>90</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
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              "      <th>2</th>\n",
              "      <td>한석봉</td>\n",
              "      <td>99</td>\n",
              "      <td>98</td>\n",
              "      <td>99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
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              "      <td>35</td>\n",
              "      <td>45</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>안중근</td>\n",
              "      <td>90</td>\n",
              "      <td>85</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>박문수</td>\n",
              "      <td>95</td>\n",
              "      <td>98</td>\n",
              "      <td>96</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>임꺽정</td>\n",
              "      <td>15</td>\n",
              "      <td>35</td>\n",
              "      <td>45</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>김정호</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "      <td>80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>정몽주</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>오우석</td>\n",
              "      <td>50</td>\n",
              "      <td>45</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    이름  국어  영어  수학\n",
              "0  이순신  85  87  90\n",
              "1  강감찬  75  80  95\n",
              "2  한석봉  99  98  99\n",
              "3  황진이  35  45  20\n",
              "4  안중근  90  85  90\n",
              "5  박문수  95  98  96\n",
              "6  임꺽정  15  35  45\n",
              "7  김정호  90  95  80\n",
              "8  정몽주  90  90  95\n",
              "9  오우석  50  45  60"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 225
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zPh6UouNuocJ",
        "outputId": "d7d94815-cb96-482a-deed-ab14272999e2"
      },
      "source": [
        "pd5.mean()"
      ],
      "execution_count": 226,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "국어    72.4\n",
              "영어    75.8\n",
              "수학    77.0\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 226
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "l-CKwDBjusph",
        "outputId": "133e5c3f-7cfb-458c-87d7-2979df23f17e"
      },
      "source": [
        "pd5.loc[:,['국어','영어','수학']] >= 70"
      ],
      "execution_count": 229,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    <tr style=\"text-align: right;\">\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      국어     영어     수학\n",
              "0   True   True   True\n",
              "1   True   True   True\n",
              "2   True   True   True\n",
              "3  False  False  False\n",
              "4   True   True   True\n",
              "5   True   True   True\n",
              "6  False  False  False\n",
              "7   True   True   True\n",
              "8   True   True   True\n",
              "9  False  False  False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 229
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "7AGzsb2au1V_",
        "outputId": "06ffd0ba-4cd9-46db-eb43-d731455dcf14"
      },
      "source": [
        "pd5.iloc[:,1:] >= 70"
      ],
      "execution_count": 230,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>국어</th>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      국어     영어     수학\n",
              "0   True   True   True\n",
              "1   True   True   True\n",
              "2   True   True   True\n",
              "3  False  False  False\n",
              "4   True   True   True\n",
              "5   True   True   True\n",
              "6  False  False  False\n",
              "7   True   True   True\n",
              "8   True   True   True\n",
              "9  False  False  False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 230
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YNSYbHLNu_ga",
        "outputId": "54c56175-3fdd-4571-f7b4-15d51474cc7d"
      },
      "source": [
        "pd5.sum(axis=1)"
      ],
      "execution_count": 231,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    262\n",
              "1    250\n",
              "2    296\n",
              "3    100\n",
              "4    265\n",
              "5    289\n",
              "6     95\n",
              "7    265\n",
              "8    275\n",
              "9    155\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 231
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mn848PM4vIbb",
        "outputId": "46740007-e333-4bc0-9fab-f6c43b5cd944"
      },
      "source": [
        "pd5['국어'].value_counts()\n",
        "#점수 분포도?"
      ],
      "execution_count": 233,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "90    3\n",
              "95    1\n",
              "75    1\n",
              "15    1\n",
              "85    1\n",
              "99    1\n",
              "50    1\n",
              "35    1\n",
              "Name: 국어, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 233
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cmBEYVSbvOdK",
        "outputId": "2493ed90-52df-4530-e091-12ad020eb444"
      },
      "source": [
        "pd5['국어'].value_counts(ascending=False)"
      ],
      "execution_count": 234,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "90    3\n",
              "95    1\n",
              "75    1\n",
              "15    1\n",
              "85    1\n",
              "99    1\n",
              "50    1\n",
              "35    1\n",
              "Name: 국어, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 234
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-U6w5h0pvap4",
        "outputId": "c58136aa-7617-4a9c-a024-e37fa0011fe5"
      },
      "source": [
        "pd5['국어'].sort_values()"
      ],
      "execution_count": 235,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6    15\n",
              "3    35\n",
              "9    50\n",
              "1    75\n",
              "0    85\n",
              "4    90\n",
              "7    90\n",
              "8    90\n",
              "5    95\n",
              "2    99\n",
              "Name: 국어, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 235
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g_8VfVrjvkEX",
        "outputId": "5373d4dc-1a2e-4435-ba62-981a786523e7"
      },
      "source": [
        "pd5['국어'].sort_values(ascending=False)"
      ],
      "execution_count": 236,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2    99\n",
              "5    95\n",
              "8    90\n",
              "7    90\n",
              "4    90\n",
              "0    85\n",
              "1    75\n",
              "9    50\n",
              "3    35\n",
              "6    15\n",
              "Name: 국어, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 236
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "-dHm6HiPvpGd",
        "outputId": "7086bfc5-6817-4808-9915-33d85b1a733c"
      },
      "source": [
        "pd5.sort_values(by='영어')\n",
        "#영어점수 기준으로 줄세우기"
      ],
      "execution_count": 237,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <td>60</td>\n",
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              "      <td>85</td>\n",
              "      <td>90</td>\n",
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              "    <tr>\n",
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              "      <td>87</td>\n",
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              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
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              "    <tr>\n",
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              "      <td>김정호</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "      <td>80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>한석봉</td>\n",
              "      <td>99</td>\n",
              "      <td>98</td>\n",
              "      <td>99</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>박문수</td>\n",
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              "      <td>98</td>\n",
              "      <td>96</td>\n",
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              "</div>"
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              "    이름  국어  영어  수학\n",
              "6  임꺽정  15  35  45\n",
              "3  황진이  35  45  20\n",
              "9  오우석  50  45  60\n",
              "1  강감찬  75  80  95\n",
              "4  안중근  90  85  90\n",
              "0  이순신  85  87  90\n",
              "8  정몽주  90  90  95\n",
              "7  김정호  90  95  80\n",
              "2  한석봉  99  98  99\n",
              "5  박문수  95  98  96"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 237
        }
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    {
      "cell_type": "code",
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          "base_uri": "https://localhost:8080/",
          "height": 355
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        "id": "Dxt4S5Lrv0ox",
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      },
      "source": [
        "pd5.sort_values(by=['영어','수학'])\n",
        "# 기준을 2가지\n",
        "# 영어가 동점일떄 수학이 높은 순서로"
      ],
      "execution_count": 238,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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            "text/plain": [
              "    이름  국어  영어  수학\n",
              "6  임꺽정  15  35  45\n",
              "3  황진이  35  45  20\n",
              "9  오우석  50  45  60\n",
              "1  강감찬  75  80  95\n",
              "4  안중근  90  85  90\n",
              "0  이순신  85  87  90\n",
              "8  정몽주  90  90  95\n",
              "7  김정호  90  95  80\n",
              "5  박문수  95  98  96\n",
              "2  한석봉  99  98  99"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 238
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uFpRMLNmwAzf"
      },
      "source": [
        "pd5.sort_values(by=['영어','수학'], inplace=True)"
      ],
      "execution_count": 250,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BM03VF43wQrM",
        "outputId": "02ce1314-d1cc-41f2-b00a-86c4d7818288"
      },
      "source": [
        "pd5['영어'] + 5\n",
        "#영어 점수만 5점 더줘야할때"
      ],
      "execution_count": 253,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6     40\n",
              "3     50\n",
              "9     50\n",
              "1     85\n",
              "4     90\n",
              "0     92\n",
              "8     95\n",
              "7    100\n",
              "5    103\n",
              "2    103\n",
              "Name: 영어, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 253
        }
      ]
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        "outputId": "190c583a-42c2-47ee-cc85-e8ab6fc90972"
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      "source": [
        "pd5"
      ],
      "execution_count": 254,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>80</td>\n",
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              "      <th>5</th>\n",
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              "      <td>98</td>\n",
              "      <td>96</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
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            "text/plain": [
              "    이름  국어  영어  수학\n",
              "6  임꺽정  15  35  45\n",
              "3  황진이  35  45  20\n",
              "9  오우석  50  45  60\n",
              "1  강감찬  75  80  95\n",
              "4  안중근  90  85  90\n",
              "0  이순신  85  87  90\n",
              "8  정몽주  90  90  95\n",
              "7  김정호  90  95  80\n",
              "5  박문수  95  98  96\n",
              "2  한석봉  99  98  99"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 254
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JoF33MYFxc3F"
      },
      "source": [
        "###평균으로 수우미 양가\n",
        "\n",
        "\n",
        "def get_grade(x):\n",
        "\n",
        "        grade = ''\n",
        "\n",
        "        if x >= 90: grade = '수'\n",
        "\n",
        "        elif x >= 80: grade = '우'\n",
        "\n",
        "        elif x >= 70: grade = '미'\n",
        "\n",
        "        elif x >= 70: grade = '양'\n",
        "\n",
        "        else: grade = '가'\n",
        "\n",
        "        return grade\n",
        "\n",
        "pd5['평가'] = pd5['평균'].apply(lambda x: get_grade(x))\n",
        "\n",
        "pd5"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7A48n5-W2qBb"
      },
      "source": [
        "#pandas column 추가하기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LwPAy0zBw6Ox"
      },
      "source": [
        "pd5['총점']=100\n",
        "# 우측에 총점 항목으로 기본값 100을 입력"
      ],
      "execution_count": 265,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "WEQ5GcEF1_RC",
        "outputId": "0f0218ad-ba9b-4e42-d692-c461bc7623aa"
      },
      "source": [
        "pd5"
      ],
      "execution_count": 266,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>이름</th>\n",
              "      <th>국어</th>\n",
              "      <th>영어</th>\n",
              "      <th>수학</th>\n",
              "      <th>평균</th>\n",
              "      <th>총점</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>임꺽정</td>\n",
              "      <td>15</td>\n",
              "      <td>35</td>\n",
              "      <td>45</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>황진이</td>\n",
              "      <td>35</td>\n",
              "      <td>45</td>\n",
              "      <td>20</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>오우석</td>\n",
              "      <td>50</td>\n",
              "      <td>45</td>\n",
              "      <td>60</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>강감찬</td>\n",
              "      <td>75</td>\n",
              "      <td>80</td>\n",
              "      <td>95</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>안중근</td>\n",
              "      <td>90</td>\n",
              "      <td>85</td>\n",
              "      <td>90</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>이순신</td>\n",
              "      <td>85</td>\n",
              "      <td>87</td>\n",
              "      <td>90</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>정몽주</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>김정호</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "      <td>80</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>박문수</td>\n",
              "      <td>95</td>\n",
              "      <td>98</td>\n",
              "      <td>96</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>한석봉</td>\n",
              "      <td>99</td>\n",
              "      <td>98</td>\n",
              "      <td>99</td>\n",
              "      <td>10</td>\n",
              "      <td>100</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    이름  국어  영어  수학  평균   총점\n",
              "6  임꺽정  15  35  45  10  100\n",
              "3  황진이  35  45  20  10  100\n",
              "9  오우석  50  45  60  10  100\n",
              "1  강감찬  75  80  95  10  100\n",
              "4  안중근  90  85  90  10  100\n",
              "0  이순신  85  87  90  10  100\n",
              "8  정몽주  90  90  95  10  100\n",
              "7  김정호  90  95  80  10  100\n",
              "5  박문수  95  98  96  10  100\n",
              "2  한석봉  99  98  99  10  100"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 266
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xtNazxWD2EMs"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}