02w_Pandas.ipynb

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      "name": "Pandas.ipynb",
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              "a    1\n",
              "b    2\n",
              "c    3\n",
              "d    4\n",
              "e    5\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "import pandas as pd \n",
        "import numpy as np\n",
        "from pandas import Series, DataFrame\n",
        "list_data = [1,2,3,4,5]\n",
        "list_name = [\"a\",\"b\",\"c\",\"d\",\"e\"]\n",
        "example_obj = Series(data = list_data, index=list_name)\n",
        "example_obj"
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        "example_obj.index"
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            "text/plain": [
              "Index(['a', 'b', 'c', 'd', 'e'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
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        "example_obj.values"
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        "outputId": "788ad412-2619-4602-edfa-96e3bf825b5b"
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          "data": {
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              "array([1, 2, 3, 4, 5])"
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          "execution_count": 4
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        "type(example_obj.values)"
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        "outputId": "adf711ee-8e29-40e8-f92e-f57c2d5f3c62"
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              "numpy.ndarray"
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        "example_obj.name = \"number\"\n",
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        "example_obj"
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        "dict_data = {\"a\":1, \"b\":2, \"c\":3, \"d\":4, \"e\":5}\n",
        "example_obj = Series(dict_data, dtype=np.float32, name=\"example_data\")\n",
        "example_obj"
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              "a    1.0\n",
              "b    2.0\n",
              "c    3.0\n",
              "d    4.0\n",
              "e    5.0\n",
              "Name: example_data, dtype: float32"
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          "execution_count": 9
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        "dict_data_1 = {\"a\":1, \"b\":2, \"c\":3, \"d\":4, \"e\":5}\n",
        "indexes = [\"a\",\"b\",\"c\",\"d\",\"e\",\"f\",\"g\",\"h\"]\n",
        "series_obj_1 = Series(dict_data_1, index=indexes)\n",
        "series_obj_1"
      ],
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      "execution_count": 10,
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              "a    1.0\n",
              "b    2.0\n",
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      "source": [
        "data_url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data'\n",
        "df_data = pd.read_csv(data_url, sep='\\\\s+', header = None) \n",
        "df = pd.DataFrame(df_data)\n",
        "df"
      ],
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              "          0     1      2   3      4      5     6       7   8      9     10  \\\n",
              "0    0.00632  18.0   2.31   0  0.538  6.575  65.2  4.0900   1  296.0  15.3   \n",
              "1    0.02731   0.0   7.07   0  0.469  6.421  78.9  4.9671   2  242.0  17.8   \n",
              "2    0.02729   0.0   7.07   0  0.469  7.185  61.1  4.9671   2  242.0  17.8   \n",
              "3    0.03237   0.0   2.18   0  0.458  6.998  45.8  6.0622   3  222.0  18.7   \n",
              "4    0.06905   0.0   2.18   0  0.458  7.147  54.2  6.0622   3  222.0  18.7   \n",
              "..       ...   ...    ...  ..    ...    ...   ...     ...  ..    ...   ...   \n",
              "501  0.06263   0.0  11.93   0  0.573  6.593  69.1  2.4786   1  273.0  21.0   \n",
              "502  0.04527   0.0  11.93   0  0.573  6.120  76.7  2.2875   1  273.0  21.0   \n",
              "503  0.06076   0.0  11.93   0  0.573  6.976  91.0  2.1675   1  273.0  21.0   \n",
              "504  0.10959   0.0  11.93   0  0.573  6.794  89.3  2.3889   1  273.0  21.0   \n",
              "505  0.04741   0.0  11.93   0  0.573  6.030  80.8  2.5050   1  273.0  21.0   \n",
              "\n",
              "         11    12    13  \n",
              "0    396.90  4.98  24.0  \n",
              "1    396.90  9.14  21.6  \n",
              "2    392.83  4.03  34.7  \n",
              "3    394.63  2.94  33.4  \n",
              "4    396.90  5.33  36.2  \n",
              "..      ...   ...   ...  \n",
              "501  391.99  9.67  22.4  \n",
              "502  396.90  9.08  20.6  \n",
              "503  396.90  5.64  23.9  \n",
              "504  393.45  6.48  22.0  \n",
              "505  396.90  7.88  11.9  \n",
              "\n",
              "[506 rows x 14 columns]"
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pandas import Series, DataFrame\n",
        "raw_data = {'first_name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],\n",
        "'last_name': ['Miller', 'Jacobson', 'Ali', 'Milner', 'Cooze'],\n",
        "'age': [42, 52, 36, 24, 73],\n",
        "'city': ['San Francisco', 'Baltimore', 'Miami', 'Douglas', 'Boston']}\n",
        "df = pd.DataFrame(raw_data, columns = ['first_name', 'last_name', 'age', 'city'])\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 213
        },
        "id": "XkZjTFhlFeUh",
        "outputId": "e35d0466-7ed1-42f6-81d7-b435e4557695"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  first_name last_name  age           city\n",
              "0      Jason    Miller   42  San Francisco\n",
              "1      Molly  Jacobson   52      Baltimore\n",
              "2       Tina       Ali   36          Miami\n",
              "3       Jake    Milner   24        Douglas\n",
              "4        Amy     Cooze   73         Boston"
            ],
            "text/html": [
              "\n",
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              "      <div>\n",
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              "\n",
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              "        text-align: right;\n",
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              "  <thead>\n",
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              "      <td>Ali</td>\n",
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              "      <th>3</th>\n",
              "      <td>Jake</td>\n",
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              "      <td>24</td>\n",
              "      <td>Douglas</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Amy</td>\n",
              "      <td>Cooze</td>\n",
              "      <td>73</td>\n",
              "      <td>Boston</td>\n",
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              "\n",
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              "          const element = document.querySelector('#df-1a780df2-240d-41ed-a9b7-71a2467d75ed');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "DataFrame(raw_data, columns = [\"age\", \"city\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "ZncRx_J0F9wx",
        "outputId": "f426363e-2d8f-43cc-fc9d-36afb04d3e2c"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   age           city\n",
              "0   42  San Francisco\n",
              "1   52      Baltimore\n",
              "2   36          Miami\n",
              "3   24        Douglas\n",
              "4   73         Boston"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-23610fbe-5a2b-4877-93a1-65bccab61037\">\n",
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              "      <td>Boston</td>\n",
              "    </tr>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-23610fbe-5a2b-4877-93a1-65bccab61037')\"\n",
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              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
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    {
      "cell_type": "code",
      "source": [
        "DataFrame(raw_data, columns = [\"first_name\",\"last_name\",\"age\", \"city\", \"debt\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "QJkYaBVkGDE9",
        "outputId": "25785f00-660b-4382-81ea-49e23235d096"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  first_name last_name  age           city debt\n",
              "0      Jason    Miller   42  San Francisco  NaN\n",
              "1      Molly  Jacobson   52      Baltimore  NaN\n",
              "2       Tina       Ali   36          Miami  NaN\n",
              "3       Jake    Milner   24        Douglas  NaN\n",
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              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-36f72971-b844-4d41-9673-c3eb111bdcb3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-36f72971-b844-4d41-9673-c3eb111bdcb3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    }
  ]
}