aula02_minicurso_ds_exercises.ipynb

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    {
      "cell_type": "markdown",
      "source": [
        "# Exercícios da Aula 02"
      ],
      "metadata": {
        "id": "SmOG_U0kiGLj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import io\n",
        "import numpy as np\n",
        "\n",
        "from google.colab import files"
      ],
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        "id": "inpKoCjL_9zG"
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      "execution_count": 1,
      "outputs": []
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        "arq = files.upload()"
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              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
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        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving AB_NYC_2019.csv to AB_NYC_2019.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(io.BytesIO(arq['AB_NYC_2019.csv']))"
      ],
      "metadata": {
        "id": "EGYJjxMQ_9VP"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **1. Qual o número total de linhas do conjunto de dados?**"
      ],
      "metadata": {
        "id": "IY9P67Z3iMlU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "len(df.index)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KvK92KiIA24P",
        "outputId": "9cde6b65-6a9b-4c91-8dff-bd88978d3300"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "48895"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **2. Calcule o valor máximo das Quantidade de Anúncios do Host do Imóvel**"
      ],
      "metadata": {
        "id": "PsCGm9e9iMja"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "host_listings = df.loc[:, 'calculated_host_listings_count']\n",
        "\n",
        "np.max(host_listings)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lS9wS_UxB-o4",
        "outputId": "36432370-9b6c-40f4-a773-738606c9807e"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "327"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **3. Quais os tipos de dados de cada coluna?**"
      ],
      "metadata": {
        "id": "0TVbIh3KiMhS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vFg4tI7uFeYG",
        "outputId": "ee8687da-48fd-4d81-e266-1e60a4d979ec"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                                  int64\n",
              "name                               object\n",
              "host_id                             int64\n",
              "host_name                          object\n",
              "neighbourhood_group                object\n",
              "neighbourhood                      object\n",
              "latitude                          float64\n",
              "longitude                         float64\n",
              "room_type                          object\n",
              "price                               int64\n",
              "minimum_nights                      int64\n",
              "number_of_reviews                   int64\n",
              "last_review                        object\n",
              "reviews_per_month                 float64\n",
              "calculated_host_listings_count      int64\n",
              "availability_365                    int64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **4. Qual o número de dados faltantes do conjunto de dados?**"
      ],
      "metadata": {
        "id": "hH4wuH1JiMKw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xzj-mYIqFh_Y",
        "outputId": "fe407ac2-115f-4485-e3b7-4e26c8495b16"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                                    0\n",
              "name                                 16\n",
              "host_id                               0\n",
              "host_name                            21\n",
              "neighbourhood_group                   0\n",
              "neighbourhood                         0\n",
              "latitude                              0\n",
              "longitude                             0\n",
              "room_type                             0\n",
              "price                                 0\n",
              "minimum_nights                        0\n",
              "number_of_reviews                     0\n",
              "last_review                       10052\n",
              "reviews_per_month                 10052\n",
              "calculated_host_listings_count        0\n",
              "availability_365                      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **5. Seleciona as seguintes colunas:**\n",
        " - Identificador do registro na base de dados\n",
        " - Nome do Anúncio na plataforma do Airbnb\n",
        " - Ponto Geográfico de Latitude\n",
        " - Ponto Geográfico de Longitude\n",
        " - Tipo de Locação (Quarto, Casa inteira, etc)\n",
        " - Preço do aluguel (diária)\n",
        " - Quantidade de Revisões Mensais"
      ],
      "metadata": {
        "id": "26kvLu79iMJD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cols = ['id', 'name', 'latitude', 'longitude', 'room_type', 'price', 'reviews_per_month']\n",
        "cols_select = df.loc[:, cols]\n",
        "cols_select.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "UO8465PvFpq6",
        "outputId": "a5c3b731-150f-4cbd-f226-3108af9e6e0c"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     id                                              name  latitude  \\\n",
              "0  2539                Clean & quiet apt home by the park  40.64749   \n",
              "1  2595                             Skylit Midtown Castle  40.75362   \n",
              "2  3647               THE VILLAGE OF HARLEM....NEW YORK !  40.80902   \n",
              "3  3831                   Cozy Entire Floor of Brownstone  40.68514   \n",
              "4  5022  Entire Apt: Spacious Studio/Loft by central park  40.79851   \n",
              "\n",
              "   longitude        room_type  price  reviews_per_month  \n",
              "0  -73.97237     Private room    149               0.21  \n",
              "1  -73.98377  Entire home/apt    225               0.38  \n",
              "2  -73.94190     Private room    150                NaN  \n",
              "3  -73.95976  Entire home/apt     89               4.64  \n",
              "4  -73.94399  Entire home/apt     80               0.10  "
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      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-e0e22203-ccca-43a5-8257-48ac30d937ca 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-e0e22203-ccca-43a5-8257-48ac30d937ca');\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": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **6. Calcule o valor médio das Diárias Mínimas para Locação**"
      ],
      "metadata": {
        "id": "gzwwhauAiMG5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cols = ['minimum_nights']\n",
        "\n",
        "minimum_nights = df.loc[:, cols]\n",
        "\n",
        "np.mean(minimum_nights)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ibmdS1DqH8nD",
        "outputId": "3626127f-cbfa-4f6c-ec34-384f516730e7"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "minimum_nights    7.029962\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **7. Calcule o valor mediano das Diárias Mínimas para Locação**"
      ],
      "metadata": {
        "id": "jI2wCMp3iMEr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cols = ['minimum_nights']\n",
        "\n",
        "minimum_nights_median = df.loc[:, cols]\n",
        "\n",
        "np.median(minimum_nights_median)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "an6j6B4RJWe-",
        "outputId": "03f16fdc-fd23-4740-e6df-6f38dee24175"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3.0"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **8. Quais os nomes das colunas?**"
      ],
      "metadata": {
        "id": "EYZg2cWQiMCa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6KAXIhm2JhrG",
        "outputId": "850b63a8-a3a9-4b0c-ac79-332a81de66da"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['id', 'name', 'host_id', 'host_name', 'neighbourhood_group',\n",
              "       'neighbourhood', 'latitude', 'longitude', 'room_type', 'price',\n",
              "       'minimum_nights', 'number_of_reviews', 'last_review',\n",
              "       'reviews_per_month', 'calculated_host_listings_count',\n",
              "       'availability_365'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **9. Calcule o valor mínimo das Quantidade de Anúncios do Host do Imóvel**"
      ],
      "metadata": {
        "id": "xmHzDC8diL_5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "host_listings_min = df.loc[:, 'calculated_host_listings_count']\n",
        "\n",
        "np.min(host_listings_min)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bYEjIakxJ1n7",
        "outputId": "089319fc-bd2d-40f2-bda3-3e230b249698"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **10. Qual o número total de colunas do conjunto de dados?**"
      ],
      "metadata": {
        "id": "xKX0ZdfGiL8B"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "len(df.columns)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "syRjK0l9KD9K",
        "outputId": "23f954a0-d180-432b-cd36-fb7ec8f9cf80"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **11. Calcule o valor médio das Quantidade de Anúncios do Host do Imóvel**"
      ],
      "metadata": {
        "id": "tlFigDogiL57"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cols = ['calculated_host_listings_count']\n",
        "\n",
        "host_listings_mean = df.loc[:, cols]\n",
        "\n",
        "np.mean(host_listings_mean)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vSALu6MDKU7x",
        "outputId": "bef5ade5-51a3-4f55-91b0-728ae7beba2a"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "calculated_host_listings_count    7.143982\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **12. Calcule o valor mediano das Quantidade de Anúncios do Host do Imóvel**"
      ],
      "metadata": {
        "id": "fTdTp5kOichY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cols = ['calculated_host_listings_count']\n",
        "\n",
        "host_listings_median = df.loc[:, cols]\n",
        "\n",
        "np.median(host_listings_median)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MhCeEhysKVOp",
        "outputId": "22045fc7-d23a-47c5-f4ba-679b8d878e05"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.0"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **13. Calcule o valor mínimo das Quantidade de Avaliações**"
      ],
      "metadata": {
        "id": "Kdb84vnPicfp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cols = ['calculated_host_listings_count']\n",
        "\n",
        "host_listings_min = df.loc[:, cols]\n",
        "\n",
        "np.min(host_listings_min)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fmrybANDKV55",
        "outputId": "c6707200-f9b2-4fc8-bb46-c189736fbe3e"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "calculated_host_listings_count    1\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    }
  ]
}