diff --git a/exercicios/para-casa/Rayla_Santos.ipynb b/exercicios/para-casa/Rayla_Santos.ipynb
new file mode 100644
index 0000000..ddc5099
--- /dev/null
+++ b/exercicios/para-casa/Rayla_Santos.ipynb
@@ -0,0 +1,830 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "WbfCMj_D0WqN"
+      },
+      "outputs": [],
+      "source": [
+        "import pandas as pd"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df = pd.read_csv('/content/vendas_ficticias.csv')\n",
+        "df"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 361
+        },
+        "id": "CFXR0gRi_mLM",
+        "outputId": "e860876e-a419-4391-abf7-6d0a829c4b42"
+      },
+      "execution_count": 14,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "   Data da venda  Valor da venda Vendedor  Quantidade vendida    Produto\n",
+              "0     2024-01-29          212.80    Pedro                   8  Produto D\n",
+              "1     2024-05-19          428.04     João                  16  Produto E\n",
+              "2     2024-02-19          982.79      Ana                  20  Produto A\n",
+              "3     2024-02-15          127.86    Pedro                   1  Produto B\n",
+              "4     2024-01-13          429.88    Maria                   6  Produto E\n",
+              "..           ...             ...      ...                 ...        ...\n",
+              "95    2024-03-13           78.17     João                  18  Produto A\n",
+              "96    2024-04-19          865.72    Maria                  14  Produto D\n",
+              "97    2024-01-19          117.36   Carlos                  12  Produto E\n",
+              "98    2024-01-13          934.73    Pedro                   4  Produto E\n",
+              "99    2024-03-26          349.69      Ana                  11  Produto E\n",
+              "\n",
+              "[100 rows x 5 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-cbe424c3-a7ce-4838-bde5-fc380ed1f551\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
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+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Data da venda</th>\n",
+              "      <th>Valor da venda</th>\n",
+              "      <th>Vendedor</th>\n",
+              "      <th>Quantidade vendida</th>\n",
+              "      <th>Produto</th>\n",
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+              "      <td>2024-01-29</td>\n",
+              "      <td>212.80</td>\n",
+              "      <td>Pedro</td>\n",
+              "      <td>8</td>\n",
+              "      <td>Produto D</td>\n",
+              "    </tr>\n",
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+              "      <th>1</th>\n",
+              "      <td>2024-05-19</td>\n",
+              "      <td>428.04</td>\n",
+              "      <td>João</td>\n",
+              "      <td>16</td>\n",
+              "      <td>Produto E</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>2024-02-19</td>\n",
+              "      <td>982.79</td>\n",
+              "      <td>Ana</td>\n",
+              "      <td>20</td>\n",
+              "      <td>Produto A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>2024-02-15</td>\n",
+              "      <td>127.86</td>\n",
+              "      <td>Pedro</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Produto B</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>2024-01-13</td>\n",
+              "      <td>429.88</td>\n",
+              "      <td>Maria</td>\n",
+              "      <td>6</td>\n",
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+              "      <td>78.17</td>\n",
+              "      <td>João</td>\n",
+              "      <td>18</td>\n",
+              "      <td>Produto A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>96</th>\n",
+              "      <td>2024-04-19</td>\n",
+              "      <td>865.72</td>\n",
+              "      <td>Maria</td>\n",
+              "      <td>14</td>\n",
+              "      <td>Produto D</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>97</th>\n",
+              "      <td>2024-01-19</td>\n",
+              "      <td>117.36</td>\n",
+              "      <td>Carlos</td>\n",
+              "      <td>12</td>\n",
+              "      <td>Produto E</td>\n",
+              "    </tr>\n",
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+              "      <th>98</th>\n",
+              "      <td>2024-01-13</td>\n",
+              "      <td>934.73</td>\n",
+              "      <td>Pedro</td>\n",
+              "      <td>4</td>\n",
+              "      <td>Produto E</td>\n",
+              "    </tr>\n",
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+              "      <th>99</th>\n",
+              "      <td>2024-03-26</td>\n",
+              "      <td>349.69</td>\n",
+              "      <td>Ana</td>\n",
+              "      <td>11</td>\n",
+              "      <td>Produto E</td>\n",
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+              "          '<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",
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+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 100,\n  \"fields\": [\n    {\n      \"column\": \"Data da venda\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 70,\n        \"samples\": [\n          \"2024-03-13\",\n          \"2024-01-29\",\n          \"2024-04-14\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Valor da venda\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 281.06073685041633,\n        \"min\": 55.02,\n        \"max\": 987.42,\n        \"num_unique_values\": 100,\n        \"samples\": [\n          861.73,\n          562.53,\n          455.02\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Vendedor\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Jo\\u00e3o\",\n          \"Carlos\",\n          \"Ana\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Quantidade vendida\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5,\n        \"min\": 1,\n        \"max\": 20,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          8,\n          11,\n          15\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Produto\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Produto E\",\n          \"Produto C\",\n          \"Produto A\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 14
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Cálculo Média"
+      ],
+      "metadata": {
+        "id": "fkg-sd6tD8HN"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "media_venda = df['Valor da venda'].mean()\n",
+        "media_venda"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Co00HsN8IBLv",
+        "outputId": "1ec9a9dc-b621-4676-dd63-cafb751e30f5"
+      },
+      "execution_count": 53,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "553.2947"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 53
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "media_qtd = df['Quantidade vendida'].mean()\n",
+        "media_qtd"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "c3SvIX95JTf_",
+        "outputId": "28c20fd2-a119-4774-8818-c44ad71054a9"
+      },
+      "execution_count": 54,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "9.9"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 54
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Cálculo Mediana"
+      ],
+      "metadata": {
+        "id": "JIzbNsB-JdQA"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "venda_mediana = df['Valor da venda'].median()\n",
+        "venda_mediana"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Dpe_xiLwJqpt",
+        "outputId": "c4c0bea1-c15a-4595-ebbf-3f83721d8ca0"
+      },
+      "execution_count": 55,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "569.535"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 55
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "qtd_vendida_mediana = df['Quantidade vendida'].median()\n",
+        "qtd_vendida_mediana"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "_R04V3MpJ7M1",
+        "outputId": "5d988cc5-837a-4301-e9df-341532203c9a"
+      },
+      "execution_count": 56,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "10.0"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 56
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Cálculo Mínimo"
+      ],
+      "metadata": {
+        "id": "fI4NrCejKKSz"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "menor_venda = df['Valor da venda'].min()\n",
+        "menor_venda"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "YBiTPYwXKQKC",
+        "outputId": "3d2fe5d7-bfa4-4e08-8a5b-3e190effe244"
+      },
+      "execution_count": 49,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "55.02"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 49
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "menor_qtd = df['Quantidade vendida'].min()\n",
+        "menor_qtd"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "NS_VZI1tKsTu",
+        "outputId": "036ce102-4255-4ca9-d153-87b463540d86"
+      },
+      "execution_count": 50,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "1"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 50
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Cálculo Máximo"
+      ],
+      "metadata": {
+        "id": "ypDpX27jKxf7"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "maior_venda = df['Valor da venda'].max()\n",
+        "maior_venda"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "LVYbO4s3K18O",
+        "outputId": "dfb456c2-d3a4-42a0-9dc6-03faa240b727"
+      },
+      "execution_count": 52,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "987.42"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 52
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "maior_qtd = df['Quantidade vendida'].max()\n",
+        "maior_qtd"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "HpgH5_RiK6df",
+        "outputId": "2fa5dfa8-72ec-48c5-914e-101ec4b629aa"
+      },
+      "execution_count": 51,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "20"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 51
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Desvio de Padrão"
+      ],
+      "metadata": {
+        "id": "mnKKX3BhLDan"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "desviopd = df['Valor da venda'].var() ** 0.5\n",
+        "desviopd"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-G1gFWQoPcwu",
+        "outputId": "bdda85d1-2584-4d41-b509-166f84d842d9"
+      },
+      "execution_count": 41,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "281.06073685041633"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 41
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "desviopd = df['Quantidade vendida'].var() ** 0.5\n",
+        "desviopd"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "_NUODkKpPocN",
+        "outputId": "1d427487-9db6-41f2-a315-36ec49277b7d"
+      },
+      "execution_count": 42,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "5.880115438982264"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 42
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Produto mais vendido"
+      ],
+      "metadata": {
+        "id": "3aY9wErkQZKY"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "pd_mais_vendido = df['Produto'].mode()\n",
+        "pd_mais_vendido"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 115
+        },
+        "id": "cfcUTsk3Qa9J",
+        "outputId": "12834de5-87ad-4811-b7de-e81c61aaddd0"
+      },
+      "execution_count": 46,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0    Produto D\n",
+              "Name: Produto, dtype: object"
+            ],
+            "text/html": [
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Produto</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>Produto D</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table><br><label><b>dtype:</b> object</label>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 46
+        }
+      ]
+    }
+  ]
+}
\ No newline at end of file