diff --git a/exercicios/para-casa/casa.ipynb b/exercicios/para-casa/casa.ipynb
new file mode 100644
index 0000000..a55165f
--- /dev/null
+++ b/exercicios/para-casa/casa.ipynb
@@ -0,0 +1,421 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Parte 1: Preparação do Ambiente"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as pltim"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Configurando a seed para reprodutibilidade\n",
+    "np.random.seed(42)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Conjunto de dados gerado e salvo como 'dados_vendas.csv'.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Gerando dados falsos\n",
+    "num_registros = 100 \n",
+    "datas = pd.date_range(start='2023-01-01', end='2023-12-31', freq='D')\n",
+    "categorias = ['Eletrônicos', 'Roupas', 'Alimentos', 'Brinquedos']\n",
+    "# Criando DataFrame\n",
+    "data = {\n",
+    "    'Data': np.random.choice(datas, num_registros),\n",
+    "    'Categoria': np.random.choice(categorias, num_registros),\n",
+    "    'Quantidade_Vendida': np.random.randint(1, 100, num_registros),\n",
+    "    'Preco_Unitario': np.round(np.random.uniform(10, 500, num_registros), 2)\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "df['Valor_Total'] = df['Quantidade_Vendida'] * df['Preco_Unitario']\n",
+    "\n",
+    "# Salvando o DataFrame em um arquivo CSV\n",
+    "df.to_csv('dados_vendas.csv', index=False)\n",
+    "\n",
+    "print(\"Conjunto de dados gerado e salvo como 'dados_vendas.csv'.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Parte 2: Consulta e Filtragem de Dados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Carregando os dados do csv criado anteriormente.\n",
+    "df = pd.read_csv('dados_vendas.csv')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "O DataFrame possui 100 linhas e 5 colunas.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Aqui utilizei a função shape para descobrir o número de linhas e colunas\n",
+    "linhas, colunas = df.shape\n",
+    "print(f\"O DataFrame possui {linhas} linhas e {colunas} colunas.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data                   object\n",
+      "Categoria              object\n",
+      "Quantidade_Vendida      int64\n",
+      "Preco_Unitario        float64\n",
+      "Valor_Total           float64\n",
+      "dtype: object\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Listei os tipos de dados das colunas\n",
+    "print(df.dtypes)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "         Data   Categoria  Quantidade_Vendida  Preco_Unitario  Valor_Total\n",
+      "0  2023-04-13  Brinquedos                  92          491.26     45195.92\n",
+      "1  2023-12-15  Brinquedos                  89          263.15     23420.35\n",
+      "2  2023-09-28  Brinquedos                  62          137.81      8544.22\n",
+      "3  2023-04-17   Alimentos                  97          498.16     48321.52\n",
+      "4  2023-03-13   Alimentos                   1          483.06       483.06\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Exibi as primeiras 5 linhas do DataFrame\n",
+    "print(df.head())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Existem 4 categorias únicas: ['Brinquedos' 'Alimentos' 'Eletrônicos' 'Roupas'].\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Utilizei esse comando para imprimir  o número de categorias únicas e listar as categorias.\n",
+    "categorias_unicas = df['Categoria'].unique()\n",
+    "print(f\"Existem {len(categorias_unicas)} categorias únicas: {categorias_unicas}.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Esse comando seleciona apenas as linhas onde a coluna 'Categoria' é igual a 'Eletrônicos'\n",
+    "eletronicos = df[df['Categoria'] == 'Eletrônicos']\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "A média do valor total das vendas na categoria 'Eletrônicos' é de R$ 10544.60.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Aqui foi calculada a média do valor total das vendas na categoria 'Eletrônicos'\n",
+    "media_venda_total_eletronicos = eletronicos['Valor_Total'].mean()\n",
+    "print(f\"A média do valor total das vendas na categoria 'Eletrônicos' é de R$ {media_venda_total_eletronicos:.2f}.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "          Data   Categoria  Quantidade_Vendida  Preco_Unitario  Valor_Total\n",
+      "0   2023-04-13  Brinquedos                  92          491.26     45195.92\n",
+      "1   2023-12-15  Brinquedos                  89          263.15     23420.35\n",
+      "2   2023-09-28  Brinquedos                  62          137.81      8544.22\n",
+      "3   2023-04-17   Alimentos                  97          498.16     48321.52\n",
+      "5   2023-07-08   Alimentos                  27          283.56      7656.12\n",
+      "..         ...         ...                 ...             ...          ...\n",
+      "94  2023-03-06      Roupas                  94          444.44     41777.36\n",
+      "96  2023-11-23   Alimentos                  99          293.64     29070.36\n",
+      "97  2023-01-09  Brinquedos                   7          224.85      1573.95\n",
+      "98  2023-12-10      Roupas                  16          339.29      5428.64\n",
+      "99  2023-05-09   Alimentos                  90          170.79     15371.10\n",
+      "\n",
+      "[87 rows x 5 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Esse comando seleciona apenas as linhas onde o valor na coluna 'Valor_Total' é maior que R$ 1000. \n",
+    "vendas_acima_1000 = df[df['Valor_Total'] > 1000]\n",
+    "print(vendas_acima_1000)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Ocorreram 87 vendas acima de R$ 1000.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Verificar as linhas onde o valor na coluna 'Valor_Total' é maior que R$ 1000\n",
+    "qtd_vendas_acima_1000 = len(vendas_acima_1000)\n",
+    "print(f\"Ocorreram {qtd_vendas_acima_1000} vendas acima de R$ 1000.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Parte 3: Agrupamento e Agregação"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     Categoria  Valor_Total\n",
+      "0    Alimentos    530548.52\n",
+      "1   Brinquedos    296852.89\n",
+      "2  Eletrônicos    231981.13\n",
+      "3       Roupas    348665.18\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Aqui foram agrupados os dados por categoria e somados os valores totais de vendas\n",
+    "total_categoria = df.groupby('Categoria')['Valor_Total'].sum().reset_index()\n",
+    "print(total_categoria)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "A categoria com o maior valor total de vendas é 'Alimentos' com R$ 530548.52.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Fiz a ategoria para calular com maior valor total de vendas\n",
+    "categoria_max_vendas = total_categoria.loc[total_categoria['Valor_Total'].idxmax()]\n",
+    "print(f\"A categoria com o maior valor total de vendas é '{categoria_max_vendas['Categoria']}' com R$ {categoria_max_vendas['Valor_Total']:.2f}.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     Categoria  Quantidade_Vendida\n",
+      "0    Alimentos           53.117647\n",
+      "1   Brinquedos           50.760000\n",
+      "2  Eletrônicos           40.818182\n",
+      "3       Roupas           65.052632\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Agrupei os dados por categoria e calcula a média da coluna.\n",
+    "media_qtdade_categoria = df.groupby('Categoria')['Quantidade_Vendida'].mean().reset_index()\n",
+    "print(media_qtdade_categoria)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Parte 4: Visualização de Dados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Criaação de um  gráfico de barras para o total de vendas por categoria\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "plt.bar(total_categoria['Categoria'], total_categoria['Valor_Total'], color='skyblue')\n",
+    "plt.xlabel('Categoria')\n",
+    "plt.ylabel('Valor Total de Vendas (R$)')\n",
+    "plt.title('Total de Vendas por Categoria')\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Com base no gráfico, qual categoria visualmente se destaca em termos de vendas totais? Alimentos."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Aqui foi verificada  as vendas de 'Eletrônicos' por data e somando os valores totais\n",
+    "vendas_diarias = eletronicos.groupby('Data')['Valor_Total'].sum().reset_index()\n",
+    "\n",
+    "# Criação de  um gráfico de linha para a variação diária das vendas de 'Eletrônicos'\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "plt.plot(vendas_diarias['Data'], vendas_diarias['Valor_Total'], color='purple')\n",
+    "plt.xlabel('Data')\n",
+    "plt.ylabel('Valor Total de Vendas (R$)')\n",
+    "plt.title('Variação Diária das Vendas de Eletrônicos')\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Existe algum padrão ou tendência observável nas vendas diárias de eletrônicos?"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/exercicios/para-casa/dados_vendas.csv b/exercicios/para-casa/dados_vendas.csv
new file mode 100644
index 0000000..4ccbf10
--- /dev/null
+++ b/exercicios/para-casa/dados_vendas.csv
@@ -0,0 +1,101 @@
+Data,Categoria,Quantidade_Vendida,Preco_Unitario,Valor_Total
+2023-04-13,Brinquedos,92,491.26,45195.92
+2023-12-15,Brinquedos,89,263.15,23420.35
+2023-09-28,Brinquedos,62,137.81,8544.22
+2023-04-17,Alimentos,97,498.16,48321.520000000004
+2023-03-13,Alimentos,1,483.06,483.06
+2023-07-08,Alimentos,27,283.56,7656.12
+2023-01-21,Eletrônicos,62,442.49,27434.38
+2023-04-13,Brinquedos,77,102.47,7890.19
+2023-05-02,Alimentos,3,146.65,439.95000000000005
+2023-08-03,Alimentos,70,353.18,24722.600000000002
+2023-11-27,Eletrônicos,72,424.86,30589.920000000002
+2023-03-29,Alimentos,27,429.6,11599.2
+2023-04-10,Eletrônicos,9,208.21,1873.89
+2023-12-26,Roupas,62,445.01,27590.62
+2023-06-01,Alimentos,37,426.95,15797.15
+2023-05-11,Roupas,97,468.46,45440.619999999995
+2023-05-30,Eletrônicos,51,394.82,20135.82
+2023-11-05,Brinquedos,44,337.8,14863.2
+2023-09-15,Alimentos,24,294.54,7068.960000000001
+2023-12-10,Eletrônicos,79,192.42,15201.179999999998
+2023-10-21,Brinquedos,59,470.67,27769.530000000002
+2023-07-11,Brinquedos,32,487.1,15587.2
+2023-10-04,Roupas,96,149.12,14315.52
+2023-06-10,Eletrônicos,88,159.63,14047.439999999999
+2023-11-10,Brinquedos,52,247.95,12893.4
+2023-01-22,Alimentos,62,229.73,14243.26
+2023-09-10,Alimentos,58,497.28,28842.239999999998
+2023-08-24,Roupas,52,96.2,5002.400000000001
+2023-12-11,Brinquedos,12,18.86,226.32
+2023-02-18,Eletrônicos,39,252.01,9828.39
+2023-02-28,Alimentos,2,97.62,195.24
+2023-06-19,Brinquedos,3,189.57,568.71
+2023-07-07,Brinquedos,56,374.64,20979.84
+2023-09-28,Roupas,81,363.26,29424.059999999998
+2023-07-09,Alimentos,59,160.95,9496.05
+2023-06-24,Alimentos,2,275.84,551.68
+2023-02-20,Eletrônicos,2,259.32,518.64
+2023-12-30,Alimentos,92,321.8,29605.600000000002
+2023-02-24,Eletrônicos,54,132.73,7167.419999999999
+2023-09-01,Alimentos,87,299.04,26016.480000000003
+2023-11-16,Roupas,96,489.66,47007.36
+2023-05-11,Alimentos,97,248.5,24104.5
+2023-11-03,Eletrônicos,1,453.99,453.99
+2023-05-15,Eletrônicos,19,222.85,4234.15
+2023-01-21,Roupas,2,181.54,363.08
+2023-11-25,Alimentos,53,326.1,17283.300000000003
+2023-06-16,Alimentos,44,337.77,14861.88
+2023-10-01,Roupas,90,433.44,39009.6
+2023-03-30,Alimentos,32,122.79,3929.28
+2023-11-12,Alimentos,70,254.6,17822.0
+2023-01-14,Eletrônicos,32,290.28,9288.96
+2023-08-30,Alimentos,68,386.59,26288.12
+2023-09-22,Alimentos,55,31.37,1725.3500000000001
+2023-12-12,Roupas,75,497.33,37299.75
+2023-02-22,Roupas,56,240.27,13455.12
+2023-12-06,Brinquedos,17,146.98,2498.66
+2023-04-02,Eletrônicos,38,442.91,16830.58
+2023-09-21,Alimentos,24,376.38,9033.119999999999
+2023-02-04,Alimentos,69,477.01,32913.69
+2023-07-25,Brinquedos,98,172.07,16862.86
+2023-03-22,Alimentos,70,280.85,19659.5
+2023-02-19,Eletrônicos,86,290.42,24976.120000000003
+2023-12-26,Brinquedos,11,490.36,5393.96
+2023-01-02,Eletrônicos,16,46.92,750.72
+2023-02-23,Brinquedos,97,159.79,15499.63
+2023-04-16,Brinquedos,73,103.55,7559.15
+2023-09-17,Roupas,59,141.55,8351.45
+2023-11-06,Eletrônicos,70,247.79,17345.3
+2023-07-10,Alimentos,80,192.62,15409.6
+2023-08-06,Alimentos,93,203.4,18916.2
+2023-02-13,Eletrônicos,3,423.66,1270.98
+2023-06-11,Alimentos,20,465.71,9314.199999999999
+2023-07-21,Alimentos,59,44.5,2625.5
+2023-09-27,Eletrônicos,36,112.37,4045.32
+2023-12-17,Brinquedos,19,338.86,6438.34
+2023-10-31,Eletrônicos,90,185.74,16716.600000000002
+2023-09-28,Brinquedos,67,134.54,9014.18
+2023-08-03,Alimentos,19,154.69,2939.11
+2023-09-09,Alimentos,20,168.05,3361.0
+2023-07-09,Alimentos,96,425.85,40881.600000000006
+2023-10-23,Roupas,71,76.94,5462.74
+2023-08-01,Brinquedos,52,357.37,18583.24
+2023-07-27,Roupas,33,280.88,9269.039999999999
+2023-08-25,Roupas,40,155.29,6211.599999999999
+2023-12-04,Eletrônicos,39,215.69,8411.91
+2023-02-22,Roupas,82,135.54,11114.279999999999
+2023-10-07,Eletrônicos,1,309.64,309.64
+2023-08-05,Eletrônicos,11,49.98,549.78
+2023-09-09,Roupas,92,12.54,1153.6799999999998
+2023-07-07,Brinquedos,57,317.67,18107.190000000002
+2023-02-10,Brinquedos,89,105.19,9361.91
+2023-06-06,Brinquedos,50,44.76,2238.0
+2023-01-15,Brinquedos,23,204.42,4701.66
+2023-10-28,Brinquedos,31,34.88,1081.28
+2023-03-06,Roupas,94,444.44,41777.36
+2023-12-11,Roupas,42,23.53,988.26
+2023-11-23,Alimentos,99,293.64,29070.359999999997
+2023-01-09,Brinquedos,7,224.85,1573.95
+2023-12-10,Roupas,16,339.29,5428.64
+2023-05-09,Alimentos,90,170.79,15371.099999999999