analise-de-segmentacao-de-clientes-no-e-commerce.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/carlamendescms/analise-de-segmentacao-de-clientes-no-e-commerce?scriptVersionId=120425918\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown","outputs":[],"execution_count":0},{"cell_type":"markdown","id":"7e72b9bd","metadata":{"_cell_guid":"049068e6-de54-44d8-a850-e5e9e7275088","_uuid":"3c614c51-29b3-4021-a7bd-e4774e950cc0","papermill":{"duration":0.021395,"end_time":"2023-02-26T23:21:01.990528","exception":false,"start_time":"2023-02-26T23:21:01.969133","status":"completed"},"tags":[]},"source":["# <font color=\"#ff009e\">Projeto 3 - Análise de Segmentação de Clientes no e-commerce</font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","<img align=\"right\" width=\"240\" height=\"240\" src=\"https://v.fastcdn.co/u/cf943cfe/59276032-0-Ilustraciones.png\">\n","\n","Este notebook faz parte da solução que desenvolvi para o Projeto 3 da **[Certificação Analista de Dados](https://www.laboratoria.la/br/certificacao-analise-de-dados)** da Laboratoria em parceria com a IBM.\n","\n","**Por: [Carla Mendes](https://www.linkedin.com/in/carlamendescms/)**\n","\n","\n","\n","\n","## <img align=\"left\"  width=\"240\" height=\"120\" src=\"https://v.fastcdn.co/u/cf943cfe/27418802-0-Laboratoria-Logo-RGB.png\"> \n","\n","<hr color=\"#F5F5F5\" size=\"2\"> \n","\n","\n","A **[Laboratoria](https://laboratoria.la/br)** tem como principal objetivo tornar a economia digital mais diversificada, inclusiva e competitiva que abra oportunidades para que mulheres possam desenvolver o seu potencial e assim transforme o futuro da América Latina.\n","\n","<div style=\"display:inline-block;vertical-align:top;\">\n","<h2>Sumário:</h2>\n","<ul>\n","    <li><a href=\"#contexto-projeto\">Sobre o Contexto do Projeto </a></li>\n","    <li><a href=\"#descricao-variaveis\">Descrição das Variáveis do Dataset</a></li>\n","     <li><a href=\"#importar-dataset\">Importar o Dataset</a></li>\n","    <li><a href=\"#limpar-dataset\">Entender e limpar o conjunto de dados</a></li>\n","     <li><a href=\"#analise-metricas\">Análise de Métricas de Vendas </a></li>\n","     <li><a href=\"#analise-coorte\">Análise de Coorte</a></li>\n","    <li><a href=\"#segmentacao\"> Segmentação de Clientes usando RFM </a></li>\n","     <li><a href=\"#recomendacoes\">Recomendações a UK Merch</a></li>\n","     <li><a href=\"#referencias\">Referências</a></li>\n","</ul>\n","</div>\n","\n","<a id='contexto-projeto'></a>\n","# <font color=\"#ff009e\">Sobre o Contexto do Projeto</font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","### Realizar uma segmentação de clientes aplicando a metodologia RFM para um e-commerce.\n","\n","Neste projeto, deverá ser realizada uma análise descritiva que mostrará ao CEO da <strong>UK Merch</strong>, uma empresa de varejo o quão bem ou mal as vendas estão indo em sua empresa.\n","\n","Trata-se de uma empresa jovem, com apenas 10 meses, que se dedica à venda de vestuário no atacado, ou seja, vende em quantidades relativamente grandes (geralmente 20 peças ou mais) e oferece um preço mais competitivo que o varejo convencional. Seus clientes são empresas menores que abastecem seu estoque comprando da UK Merch.\n","\n","Deverá medir o engajamento do cliente com base em uma <mark><b>análise de coorte</b></mark> e realizar uma <mark><b>segmentação de clientes aplicando a metodologia RFM</b></mark>, para que o negócio possa focar seus esforços e adotar estratégias diferenciadas para cada segmento, além de realizar a limpeza e o tratamento dos dados anteriormente a isso.\n","\n","<div class=\"alert alert-info\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">📌 Os principais objetivos na aprendizagem deste projeto: </div></strong> <br>\n","<div style=\"color: rgb(0, 0, 0);\">→ Realizar limpeza e tratamento de dados; </div>\n","<div style=\"color: rgb(0, 0, 0);\">→ Realizar uma análise de coorte;</div>\n","<div style=\"color: rgb(0, 0, 0);\">→ Realizar segmentação de clientes usando o modelo RFM; e</div>\n","<div style=\"color: rgb(0, 0, 0);\">→ Desenvolver visualizações.</div>\n","</div>\n","\n","<a id='descricao-variaveis'></a>\n","# <font color=\"#ff009e\"> Descrição das Variáveis do Dataset</font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","| Variável | Descrição |\n","| --- | --- |\n","| **Nº da fatura** | Um número atribuído exclusivamente a cada transação. Se começar com \"c\", indica uma substituição. |\n","| **Data da fatura** | Data e hora da fatura, dia e hora em que a transação foi gerada. |\n","| **ID Cliente** | Número de clientes. Um número integral de 5 dígitos atribuído exclusivamente a cada cliente. |\n","| **País** | O nome do país onde cada cliente reside. |\n","| **Quantidade** | As quantidades de cada produto (item) por transação. |\n","| **Valor** | Valor da fatura em libras esterlinas. |"]},{"cell_type":"code","execution_count":1,"id":"83412b9c","metadata":{"_cell_guid":"1089fc2e-6b5d-4ac6-9c48-d1c0c4587bd0","_kg_hide-input":false,"_uuid":"ea1860b2-8a00-41f8-b8a9-97a78637bf54","execution":{"iopub.execute_input":"2023-02-26T23:21:02.030544Z","iopub.status.busy":"2023-02-26T23:21:02.029937Z","iopub.status.idle":"2023-02-26T23:21:04.137777Z","shell.execute_reply":"2023-02-26T23:21:04.136682Z"},"papermill":{"duration":2.13074,"end_time":"2023-02-26T23:21:04.140161","exception":false,"start_time":"2023-02-26T23:21:02.009421","status":"completed"},"tags":[]},"outputs":[],"source":["import numpy as np # linear algebra\n","import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n","import seaborn as sns \n","import matplotlib.pyplot as plt\n","import squarify\n","import plotly.express as px\n","\n","import warnings\n","warnings.simplefilter(action='ignore', category=FutureWarning)\n","\n","diretorio = ''\n","import os\n","for dirname, _, filenames in os.walk('/kaggle/input'):\n","    for filename in filenames:\n","        diretorio = diretorio + (os.path.join(dirname, filename)) # diretorio do local do dataset"]},{"cell_type":"code","execution_count":2,"id":"a1971c92","metadata":{"_cell_guid":"42570175-35cc-4942-bfda-6e4d49d339b9","_kg_hide-input":false,"_uuid":"71710942-1b55-4628-80af-a3e3971ca7b0","execution":{"iopub.execute_input":"2023-02-26T23:21:04.179427Z","iopub.status.busy":"2023-02-26T23:21:04.179076Z","iopub.status.idle":"2023-02-26T23:21:04.185357Z","shell.execute_reply":"2023-02-26T23:21:04.184037Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.029735,"end_time":"2023-02-26T23:21:04.188665","exception":false,"start_time":"2023-02-26T23:21:04.15893","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Versão do Pandas -> 1.3.5\n","Versão do Numpy -> 1.21.6\n","Versão do Seaborn -> 0.11.2\n"]}],"source":["# Verificando as versões das bibliotecas utilizadas\n","print('Versão do Pandas -> %s' % pd.__version__)\n","print('Versão do Numpy -> %s' % np.__version__)\n","print('Versão do Seaborn -> %s' % sns.__version__)"]},{"cell_type":"markdown","id":"6f7898b2","metadata":{"_cell_guid":"ee9ae3b6-6018-4068-8838-5c9b7e6ba5f9","_uuid":"8de8982a-f5c9-4016-bba1-8d6a389a29b8","papermill":{"duration":0.018697,"end_time":"2023-02-26T23:21:04.226856","exception":false,"start_time":"2023-02-26T23:21:04.208159","status":"completed"},"tags":[]},"source":["<div class=\"alert alert-info\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">✨  Comentário:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\">→ A etapa de entendimento, limpeza e tratamento dos dados é um <strong>item obrigatório</strong> e sua entrega será avaliada, sendo assim, os passos desenvolvidos para esta finalidade foram <strong>descritos detalhadamente neste notebook</strong>.</div>\n","</div>"]},{"cell_type":"markdown","id":"1425ed63","metadata":{"_cell_guid":"36a93325-9466-4efa-8ae9-1437e3b0d941","_uuid":"7f2e54be-ffed-436f-87f3-d35afd441e2a","papermill":{"duration":0.01885,"end_time":"2023-02-26T23:21:04.264722","exception":false,"start_time":"2023-02-26T23:21:04.245872","status":"completed"},"tags":[]},"source":["<a id='importar-dataset'></a>\n","# <font color=\"#ff009e\"> 1 - Importar o dataset </font>\n","<hr color=\"#F5F5F5\" size=\"1\">"]},{"cell_type":"code","execution_count":3,"id":"587c11e6","metadata":{"_cell_guid":"d4a21fd4-0603-4c2a-829a-3c9342312c94","_uuid":"0fb99af2-708b-40bc-9b6b-4e4435bc322f","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:04.304017Z","iopub.status.busy":"2023-02-26T23:21:04.303676Z","iopub.status.idle":"2023-02-26T23:21:04.389315Z","shell.execute_reply":"2023-02-26T23:21:04.387946Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.107916,"end_time":"2023-02-26T23:21:04.391489","exception":false,"start_time":"2023-02-26T23:21:04.283573","status":"completed"},"tags":[]},"outputs":[{"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>N° da fatura</th>\n","      <th>Data da fatura</th>\n","      <th>ID Cliente</th>\n","      <th>País</th>\n","      <th>Quantidade</th>\n","      <th>Valor</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>548370</td>\n","      <td>3/30/2021 16:14:00</td>\n","      <td>15528.0</td>\n","      <td>United Kingdom</td>\n","      <td>123</td>\n","      <td>229,33</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>575767</td>\n","      <td>11/11/2021 11:11:00</td>\n","      <td>17348.0</td>\n","      <td>United Kingdom</td>\n","      <td>163</td>\n","      <td>209,73</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>C570727</td>\n","      <td>10/12/2021 11:32:00</td>\n","      <td>12471.0</td>\n","      <td>Germany</td>\n","      <td>-1</td>\n","      <td>-1,45</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>549106</td>\n","      <td>4/6/2021 12:08:00</td>\n","      <td>17045.0</td>\n","      <td>United Kingdom</td>\n","      <td>1</td>\n","      <td>39,95</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>573112</td>\n","      <td>10/27/2021 15:33:00</td>\n","      <td>16416.0</td>\n","      <td>United Kingdom</td>\n","      <td>357</td>\n","      <td>344,83</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  N° da fatura       Data da fatura  ID Cliente            País  Quantidade  \\\n","0       548370   3/30/2021 16:14:00     15528.0  United Kingdom         123   \n","1       575767  11/11/2021 11:11:00     17348.0  United Kingdom         163   \n","2      C570727  10/12/2021 11:32:00     12471.0         Germany          -1   \n","3       549106    4/6/2021 12:08:00     17045.0  United Kingdom           1   \n","4       573112  10/27/2021 15:33:00     16416.0  United Kingdom         357   \n","\n","    Valor  \n","0  229,33  \n","1  209,73  \n","2   -1,45  \n","3   39,95  \n","4  344,83  "]},"execution_count":3,"metadata":{},"output_type":"execute_result"}],"source":["df_ecommerce = pd.read_csv(diretorio)\n","df_ecommerce.head()"]},{"cell_type":"code","execution_count":4,"id":"e65806cc","metadata":{"_cell_guid":"9727798c-0fd0-4516-99c1-920fdbbd8255","_uuid":"9003b0e0-8557-4675-adc9-4863ae710190","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:04.432116Z","iopub.status.busy":"2023-02-26T23:21:04.431757Z","iopub.status.idle":"2023-02-26T23:21:04.438254Z","shell.execute_reply":"2023-02-26T23:21:04.436941Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.030077,"end_time":"2023-02-26T23:21:04.440754","exception":false,"start_time":"2023-02-26T23:21:04.410677","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Index(['N° da fatura', 'Data da fatura', 'ID Cliente', 'País', 'Quantidade',\n","       'Valor'],\n","      dtype='object')"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["df_ecommerce.columns"]},{"cell_type":"markdown","id":"51dc946a","metadata":{"_cell_guid":"bc44bdae-6a43-4f4a-83a9-8da6165308c5","_uuid":"83640fc0-4b07-421d-9e1b-571f1e6bd7b9","papermill":{"duration":0.019358,"end_time":"2023-02-26T23:21:04.480153","exception":false,"start_time":"2023-02-26T23:21:04.460795","status":"completed"},"tags":[]},"source":["Confirmando as colunas importadas no dataset que já sabemos que deveriam ser 6 e quais são. Aqui estão todas as colunas: 'N° da fatura', 'Data da fatura', 'ID Cliente', 'País', 'Quantidade' e 'Valor'."]},{"cell_type":"code","execution_count":5,"id":"6e9bf339","metadata":{"_cell_guid":"10475cc6-e116-4feb-a082-50b1059e4e9d","_uuid":"5ae61541-56c3-4629-977a-49981b680162","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:04.520038Z","iopub.status.busy":"2023-02-26T23:21:04.519709Z","iopub.status.idle":"2023-02-26T23:21:04.525142Z","shell.execute_reply":"2023-02-26T23:21:04.523764Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.028493,"end_time":"2023-02-26T23:21:04.527771","exception":false,"start_time":"2023-02-26T23:21:04.499278","status":"completed"},"tags":[]},"outputs":[],"source":["# Adicionando _ no nome das colunas para facilitar a manipulação\n","df_ecommerce.columns = df_ecommerce.columns.str.replace(\" \", \"_\")"]},{"cell_type":"markdown","id":"7398cb36","metadata":{"_cell_guid":"7eff1439-17b9-4f4a-b576-2e702bf4b4c1","_uuid":"7fae4261-d240-49de-9dfa-39f7ffb725f5","papermill":{"duration":0.018529,"end_time":"2023-02-26T23:21:04.565312","exception":false,"start_time":"2023-02-26T23:21:04.546783","status":"completed"},"tags":[]},"source":["<a id='limpar-dataset'></a>\n","# <font color=\"#ff009e\"> 2 - Entender e limpar o conjunto de dados </font>\n","<hr color=\"#F5F5F5\" size=\"1\">"]},{"cell_type":"code","execution_count":6,"id":"96de8b6f","metadata":{"_cell_guid":"2e1c7e53-2144-4c49-a8a1-4ab5ce102d58","_uuid":"c2f06231-afb8-4488-b08e-a6cf3e674049","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:04.605355Z","iopub.status.busy":"2023-02-26T23:21:04.604982Z","iopub.status.idle":"2023-02-26T23:21:04.633091Z","shell.execute_reply":"2023-02-26T23:21:04.632213Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.050093,"end_time":"2023-02-26T23:21:04.635031","exception":false,"start_time":"2023-02-26T23:21:04.584938","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 25953 entries, 0 to 25952\n","Data columns (total 6 columns):\n"," #   Column          Non-Null Count  Dtype  \n","---  ------          --------------  -----  \n"," 0   N°_da_fatura    25953 non-null  object \n"," 1   Data_da_fatura  25953 non-null  object \n"," 2   ID_Cliente      22229 non-null  float64\n"," 3   País            25953 non-null  object \n"," 4   Quantidade      25953 non-null  int64  \n"," 5   Valor           25953 non-null  object \n","dtypes: float64(1), int64(1), object(4)\n","memory usage: 1.2+ MB\n"]}],"source":["df_ecommerce.info()"]},{"cell_type":"markdown","id":"db92b504","metadata":{"_cell_guid":"408b76a5-231f-4334-9610-e1de0a5aecb4","_uuid":"e865c3f7-617d-4290-af78-3166622e5fa8","papermill":{"duration":0.018554,"end_time":"2023-02-26T23:21:04.673036","exception":false,"start_time":"2023-02-26T23:21:04.654482","status":"completed"},"tags":[]},"source":["<a id='detectar-nulo'></a>\n","## <font color=\"#ff009e\"> 2.1 Detecção de nulos ou vazios </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","Existem 22229 linhas com dados sobre 'ID_Cliente' enquanto há 25953 linhas preenchidas referente as outras colunas. Ou seja, temos que <mark><strong> existem 3.724 registros que não conseguimos identificar quem é o cliente</strong></mark>.\n","\n","<div class=\"alert alert-warning\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">☠️  Importante:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\">Na análise de coorte de clientes, utilizamos como critério para cálculo da retenção de clientes uma data de coorte. Para evitar criar cenários falsos de retenção, como não conseguimos afirmar que os clientes com ID nulo são ou não os mesmos que já contabilizados em alguma data de coorte, então iremos <strong>remover os registros que tenham 'ID_Cliente' nulos</strong> e evitar esse equívoco. </div>\n","</div>"]},{"cell_type":"code","execution_count":7,"id":"de1a1d4e","metadata":{"_cell_guid":"cdab7226-67eb-4edd-afb9-67d516db1438","_uuid":"b5b7b344-b2aa-43d3-96b0-6ebbc7afb699","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:04.711779Z","iopub.status.busy":"2023-02-26T23:21:04.711408Z","iopub.status.idle":"2023-02-26T23:21:04.722459Z","shell.execute_reply":"2023-02-26T23:21:04.72089Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.033607,"end_time":"2023-02-26T23:21:04.725116","exception":false,"start_time":"2023-02-26T23:21:04.691509","status":"completed"},"tags":[]},"outputs":[],"source":["# Removendo linhas com registro nulo na coluna 'ID_Cliente'\n","df_ecommerce = df_ecommerce.dropna(subset=[\"ID_Cliente\"])"]},{"cell_type":"code","execution_count":8,"id":"5f2297d7","metadata":{"_cell_guid":"326846dd-2205-4afa-8f7d-fc1200c97872","_uuid":"aeb02b45-4f36-4bcd-b124-02f98beaec76","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:04.765361Z","iopub.status.busy":"2023-02-26T23:21:04.765033Z","iopub.status.idle":"2023-02-26T23:21:04.775126Z","shell.execute_reply":"2023-02-26T23:21:04.773867Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.033294,"end_time":"2023-02-26T23:21:04.777766","exception":false,"start_time":"2023-02-26T23:21:04.744472","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["False"]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["# verificando se existem valores nulos em qualquer uma das colunas\n","df_ecommerce.isnull().values.any()"]},{"cell_type":"markdown","id":"9b09f546","metadata":{"_cell_guid":"a7cca60d-b92a-455b-a660-eb110d1dbeae","_uuid":"91d22362-ddb9-4455-b20a-cefaf07c9498","papermill":{"duration":0.019646,"end_time":"2023-02-26T23:21:04.81815","exception":false,"start_time":"2023-02-26T23:21:04.798504","status":"completed"},"tags":[]},"source":["Após isso foi possível validar que não há mais campos nulos em nenhuma das colunas existentes."]},{"cell_type":"markdown","id":"46d5fb42","metadata":{"_cell_guid":"8ffcc875-f941-4869-a740-6c95237a9087","_uuid":"895e408d-109e-4a1c-a43f-8d6bbb4fc9b9","papermill":{"duration":0.019104,"end_time":"2023-02-26T23:21:04.856579","exception":false,"start_time":"2023-02-26T23:21:04.837475","status":"completed"},"tags":[]},"source":["<a id='detectar-dupliacados'></a>\n","## <font color=\"#ff009e\">  2.2 Detecção e remoção de dados duplicados </font>\n","<hr color=\"#F5F5F5\" size=\"1\">"]},{"cell_type":"code","execution_count":9,"id":"b0ebbf35","metadata":{"_cell_guid":"f53366e6-e086-4e91-8a47-c6b4057e8d77","_uuid":"558b76df-fb2d-45be-a8fe-01943ca189e6","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:04.897613Z","iopub.status.busy":"2023-02-26T23:21:04.897246Z","iopub.status.idle":"2023-02-26T23:21:04.921379Z","shell.execute_reply":"2023-02-26T23:21:04.920117Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.047006,"end_time":"2023-02-26T23:21:04.923232","exception":false,"start_time":"2023-02-26T23:21:04.876226","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["(22221, 6)"]},"execution_count":9,"metadata":{},"output_type":"execute_result"}],"source":["# Removendo os dados duplicados do dataset, se houver\n","df_ecommerce.drop_duplicates(inplace=True)\n","\n","# apresentando quantidade de linhas e colunas\n","df_ecommerce.shape"]},{"cell_type":"markdown","id":"323cb2e9","metadata":{"_cell_guid":"7fb2a594-112f-419a-88c7-e7e22069e216","_uuid":"7056ba5e-d5af-4349-99e2-e1af7e883690","papermill":{"duration":0.018898,"end_time":"2023-02-26T23:21:04.960992","exception":false,"start_time":"2023-02-26T23:21:04.942094","status":"completed"},"tags":[]},"source":["Para evitar contabilizar a mesma venda duas ou mais vezes, iremos remover as vendas que foram duplicadas, deixando apeas 1 venda para cada uma. Agora temos 22221 registros, ou seja, foram identificadas e <mark><strong>removidas 8 linhas duplicadas</strong></mark>."]},{"cell_type":"markdown","id":"98a43a7e","metadata":{"_cell_guid":"5c2915fe-4ebc-4207-b2eb-b803e58f9871","_uuid":"9ee0a0d4-8278-42b2-91f0-bb88b7dde019","papermill":{"duration":0.019325,"end_time":"2023-02-26T23:21:04.999797","exception":false,"start_time":"2023-02-26T23:21:04.980472","status":"completed"},"tags":[]},"source":["<a id='eliminar-negativos'></a>\n","##  <font color=\"#ff009e\">  2.3 Detecção e eliminação de quantidades negativas </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","Como as faturas que iniciam com a letra 'C' correspondem a devolução e desejamos analisar as vendas do negócio e não os estornos realizados, então iremos identificar e remover esses valores do nosso dataset."]},{"cell_type":"code","execution_count":10,"id":"9cace5ef","metadata":{"_cell_guid":"e761464d-86cb-4307-8d35-94c8b0aabff7","_uuid":"fd7318e1-d29a-4272-b2ab-6f0e9b446da9","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:05.040306Z","iopub.status.busy":"2023-02-26T23:21:05.039885Z","iopub.status.idle":"2023-02-26T23:21:05.056748Z","shell.execute_reply":"2023-02-26T23:21:05.055877Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.039411,"end_time":"2023-02-26T23:21:05.058487","exception":false,"start_time":"2023-02-26T23:21:05.019076","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["(3655, 6)"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["# filtrando todas as faturas que começam com 'C'\n","devolucao = df_ecommerce['N°_da_fatura'].str.startswith('C')\n","\n","# verificando a quantidade de linhas identificadas\n","df_ecommerce[devolucao].shape"]},{"cell_type":"markdown","id":"bbbfff7f","metadata":{"_cell_guid":"f5d0178b-8316-46cf-a83c-b936dad68cca","_uuid":"3dcc49f5-3438-473d-b046-6b09c71e356b","papermill":{"duration":0.019103,"end_time":"2023-02-26T23:21:05.096546","exception":false,"start_time":"2023-02-26T23:21:05.077443","status":"completed"},"tags":[]},"source":["Foram identificadas <mark><strong>3655 compras que tiveram devolução</strong></mark> e elas <strong>serão removidas do dataset</strong>."]},{"cell_type":"code","execution_count":11,"id":"0b4c1f9e","metadata":{"_cell_guid":"345b2309-1604-4962-a68e-75df72a32514","_uuid":"4e47c6de-30c4-4ece-b949-ebc9963231d7","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:05.136328Z","iopub.status.busy":"2023-02-26T23:21:05.136009Z","iopub.status.idle":"2023-02-26T23:21:05.144247Z","shell.execute_reply":"2023-02-26T23:21:05.14359Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.030577,"end_time":"2023-02-26T23:21:05.146214","exception":false,"start_time":"2023-02-26T23:21:05.115637","status":"completed"},"tags":[]},"outputs":[],"source":["df_ecommerce.drop(df_ecommerce[devolucao].index, inplace=True)"]},{"cell_type":"markdown","id":"031feca3","metadata":{"_cell_guid":"a23ee24f-7440-4e4e-84d3-f4eb318054b4","_uuid":"d1d121c9-fd9d-4b3d-89a3-08d3dc884c58","papermill":{"duration":0.01916,"end_time":"2023-02-26T23:21:05.184656","exception":false,"start_time":"2023-02-26T23:21:05.165496","status":"completed"},"tags":[]},"source":["<div class=\"alert alert-info\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">✔️ Resultado:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\">→ Como resultado da limpeza realizada temos 18566 registros após aplicar a limpeza nos dados. </div>\n","</div>\n","\n","\n","Mas antes, para permitir a manipulação dos dados, iremos aplicar alguns tratamentos necessários para as análises.\n","\n","<a id='tratamento-dados'></a>\n","## <font color=\"#ff009e\"> 2.4 Tratamento de Dados </font>\n","<hr color=\"#F5F5F5\" size=\"1\">"]},{"cell_type":"code","execution_count":12,"id":"836421bc","metadata":{"_cell_guid":"71668e67-dc5a-4046-8480-27b36ea4b6c5","_uuid":"33b49acf-210a-4310-838b-289e23d24f7a","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:05.224462Z","iopub.status.busy":"2023-02-26T23:21:05.224137Z","iopub.status.idle":"2023-02-26T23:21:06.934933Z","shell.execute_reply":"2023-02-26T23:21:06.934251Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":1.732589,"end_time":"2023-02-26T23:21:06.936528","exception":false,"start_time":"2023-02-26T23:21:05.203939","status":"completed"},"tags":[]},"outputs":[{"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>N°_da_fatura</th>\n","      <th>Data_da_fatura</th>\n","      <th>ID_Cliente</th>\n","      <th>País</th>\n","      <th>Quantidade</th>\n","      <th>Valor</th>\n","      <th>Ano_mes</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>9367</th>\n","      <td>536365</td>\n","      <td>2020-12-01 08:26:00</td>\n","      <td>17850.0</td>\n","      <td>United Kingdom</td>\n","      <td>40</td>\n","      <td>139.12</td>\n","      <td>2020-12</td>\n","    </tr>\n","    <tr>\n","      <th>18259</th>\n","      <td>536366</td>\n","      <td>2020-12-01 08:28:00</td>\n","      <td>17850.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>22.20</td>\n","      <td>2020-12</td>\n","    </tr>\n","    <tr>\n","      <th>11185</th>\n","      <td>536368</td>\n","      <td>2020-12-01 08:34:00</td>\n","      <td>13047.0</td>\n","      <td>United Kingdom</td>\n","      <td>15</td>\n","      <td>70.05</td>\n","      <td>2020-12</td>\n","    </tr>\n","    <tr>\n","      <th>6876</th>\n","      <td>536367</td>\n","      <td>2020-12-01 08:34:00</td>\n","      <td>13047.0</td>\n","      <td>United Kingdom</td>\n","      <td>83</td>\n","      <td>278.73</td>\n","      <td>2020-12</td>\n","    </tr>\n","    <tr>\n","      <th>8195</th>\n","      <td>536369</td>\n","      <td>2020-12-01 08:35:00</td>\n","      <td>13047.0</td>\n","      <td>United Kingdom</td>\n","      <td>3</td>\n","      <td>17.85</td>\n","      <td>2020-12</td>\n","    </tr>\n","    <tr>\n","      <th>505</th>\n","      <td>536370</td>\n","      <td>2020-12-01 08:45:00</td>\n","      <td>12583.0</td>\n","      <td>France</td>\n","      <td>449</td>\n","      <td>855.86</td>\n","      <td>2020-12</td>\n","    </tr>\n","    <tr>\n","      <th>12932</th>\n","      <td>536371</td>\n","      <td>2020-12-01 09:00:00</td>\n","      <td>13748.0</td>\n","      <td>United Kingdom</td>\n","      <td>80</td>\n","      <td>204.00</td>\n","      <td>2020-12</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["      N°_da_fatura      Data_da_fatura  ID_Cliente            País  \\\n","9367        536365 2020-12-01 08:26:00     17850.0  United Kingdom   \n","18259       536366 2020-12-01 08:28:00     17850.0  United Kingdom   \n","11185       536368 2020-12-01 08:34:00     13047.0  United Kingdom   \n","6876        536367 2020-12-01 08:34:00     13047.0  United Kingdom   \n","8195        536369 2020-12-01 08:35:00     13047.0  United Kingdom   \n","505         536370 2020-12-01 08:45:00     12583.0          France   \n","12932       536371 2020-12-01 09:00:00     13748.0  United Kingdom   \n","\n","       Quantidade   Valor  Ano_mes  \n","9367           40  139.12  2020-12  \n","18259          12   22.20  2020-12  \n","11185          15   70.05  2020-12  \n","6876           83  278.73  2020-12  \n","8195            3   17.85  2020-12  \n","505           449  855.86  2020-12  \n","12932          80  204.00  2020-12  "]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["# Convertendo tipo da 'Data da Fatura' para data\n","df_ecommerce[\"Data_da_fatura\"] = pd.to_datetime(df_ecommerce[\"Data_da_fatura\"])\n","\n","# alterando a separação dos valores de ',' para '.' na coluna Valor\n","df_ecommerce['Valor'] = df_ecommerce['Valor'].str.replace(\",\", \".\")\n","\n","# alterando o tipo da coluna 'Valor' para float\n","df_ecommerce['Valor'] = pd.to_numeric(df_ecommerce['Valor'])\n","\n","# Obtendo Ano e Mês da data \n","df_ecommerce['Ano_mes'] = df_ecommerce['Data_da_fatura'].dt.to_period('M')\n","\n","# Ordenando pela Data da Fatura de maneira ascendente para facilitar nossas análises\n","df_ecommerce.sort_values(by=['Data_da_fatura'], inplace=True)\n","\n","df_ecommerce.head(7)"]},{"cell_type":"code","execution_count":13,"id":"fe84cd12","metadata":{"_cell_guid":"989cfd1f-f2a2-4f99-b64f-81d6eac12418","_uuid":"1596ce28-9271-48b1-abc9-590be738de9c","collapsed":false,"execution":{"iopub.execute_input":"2023-02-26T23:21:06.978775Z","iopub.status.busy":"2023-02-26T23:21:06.978175Z","iopub.status.idle":"2023-02-26T23:21:06.984537Z","shell.execute_reply":"2023-02-26T23:21:06.983809Z"},"jupyter":{"outputs_hidden":false},"papermill":{"duration":0.030173,"end_time":"2023-02-26T23:21:06.986907","exception":false,"start_time":"2023-02-26T23:21:06.956734","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["N°_da_fatura              object\n","Data_da_fatura    datetime64[ns]\n","ID_Cliente               float64\n","País                      object\n","Quantidade                 int64\n","Valor                    float64\n","Ano_mes                period[M]\n","dtype: object"]},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":["df_ecommerce.dtypes"]},{"cell_type":"markdown","id":"fe8d7f1c","metadata":{"_cell_guid":"c8a742ff-f10a-4519-8058-c4dd9409e362","_uuid":"5a27eabc-ca01-4c4b-95ff-fa099810c789","papermill":{"duration":0.020546,"end_time":"2023-02-26T23:21:07.027882","exception":false,"start_time":"2023-02-26T23:21:07.007336","status":"completed"},"tags":[]},"source":["<div class=\"alert alert-success\"> \n","    <strong><div style=\"color: rgb(0, 0, 0);\"><strong>Resumindo as etapas de limpeza e tratamento realizadas:</strong></div></strong> <br>\n","     <div style=\"color: rgb(0, 0, 0);\">→ ✔️ Remoção de 3.724 registros que não conseguimos identificar quem é o cliente, pois ID estava nulo. </div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ ✔️ Remoção de 8 faturas duplicadas. </div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ ✔️ Remoção de 3655 faturas que tiveram devolução. </div>     \n","    <div style=\"color: rgb(0, 0, 0);\">→ ✔️ Utilizaremos <strong><font color=\"#ff009e\">18566 faturas para as nossas análises.</font></strong></div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ ✔️ Conversão de tipos dados de algumas colunas. </div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ ✔️ Criação de coluna Ano e Mês para facilitar análises. </div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ ✔️ Dataset pronto. Vamos começar! 💪 </div>\n","</div>"]},{"cell_type":"markdown","id":"aca4ab7a","metadata":{"_cell_guid":"af515981-cbda-41a0-a966-2d4bc2ac069e","_uuid":"db5d31e9-36ac-48d1-bc0b-45605b2e9d33","papermill":{"duration":0.020035,"end_time":"2023-02-26T23:21:07.068174","exception":false,"start_time":"2023-02-26T23:21:07.048139","status":"completed"},"tags":[]},"source":["<a id='analise-metricas'></a>\n","# <font color=\"#ff009e\">  3 - Análise de Métricas de Vendas </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","<div class=\"alert alert-info\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">💡 O que queremos responder:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\">→ Quanto é a venda em média por mês? </div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ Quantas vendas há em cada mês? </div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ Qual é o mês em que mais há vendas? </div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ Quais são os clientes mais importantes? </div>\n","    <div style=\"color: rgb(0, 0, 0);\">→ Qual porcentagem de seus clientes voltou a comprar? </div>\n","     <div style=\"color: rgb(0, 0, 0);\">→ Qual é o valor médio que os clientes gastam? </div>\n","     <div style=\"color: rgb(0, 0, 0);\">→ Como as informações são desagregadas de acordo com os países onde há vendas? </div>\n","</div>\n","\n","<a id='analise-faturas'></a>\n","## <font color=\"#ff009e\"> 3.1 Análise do número de faturas por país </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","Agora iremos analisar a quantidade total de faturas emitidas por país e a porcentagem de faturas representada por país e encontrar o **5 maiores países compradores da UK Merch**."]},{"cell_type":"code","execution_count":14,"id":"fcc4a904","metadata":{"execution":{"iopub.execute_input":"2023-02-26T23:21:07.110103Z","iopub.status.busy":"2023-02-26T23:21:07.109569Z","iopub.status.idle":"2023-02-26T23:21:07.113563Z","shell.execute_reply":"2023-02-26T23:21:07.112946Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.026929,"end_time":"2023-02-26T23:21:07.115366","exception":false,"start_time":"2023-02-26T23:21:07.088437","status":"completed"},"tags":[]},"outputs":[],"source":["#definindo cores que serão usadas nos gráficos\n","cinza = '#a4a4a4'\n","rosa = '#ff009e'"]},{"cell_type":"code","execution_count":15,"id":"5f8fc03a","metadata":{"_cell_guid":"279bdeea-7c47-49ad-9821-55ef2cbeb684","_uuid":"12d41d14-c2cd-45d0-9f0e-63422bb0ecaf","execution":{"iopub.execute_input":"2023-02-26T23:21:07.157441Z","iopub.status.busy":"2023-02-26T23:21:07.156912Z","iopub.status.idle":"2023-02-26T23:21:07.17381Z","shell.execute_reply":"2023-02-26T23:21:07.172352Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.041294,"end_time":"2023-02-26T23:21:07.176352","exception":false,"start_time":"2023-02-26T23:21:07.135058","status":"completed"},"tags":[]},"outputs":[{"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>País</th>\n","      <th>N°_de_faturas</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>35</th>\n","      <td>United Kingdom</td>\n","      <td>16676</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>Germany</td>\n","      <td>457</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>France</td>\n","      <td>390</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>EIRE</td>\n","      <td>261</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Belgium</td>\n","      <td>98</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["              País  N°_de_faturas\n","35  United Kingdom          16676\n","14         Germany            457\n","13          France            390\n","10            EIRE            261\n","3          Belgium             98"]},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":["# Quantidade de Fatura por país\n","df_fatura_pais = pd.DataFrame(df_ecommerce.groupby(['País'])\n","                              ['N°_da_fatura'].count()).reset_index()\n","df_fatura_pais.columns = ['País', 'N°_de_faturas']\n","df_fatura_pais.sort_values('N°_de_faturas', ascending=False, inplace=True)\n","df_fatura_pais.head(5)"]},{"cell_type":"code","execution_count":16,"id":"4e23b802","metadata":{"_cell_guid":"485c24a7-5e3c-4250-bceb-3a2de1fa6ac6","_uuid":"7895793f-13f7-490c-9419-529037d26055","execution":{"iopub.execute_input":"2023-02-26T23:21:07.218448Z","iopub.status.busy":"2023-02-26T23:21:07.218032Z","iopub.status.idle":"2023-02-26T23:21:07.232099Z","shell.execute_reply":"2023-02-26T23:21:07.230711Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.037294,"end_time":"2023-02-26T23:21:07.234298","exception":false,"start_time":"2023-02-26T23:21:07.197004","status":"completed"},"tags":[]},"outputs":[{"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>País</th>\n","      <th>N°_de_faturas</th>\n","      <th>Percentual_de_faturas_%</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>35</th>\n","      <td>United Kingdom</td>\n","      <td>16676</td>\n","      <td>89.82</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>Germany</td>\n","      <td>457</td>\n","      <td>2.46</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>France</td>\n","      <td>390</td>\n","      <td>2.10</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>EIRE</td>\n","      <td>261</td>\n","      <td>1.41</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Belgium</td>\n","      <td>98</td>\n","      <td>0.53</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["              País  N°_de_faturas  Percentual_de_faturas_%\n","35  United Kingdom          16676                    89.82\n","14         Germany            457                     2.46\n","13          France            390                     2.10\n","10            EIRE            261                     1.41\n","3          Belgium             98                     0.53"]},"execution_count":16,"metadata":{},"output_type":"execute_result"}],"source":["#calculando percentual de faturas por país\n","df_fatura_pais['Percentual_de_faturas_%'] = (df_fatura_pais['N°_de_faturas']/\n","                                             df_fatura_pais['N°_de_faturas'].sum()) * 100\n","df_fatura_pais['Percentual_de_faturas_%'] = df_fatura_pais['Percentual_de_faturas_%'].round(2)\n","df_fatura_pais.head(5)"]},{"cell_type":"markdown","id":"c8b19a72","metadata":{"_cell_guid":"7d290cec-df7d-4a3a-8308-6d322ef4a2d0","_uuid":"10cbf7c3-419b-4ccf-86c8-1d4e3ee550e9","papermill":{"duration":0.019617,"end_time":"2023-02-26T23:21:07.274585","exception":false,"start_time":"2023-02-26T23:21:07.254968","status":"completed"},"tags":[]},"source":["O **Reino Unido** é o campeão em compras na UK Merch e **representa quase 90% da quantidade de vendas totais**. Como a empresa nasceu lá, é bem provável que isso explique o por quê dele estar em primeiro lugar. \n","\n","Os próximos 4 países com maior quantidade de compras ficam na <strong>todos ficam na Europa, ou seja, relativamente próximos ao Reino Unido</strong>. Eles são:\n","- Alemanha, \n","- França, \n","- Irlanda e \n","- Bélgica, respectivamente."]},{"cell_type":"markdown","id":"a19de010","metadata":{"_cell_guid":"94d3d191-4188-4c96-a84f-eaa406ba46ba","_uuid":"24686239-dce8-413d-aa91-67843259b735","papermill":{"duration":0.020112,"end_time":"2023-02-26T23:21:07.314706","exception":false,"start_time":"2023-02-26T23:21:07.294594","status":"completed"},"tags":[]},"source":["<a id='analise-total-pais'></a>\n","## <font color=\"#ff009e\">  3.2 Análise de valor total por país </font>\n","<hr color=\"#F5F5F5\" size=\"1\"> \n","\n","\n","Agora iremos incluir o valor médio, o valor mínimo e o valor máximo por país."]},{"cell_type":"code","execution_count":17,"id":"5a3ece5f","metadata":{"_cell_guid":"b371b6a9-7c24-4313-9afb-020ef3e20f71","_uuid":"3512ed81-8ac7-4d07-8ba7-eaabbd7e21c8","execution":{"iopub.execute_input":"2023-02-26T23:21:07.356854Z","iopub.status.busy":"2023-02-26T23:21:07.356264Z","iopub.status.idle":"2023-02-26T23:21:07.403526Z","shell.execute_reply":"2023-02-26T23:21:07.402129Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.070968,"end_time":"2023-02-26T23:21:07.405773","exception":false,"start_time":"2023-02-26T23:21:07.334805","status":"completed"},"tags":[]},"outputs":[{"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>País</th>\n","      <th>N°_de_faturas</th>\n","      <th>Percentual_de_faturas_%</th>\n","      <th>Valor_médio</th>\n","      <th>Valor_mínimo</th>\n","      <th>Valor_máximo</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>22</th>\n","      <td>Singapore</td>\n","      <td>7</td>\n","      <td>0.04</td>\n","      <td>3039.90</td>\n","      <td>999.26</td>\n","      <td>6068.06</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>Netherlands</td>\n","      <td>95</td>\n","      <td>0.51</td>\n","      <td>3004.70</td>\n","      <td>0.00</td>\n","      <td>20277.92</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>Australia</td>\n","      <td>57</td>\n","      <td>0.31</td>\n","      <td>2430.20</td>\n","      <td>61.20</td>\n","      <td>22775.93</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>Japan</td>\n","      <td>20</td>\n","      <td>0.11</td>\n","      <td>1870.82</td>\n","      <td>15.30</td>\n","      <td>5735.24</td>\n","    </tr>\n","    <tr>\n","      <th>33</th>\n","      <td>Lebanon</td>\n","      <td>1</td>\n","      <td>0.01</td>\n","      <td>1693.88</td>\n","      <td>1693.88</td>\n","      <td>1693.88</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["           País  N°_de_faturas  Percentual_de_faturas_%  Valor_médio  \\\n","22    Singapore              7                     0.04      3039.90   \n","5   Netherlands             95                     0.51      3004.70   \n","7     Australia             57                     0.31      2430.20   \n","15        Japan             20                     0.11      1870.82   \n","33      Lebanon              1                     0.01      1693.88   \n","\n","    Valor_mínimo  Valor_máximo  \n","22        999.26       6068.06  \n","5           0.00      20277.92  \n","7          61.20      22775.93  \n","15         15.30       5735.24  \n","33       1693.88       1693.88  "]},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":["# calculando o valor médio, máximo e mínimo das faturas por país\n","df_valor_medio = pd.DataFrame(df_ecommerce.groupby(['País'])\n","                              ['Valor'].mean()).round(2).reset_index()\n","df_valor_max = pd.DataFrame(df_ecommerce.groupby(['País'])\n","                            ['Valor'].max()).reset_index()\n","df_valor_min = pd.DataFrame(df_ecommerce.groupby(['País'])\n","                            ['Valor'].min()).reset_index()\n","\n","# criando dataframe com a união dos valores médio, máximo e mínimo encontrados\n","df_valor_pais = pd.merge(df_valor_medio,df_valor_min, on=\"País\")\n","df_valor_pais = pd.merge(df_valor_pais,df_valor_max, on=\"País\")\n","df_valor_pais.rename(columns={\"Valor_x\":\"Valor_médio\", \n","                              \"Valor_y\":\"Valor_mínimo\", \n","                              \"Valor\":\"Valor_máximo\"}, inplace=True)\n","\n","# criando dataframe para juntar os valores médios, mínimos e máximos\n","df_analise_pais = pd.merge(df_fatura_pais,\n","                           df_valor_pais, on=\"País\")\n","\n","# ordenando pelo valor médio de modo decrescente\n","df_analise_pais.sort_values('Valor_médio',\n","                            ascending=False, inplace=True)\n","df_analise_pais.head(5)"]},{"cell_type":"markdown","id":"c618b49b","metadata":{"_cell_guid":"07763461-a567-4e73-8aa0-494c5429e96a","_uuid":"d2eba6ca-3f36-4246-a007-fc80859b54bd","papermill":{"duration":0.019457,"end_time":"2023-02-26T23:21:07.445289","exception":false,"start_time":"2023-02-26T23:21:07.425832","status":"completed"},"tags":[]},"source":["Os <strong>países com maior valor médio por fatura</strong> são:\n","- Cingapura, \n","- Holanda, \n","- Austrália, \n","- Japão e \n","- Líbano. \n","\n","Podemos perceber que exceto pela Holanda, todos os outros <strong>ficam na Ásia ou Oceania, ou seja, longe do Reino Unido</strong>. \n","\n","<div class=\"alert alert-info\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">✨  Comentário:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\"> → Será que o valor médio de compra mais alto para esses países seja por causa do valor do frete internacional? 🤔</div>\n","</div>"]},{"cell_type":"code","execution_count":18,"id":"19ee5361","metadata":{"_cell_guid":"10218d56-0f6e-425b-9f28-739e47b06f22","_uuid":"11da80d1-5e11-4d29-b518-55eacab011fa","execution":{"iopub.execute_input":"2023-02-26T23:21:07.487939Z","iopub.status.busy":"2023-02-26T23:21:07.487484Z","iopub.status.idle":"2023-02-26T23:21:07.501174Z","shell.execute_reply":"2023-02-26T23:21:07.499861Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.03733,"end_time":"2023-02-26T23:21:07.5033","exception":false,"start_time":"2023-02-26T23:21:07.46597","status":"completed"},"tags":[]},"outputs":[{"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>País</th>\n","      <th>N°_de_faturas</th>\n","      <th>Percentual_de_faturas_%</th>\n","      <th>Valor_médio</th>\n","      <th>Valor_mínimo</th>\n","      <th>Valor_máximo</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>United Kingdom</td>\n","      <td>16676</td>\n","      <td>89.82</td>\n","      <td>438.26</td>\n","      <td>0.00</td>\n","      <td>168469.60</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Germany</td>\n","      <td>457</td>\n","      <td>2.46</td>\n","      <td>500.80</td>\n","      <td>3.00</td>\n","      <td>9341.26</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>France</td>\n","      <td>390</td>\n","      <td>2.10</td>\n","      <td>535.96</td>\n","      <td>4.63</td>\n","      <td>8895.76</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>EIRE</td>\n","      <td>261</td>\n","      <td>1.41</td>\n","      <td>1017.42</td>\n","      <td>1.45</td>\n","      <td>16774.72</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Belgium</td>\n","      <td>98</td>\n","      <td>0.53</td>\n","      <td>420.37</td>\n","      <td>34.00</td>\n","      <td>1491.59</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["             País  N°_de_faturas  Percentual_de_faturas_%  Valor_médio  \\\n","0  United Kingdom          16676                    89.82       438.26   \n","1         Germany            457                     2.46       500.80   \n","2          France            390                     2.10       535.96   \n","3            EIRE            261                     1.41      1017.42   \n","4         Belgium             98                     0.53       420.37   \n","\n","   Valor_mínimo  Valor_máximo  \n","0          0.00     168469.60  \n","1          3.00       9341.26  \n","2          4.63       8895.76  \n","3          1.45      16774.72  \n","4         34.00       1491.59  "]},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":["# ordendando pelo percentual de modo decrescente\n","df_analise_pais.sort_values('Percentual_de_faturas_%',\n","                            ascending=False, inplace=True)\n","df_analise_pais.head(5)"]},{"cell_type":"markdown","id":"9b691b4a","metadata":{"_cell_guid":"db6d2e37-c0b3-467f-89da-955e5798c2f7","_uuid":"9d261a12-5b07-48a9-b2d0-6f9fa661dc13","papermill":{"duration":0.020257,"end_time":"2023-02-26T23:21:07.544695","exception":false,"start_time":"2023-02-26T23:21:07.524438","status":"completed"},"tags":[]},"source":["O Reino Unido possui um **valor médio de £438,26** por fatura. Esse valor pode ser considerado baixo quando analisamos os 5 maiores valores médios. \n","\n","<div class=\"alert alert-warning\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">💭  Importante:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\"> → Um ponto importante que percebemos que existem <strong>faturas que apresentam valores £0,00</strong>. \n","        <div style=\"color: rgb(0, 0, 0);\"> → Isso seria <strong>erro de lançamento de dados?</strong>. 🤔\n","        <div style=\"color: rgb(0, 0, 0);\"> → Ou seriam <strong>doações</strong> que foram realizadas? 🤔\n","</div>"]},{"cell_type":"markdown","id":"00760b5b","metadata":{"_cell_guid":"3285142f-edfd-467b-a16c-8d31061cb510","_uuid":"81ce6cde-f8f7-497e-a08a-d0942da64530","papermill":{"duration":0.020302,"end_time":"2023-02-26T23:21:07.585555","exception":false,"start_time":"2023-02-26T23:21:07.565253","status":"completed"},"tags":[]},"source":["<a id='faturas-por-mes'></a>\n","## <font color=\"#ff009e\">  3.3 Faturas geradas por mês </font>\n","<hr color=\"#F5F5F5\" size=\"1\">  \n","\n","Vamos visualizar qual a quantidade de faturas geradas por mês ao longo do período."]},{"cell_type":"code","execution_count":19,"id":"fe9b7ad7","metadata":{"_cell_guid":"c49dfec5-c6c7-4a3c-b061-1aaa211a56e2","_uuid":"e3d832e5-fa46-47d4-96f8-e77bf1027e64","execution":{"iopub.execute_input":"2023-02-26T23:21:07.627928Z","iopub.status.busy":"2023-02-26T23:21:07.627548Z","iopub.status.idle":"2023-02-26T23:21:07.907249Z","shell.execute_reply":"2023-02-26T23:21:07.905831Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.303498,"end_time":"2023-02-26T23:21:07.909239","exception":false,"start_time":"2023-02-26T23:21:07.605741","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Text(0.5, 1.0, 'Total de faturas por mês')"]},"execution_count":19,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# agrupando a quantidade de fatura por Mês e Ano.\n","df_fatura_mes = pd.DataFrame(df_ecommerce.groupby(['Ano_mes'])\n","                             ['N°_da_fatura'].count()).reset_index()\n","df_fatura_mes.rename(columns={\"N°_da_fatura\": \"Quantidade_de_faturas\"},\n","                             inplace=True)\n","\n","# convertendo tipo do dado da coluna \"Ano_mes\" para string\n","df_fatura_mes['Ano_mes'] = df_fatura_mes['Ano_mes'].astype(str)\n","\n","# plotando o gráfico\n","sns.set_theme(style=\"white\", palette=None)\n","plt.figure(figsize = (15,8))\n","\n","ax = sns.lineplot(data=df_fatura_mes,\n","                  x=\"Ano_mes\",\n","                  y=\"Quantidade_de_faturas\",\n","                  color=rosa,\n","                  linewidth=2.5,\n","                  marker=\"o\")\n","ax.set_xlabel('Período')\n","ax.set_ylabel('Quantidade de Faturas')\n","ax.set_title('Total de faturas por mês')"]},{"cell_type":"markdown","id":"86e7f343","metadata":{"_cell_guid":"22b1739f-9cdf-4b96-8557-c08b2d2388f5","_uuid":"481c100c-72b5-4a01-81e1-1f7bb11d9ac9","papermill":{"duration":0.021227,"end_time":"2023-02-26T23:21:07.952303","exception":false,"start_time":"2023-02-26T23:21:07.931076","status":"completed"},"tags":[]},"source":["<a id='fatuas-por-mes'></a>\n","## <font color=\"#ff009e\">  3.4 Número de faturas do Reino Unido _versus_ estrangeiras por mês </font>\n","<hr color=\"#F5F5F5\" size=\"1\">  \n","\n","\n","Após segmentar os clientes da UK Merch em dois grupos: os que <strong>pertencem ao Reino Unido</strong> e os que <strong>não pertencem ao Reino Unido</strong>, agora iremos verificar a quantidade desses dois grupos.\n","\n","Primeiro iremos verificar quais são os países dos clientes."]},{"cell_type":"code","execution_count":20,"id":"d2b99aaa","metadata":{"_cell_guid":"7f726416-9327-431c-99c7-34cee18a38bf","_uuid":"a7eacf88-e613-4332-82c9-74fd09131549","execution":{"iopub.execute_input":"2023-02-26T23:21:07.996075Z","iopub.status.busy":"2023-02-26T23:21:07.995639Z","iopub.status.idle":"2023-02-26T23:21:08.003592Z","shell.execute_reply":"2023-02-26T23:21:08.002407Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.03247,"end_time":"2023-02-26T23:21:08.005443","exception":false,"start_time":"2023-02-26T23:21:07.972973","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["array(['United Kingdom', 'France', 'Australia', 'Netherlands', 'Germany',\n","       'Norway', 'EIRE', 'Switzerland', 'Spain', 'Poland', 'Portugal',\n","       'Italy', 'Belgium', 'Lithuania', 'Japan', 'Iceland',\n","       'Channel Islands', 'Denmark', 'Cyprus', 'Sweden', 'Finland',\n","       'Austria', 'Greece', 'Singapore', 'Lebanon',\n","       'United Arab Emirates', 'Israel', 'Saudi Arabia', 'Czech Republic',\n","       'Canada', 'Unspecified', 'Brazil', 'USA', 'European Community',\n","       'Bahrain', 'Malta', 'RSA'], dtype=object)"]},"execution_count":20,"metadata":{},"output_type":"execute_result"}],"source":["df_ecommerce['País'].unique()"]},{"cell_type":"code","execution_count":21,"id":"98d0023f","metadata":{"_cell_guid":"146752be-4f5a-4d3e-92be-516564fdc838","_uuid":"f8ce3b36-78f4-4b30-946b-3b01bd668332","execution":{"iopub.execute_input":"2023-02-26T23:21:08.050315Z","iopub.status.busy":"2023-02-26T23:21:08.049751Z","iopub.status.idle":"2023-02-26T23:21:08.058281Z","shell.execute_reply":"2023-02-26T23:21:08.057203Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.033765,"end_time":"2023-02-26T23:21:08.060523","exception":false,"start_time":"2023-02-26T23:21:08.026758","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Média de faturas sem país especificado:  333.38375\n","Soma de faturas sem país especificado:  2667.07\n"]}],"source":["# contando quantidade de faturas sem país especificado\n","nao_especificado = df_ecommerce[df_ecommerce['País']=='Unspecified']\n","nao_especificado.shape\n","print('Média de faturas sem país especificado: ', nao_especificado['Valor'].mean())\n","print('Soma de faturas sem país especificado: ', nao_especificado['Valor'].sum())"]},{"cell_type":"markdown","id":"b5ae079b","metadata":{"_cell_guid":"2409c524-b5d2-4d50-96b6-2bc171f26c83","_uuid":"f1a93324-550c-400b-aeac-4099af188260","papermill":{"duration":0.021107,"end_time":"2023-02-26T23:21:08.103167","exception":false,"start_time":"2023-02-26T23:21:08.08206","status":"completed"},"tags":[]},"source":["Percebe-se que existem <strong>8 faturas que não possuem o país de origem definidos</strong> e não conseguidos garantir que estas faturas sejam ou não do Reino Unido. \n","\n","Porém como a soma e a média dos valores das faturas não apresentam tando impacto aos resultados finais quando comparados aos valores totais das faturas do dataset, então iremos realizar a análise contabilizando-os, deixando como <strong>não pertencentes ao Reino Unido nas somas gerais.</strong>"]},{"cell_type":"code","execution_count":22,"id":"a9d85f6e","metadata":{"_cell_guid":"0fbad79a-aa40-4966-b6d3-c4ef9fea586a","_uuid":"76373dfd-07ea-442a-9de5-c574819c980f","execution":{"iopub.execute_input":"2023-02-26T23:21:08.14791Z","iopub.status.busy":"2023-02-26T23:21:08.147279Z","iopub.status.idle":"2023-02-26T23:21:08.169069Z","shell.execute_reply":"2023-02-26T23:21:08.167639Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.046987,"end_time":"2023-02-26T23:21:08.171541","exception":false,"start_time":"2023-02-26T23:21:08.124554","status":"completed"},"tags":[]},"outputs":[],"source":["# Criando coluna para classificar se o cliente pertence ou não ao Reino Unido\n","df_ecommerce.loc[df_ecommerce['País']==\"United Kingdom\", 'Pertence_UK'] = \"SIM\"\n","df_ecommerce.loc[df_ecommerce['País']!=\"United Kingdom\", 'Pertence_UK'] = \"NÃO\"\n","\n","# agrupando a quantidade de faturas por ano e se pertence ou não ao Reino Unido\n","df_fatura_mes_pais = pd.DataFrame(df_ecommerce.groupby(['Ano_mes', \n","                                              'Pertence_UK'])\n","                                  ['N°_da_fatura'].count()).reset_index()\n","\n","# renomeando a coluna N°_da_fatura\n","df_fatura_mes_pais.rename(columns={\"N°_da_fatura\":\"Quantidade_de_faturas\"},inplace=True)\n","\n","# convertendo tipo do dado da coluna \"Ano_mes\" para string \n","df_fatura_mes_pais['Ano_mes'] = df_fatura_mes_pais['Ano_mes'].astype(str)"]},{"cell_type":"markdown","id":"3f2ba781","metadata":{"_cell_guid":"c45bc8b0-291f-4db2-9ae0-968d307a559b","_uuid":"a968860e-ca20-4d98-ab34-44e5b7d2c394","papermill":{"duration":0.020338,"end_time":"2023-02-26T23:21:08.213451","exception":false,"start_time":"2023-02-26T23:21:08.193113","status":"completed"},"tags":[]},"source":["Visualizando o gráfico de **Total de Faturas por Mês** por faturas do Reino Unido X Estrangeiras"]},{"cell_type":"code","execution_count":23,"id":"1a3645bc","metadata":{"_cell_guid":"ddd06d85-8abf-4960-a204-b381b8d89caa","_uuid":"63072068-bc17-4a4f-8118-72417e2ec267","execution":{"iopub.execute_input":"2023-02-26T23:21:08.256551Z","iopub.status.busy":"2023-02-26T23:21:08.256219Z","iopub.status.idle":"2023-02-26T23:21:08.508927Z","shell.execute_reply":"2023-02-26T23:21:08.507629Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.276857,"end_time":"2023-02-26T23:21:08.51106","exception":false,"start_time":"2023-02-26T23:21:08.234203","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<matplotlib.legend.Legend at 0x7f739e117210>"]},"execution_count":23,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# plotando o gráfico\n","sns.set_theme(style=\"white\", palette=None)\n","plt.figure(figsize = (15,8))\n","ax = sns.lineplot(data=df_fatura_mes_pais,\n","                          x=\"Ano_mes\",\n","                          y=\"Quantidade_de_faturas\",\n","                          hue=\"Pertence_UK\",\n","                          legend=False,\n","                          palette=[cinza,rosa],\n","                          linewidth=2.5,\n","                          marker=\"o\"\n","                 )\n","ax.set_xlabel('Período')\n","ax.set_ylabel('Quantidade de Faturas')\n","ax.set_title('Total de faturas por mês')\n","\n","# alterando posição e nome dos dados da legenda\n","plt.legend(labels = ['Não Pertence a UK','Pertence a UK'],loc = 2, bbox_to_anchor = (1,1))"]},{"cell_type":"markdown","id":"5db4a079","metadata":{"_cell_guid":"b5299fde-d189-4541-8066-e610445d7892","_uuid":"e528a46a-487f-402a-a9e9-b7d0a5c55175","papermill":{"duration":0.022199,"end_time":"2023-02-26T23:21:08.555764","exception":false,"start_time":"2023-02-26T23:21:08.533565","status":"completed"},"tags":[]},"source":["Percebe-se que, sem levar em conta o mês atípico de dezembro de 2021, ambos os segmentos estão crescendo, porém os clientes pertecentes ao Reino Unido de maneira mais acentuada. \n","\n","<a id='clientes-por-mes'></a>\n","## <font color=\"#ff009e\">  3.5 Número de novos clientes por mês </font>\n","<hr color=\"#F5F5F5\" size=\"1\">  \n","\n","Agora iremos analisar a quantidade de clientes únicos a cada mês"]},{"cell_type":"code","execution_count":24,"id":"114db4bc","metadata":{"_cell_guid":"18998e21-258d-40f9-b3da-3866dc8cc5e8","_uuid":"8a3ea90f-07ca-4f7d-acae-09ee15b926bd","execution":{"iopub.execute_input":"2023-02-26T23:21:08.600561Z","iopub.status.busy":"2023-02-26T23:21:08.600175Z","iopub.status.idle":"2023-02-26T23:21:08.6145Z","shell.execute_reply":"2023-02-26T23:21:08.613644Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.039561,"end_time":"2023-02-26T23:21:08.616936","exception":false,"start_time":"2023-02-26T23:21:08.577375","status":"completed"},"tags":[]},"outputs":[{"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>Ano_mes</th>\n","      <th>Quantidade_clientes_unicos</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>2020-12</td>\n","      <td>885</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2021-01</td>\n","      <td>741</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2021-02</td>\n","      <td>758</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>2021-03</td>\n","      <td>974</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>2021-04</td>\n","      <td>856</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>2021-05</td>\n","      <td>1056</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>2021-06</td>\n","      <td>991</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>2021-07</td>\n","      <td>949</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>2021-08</td>\n","      <td>935</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>2021-09</td>\n","      <td>1266</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>2021-10</td>\n","      <td>1364</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>2021-11</td>\n","      <td>1665</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>2021-12</td>\n","      <td>615</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["    Ano_mes  Quantidade_clientes_unicos\n","0   2020-12                         885\n","1   2021-01                         741\n","2   2021-02                         758\n","3   2021-03                         974\n","4   2021-04                         856\n","5   2021-05                        1056\n","6   2021-06                         991\n","7   2021-07                         949\n","8   2021-08                         935\n","9   2021-09                        1266\n","10  2021-10                        1364\n","11  2021-11                        1665\n","12  2021-12                         615"]},"execution_count":24,"metadata":{},"output_type":"execute_result"}],"source":["# Quantidade de clientes únicos por mês e ano\n","df_clientes_novos = pd.DataFrame(df_ecommerce.groupby(['Ano_mes'])\n","                                 ['ID_Cliente'].nunique()).reset_index()\n","df_clientes_novos.columns = ['Ano_mes', 'Quantidade_clientes_unicos']\n","df_clientes_novos"]},{"cell_type":"code","execution_count":25,"id":"f7ffed03","metadata":{"_cell_guid":"09392c11-01b8-4326-82f4-b114c0b1664e","_uuid":"cbc553fb-7d2e-473c-80d0-0d3356ce50dc","execution":{"iopub.execute_input":"2023-02-26T23:21:08.662965Z","iopub.status.busy":"2023-02-26T23:21:08.662572Z","iopub.status.idle":"2023-02-26T23:21:08.961501Z","shell.execute_reply":"2023-02-26T23:21:08.960098Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.325179,"end_time":"2023-02-26T23:21:08.964425","exception":false,"start_time":"2023-02-26T23:21:08.639246","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# convertendo tipo do dado da coluna \"Ano_mes\" para string \n","df_clientes_novos['Ano_mes'] = df_clientes_novos['Ano_mes'].astype(str)\n","\n","sns.set_theme(style=\"white\", palette=None)\n","plt.figure(figsize = (15,8))\n","\n","ax = sns.lineplot(data=df_clientes_novos,\n","                  x=\"Ano_mes\",\n","                  y=\"Quantidade_clientes_unicos\",\n","                  color=rosa,\n","                  linewidth=2.5,\n","                  marker=\"o\")\n","\n","ax.set_xlabel('', fontsize=14, labelpad=10)\n","ax.set_ylabel('Quantidade de clientes únicos', fontsize=14, labelpad=10)\n","ax.set_title('Clientes únicos por mês')\n","\n","# incluindo rótulos nos pontos do gráfico\n","for x, y in zip(df_clientes_novos['Ano_mes'], \n","                df_clientes_novos['Quantidade_clientes_unicos']):\n","     plt.text(x = x, # posição x\n","               y = y+30, # posição y + 30 na coordenada\n","               s = '{:.0f}'.format(y), # formato \n","               color = 'white').set_backgroundcolor('#965786') # cor da fonte e do background"]},{"cell_type":"markdown","id":"b69483f7","metadata":{"_cell_guid":"95c573fd-1add-4596-876f-0b9236c43523","_uuid":"ea857afe-cab4-474c-9ddb-a8f38639739c","papermill":{"duration":0.022854,"end_time":"2023-02-26T23:21:09.010403","exception":false,"start_time":"2023-02-26T23:21:08.987549","status":"completed"},"tags":[]},"source":["<div class=\"alert alert-info\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">✨  Comentário:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\">  → O mês de Novembro/2021 teve o maior pico de clientes únicos realizando compras. Isso provavelmente se deu por causa de eventos que estimulam as compras como <strong>Black Friday</strong>? 🤔 </div>\n","</div>"]},{"cell_type":"markdown","id":"3f45b390","metadata":{"_cell_guid":"64b3600f-afcd-40c4-a0e3-356d9f264f0a","_uuid":"5a2c12cd-ebfa-42eb-8aeb-ad12d7d8ef3f","papermill":{"duration":0.022523,"end_time":"2023-02-26T23:21:09.055934","exception":false,"start_time":"2023-02-26T23:21:09.033411","status":"completed"},"tags":[]},"source":["<a id='outras-analises'></a>\n","## <font color=\"#ff009e\"> 3.6 Outras análises relevantes para o dataset </font>\n","<hr color=\"#F5F5F5\" size=\"1\"> \n","\n","- Montante total de vendas por mês"]},{"cell_type":"code","execution_count":26,"id":"7163a1b7","metadata":{"_cell_guid":"be64f77a-4199-4508-8dd9-320af5c15740","_uuid":"2d66dd9e-b813-40fc-a1b9-dc30f39bf4ca","execution":{"iopub.execute_input":"2023-02-26T23:21:09.10414Z","iopub.status.busy":"2023-02-26T23:21:09.103793Z","iopub.status.idle":"2023-02-26T23:21:09.348973Z","shell.execute_reply":"2023-02-26T23:21:09.348044Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.27133,"end_time":"2023-02-26T23:21:09.350879","exception":false,"start_time":"2023-02-26T23:21:09.079549","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Text(0, 0.5, 'Valor em Libras (k)')"]},"execution_count":26,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# realizando o cálculo total de vendas por mês\n","df_montante_mes = pd.DataFrame(df_ecommerce.groupby(['Ano_mes'])\n","                               ['Valor'].sum()).reset_index()\n","df_montante_mes.columns = ['Ano_mes', 'Montante Total de Vendas']\n","\n","# transformando o valor em múltiplo de 1.000 ou K.\n","df_montante_mes['Montante Total de Vendas (K)'] = (df_montante_mes['Montante Total de Vendas']\n","                                                   /1000).round(2)\n","\n","# convertendo tipo do dado da coluna \"Ano_mes\" para string\n","df_montante_mes['Ano_mes'] = df_montante_mes['Ano_mes'].astype(str)\n","\n","# selecionando o valor mínimo dos 3 maiores Montantes totais de vendas\n","minimo = min(df_montante_mes['Montante Total de Vendas (K)'].nlargest(n=3))\n","\n","# colorindo de azul os 3 maiores e colorindo de cinza o restante\n","clrs = [cinza if (x < minimo) else rosa \n","        for x in df_montante_mes['Montante Total de Vendas (K)']]\n","\n","# criando o gráfico de barras\n","sns.set_theme(style=\"white\", palette=None)\n","plt.figure(figsize = (15,8))\n","ax = sns.barplot(x=\"Ano_mes\",\n","                 y=\"Montante Total de Vendas (K)\",\n","                 data=df_montante_mes,\n","                 ci=False,\n","                 palette=clrs)\n","\n","ax.set_title('Montante Total de Vendas por Mês')\n","ax.set_xlabel('', fontsize=14, labelpad=10)\n","ax.set_ylabel('Valor em Libras (k)', fontsize=14, labelpad=10)"]},{"cell_type":"markdown","id":"1885c102","metadata":{"_cell_guid":"27b01e83-6eda-496c-a78c-55993398fcc2","_uuid":"8fd2abf3-dca7-4154-b523-8d448a47f744","papermill":{"duration":0.023186,"end_time":"2023-02-26T23:21:09.397016","exception":false,"start_time":"2023-02-26T23:21:09.37383","status":"completed"},"tags":[]},"source":["Podemos observar que os meses de _Setembro_, _Outubro_ e _Novembro de 2021_ tiveram o maior montante total, com os valores £952.84K, £1039.32K e £1161.82K, respectivamente.\n","\n","- Montante de vendas dentro e fora do Reino Unido, por mês"]},{"cell_type":"code","execution_count":27,"id":"19d6c2f3","metadata":{"_cell_guid":"31dbc6ae-d182-4f46-a9e1-28bc7b48b37f","_uuid":"c5ec204d-30b4-4237-96de-363619f2f66a","execution":{"iopub.execute_input":"2023-02-26T23:21:09.445358Z","iopub.status.busy":"2023-02-26T23:21:09.444968Z","iopub.status.idle":"2023-02-26T23:21:10.071855Z","shell.execute_reply":"2023-02-26T23:21:10.070659Z"},"papermill":{"duration":0.654008,"end_time":"2023-02-26T23:21:10.074365","exception":false,"start_time":"2023-02-26T23:21:09.420357","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Text(0, 0.5, 'Valor em Libras (k)')"]},"execution_count":27,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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size 1440x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["df_mes= pd.DataFrame(df_ecommerce.groupby(by=['Ano_mes',\n","                                    'Pertence_UK'])['Valor'].sum()).reset_index()\n","df_mes.columns = ['Ano_mes','Pertence UK', 'Montante Total de Vendas']\n","\n","# transformando o valor em múltiplo de 1.000 ou K.\n","df_mes['Montante Total de Vendas (K)'] = (df_mes['Montante Total de Vendas']/1000).round(2)\n","\n","# convertendo tipo do dado da coluna \"Ano_mes\" para string para ser utilizando no gráfico que será gerado\n","df_mes['Ano_mes'] = df_mes['Ano_mes'].astype(str)\n","\n","\n","sns.set_theme(style=\"white\", palette=[cinza, rosa])\n","plt.figure(figsize = (20,8))\n","ax = sns.barplot(x=\"Ano_mes\",\n","                 y=\"Montante Total de Vendas (K)\",\n","                 data=df_mes,\n","                 order=df_mes['Ano_mes'],\n","                 hue='Pertence UK',\n","                 ci=False)\n","\n","ax.set_title('Montante Total de Vendas dentro e fora do Reino Unido, por mês')\n","ax.set_xlabel('', fontsize=14, labelpad=10)\n","ax.set_ylabel('Valor em Libras (k)', fontsize=14, labelpad=10)"]},{"cell_type":"markdown","id":"7fe668e2","metadata":{"_cell_guid":"620ac039-3f5b-4f31-b974-7da533e21218","_uuid":"efef3301-f164-4d64-b42b-462db5b5f81f","papermill":{"duration":0.024072,"end_time":"2023-02-26T23:21:10.122907","exception":false,"start_time":"2023-02-26T23:21:10.098835","status":"completed"},"tags":[]},"source":["Observando o gráfico de barras é possível perceber que a grande diferença nos valores de montantes das vendas para o Reino Unido que são bem maiores do que as vendas para fora do Reino Unido.\n","\n","- 10 Maiores clientes que fizeram mais compras dentro e fora do Reino Unido, dentro de um mesmo mês"]},{"cell_type":"code","execution_count":28,"id":"d471649c","metadata":{"_cell_guid":"d2ada94f-3ae9-4beb-aff3-3606088deb87","_uuid":"7fdb7ed0-c7e1-4884-96b4-5edaa568d301","execution":{"iopub.execute_input":"2023-02-26T23:21:10.173363Z","iopub.status.busy":"2023-02-26T23:21:10.173005Z","iopub.status.idle":"2023-02-26T23:21:10.50798Z","shell.execute_reply":"2023-02-26T23:21:10.506808Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.363017,"end_time":"2023-02-26T23:21:10.510192","exception":false,"start_time":"2023-02-26T23:21:10.147175","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Text(0, 0.5, 'Valor em Libras')"]},"execution_count":28,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1296x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# calculando os 10 maiores clientes e determinando se eles são ou não do Reino Unido\n","df_cliente_mes= pd.DataFrame(df_ecommerce.groupby(by=['ID_Cliente',\n","                                                      'Pertence_UK'])\n","                             ['Valor'].sum()).reset_index()\n","df_cliente_mes.columns = ['Cliente', 'Pertence_UK', 'Montante Total de Vendas']\n","df_cliente_mes.sort_values('Montante Total de Vendas', ascending=False, inplace=True)\n","df_cliente_mes = df_cliente_mes.head(10)\n","\n","# visualização\n","sns.set_theme(style=\"white\", palette=[cinza, rosa])\n","plt.figure(figsize = (18,8))\n","ax = sns.barplot(x=\"Cliente\",\n","                 y=\"Montante Total de Vendas\",\n","                 data=df_cliente_mes,\n","                 hue='Pertence_UK',\n","                 order=df_cliente_mes['Cliente'],\n","                 ci=False)\n","ax.set_title('Valores de vendas para os 10 principais clientes')\n","ax.set_xlabel('', fontsize=14, labelpad=10)\n","ax.set_ylabel('Valor em Libras', fontsize=14, labelpad=10)"]},{"cell_type":"markdown","id":"59ab375b","metadata":{"_cell_guid":"378ff93e-c1ee-4265-8926-57db9766f5ad","_uuid":"8d940a27-c9b8-47c1-a7c6-2823e284acf1","papermill":{"duration":0.024327,"end_time":"2023-02-26T23:21:10.55934","exception":false,"start_time":"2023-02-26T23:21:10.535013","status":"completed"},"tags":[]},"source":["- Quantidade mensal de produtos vendidos"]},{"cell_type":"code","execution_count":29,"id":"53c095be","metadata":{"_cell_guid":"8b913cf1-43a9-449c-a685-b2e69e3be96e","_uuid":"18318141-f13d-4764-a935-029fd7d762f4","execution":{"iopub.execute_input":"2023-02-26T23:21:10.609239Z","iopub.status.busy":"2023-02-26T23:21:10.608858Z","iopub.status.idle":"2023-02-26T23:21:10.850636Z","shell.execute_reply":"2023-02-26T23:21:10.849553Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.269205,"end_time":"2023-02-26T23:21:10.852908","exception":false,"start_time":"2023-02-26T23:21:10.583703","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Text(0, 0.5, 'Quantidade')"]},"execution_count":29,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Calculando a quantidade mensal de produtos vendos\n","df_produtos = pd.DataFrame(df_ecommerce.groupby(['Ano_mes'])\n","                           ['Quantidade'].sum()).reset_index()\n","df_produtos.columns = ['Ano_mes', 'Quantidade de Produtos Vendidos']\n","\n","# convertendo tipo do dado da coluna \"Ano_mes\" para string\n","df_produtos['Ano_mes'] = df_produtos['Ano_mes'].astype(str)\n","\n","# selecionando o valor mínimo dos 3 maiores Montantes totais de vendas\n","minimo = min(df_produtos['Quantidade de Produtos Vendidos'].nlargest(n=3))\n","\n","# colorindo de azul os 3 maiores e colorindo de cinza o restante\n","clrs = [cinza if (x < minimo) else rosa \n","        for x in df_produtos['Quantidade de Produtos Vendidos']]\n","\n","# criando o gráfico de barras\n","sns.set_theme(style=\"white\", palette=None)\n","plt.figure(figsize = (15,8))\n","ax = sns.barplot(x=\"Ano_mes\",\n","                 y=\"Quantidade de Produtos Vendidos\",\n","                 data=df_produtos,\n","                 ci=False,\n","                 palette=clrs)\n","\n","ax.set_title('Total de Produtos Vendidos por mês')\n","ax.set_xlabel('', fontsize=14, labelpad=10)\n","ax.set_ylabel('Quantidade', fontsize=14, labelpad=10)"]},{"cell_type":"markdown","id":"3470324b","metadata":{"_cell_guid":"da3911b0-f797-4daa-9219-c740be488259","_uuid":"3a102ff7-0c2e-483f-89a0-a218713058e4","papermill":{"duration":0.024546,"end_time":"2023-02-26T23:21:10.902415","exception":false,"start_time":"2023-02-26T23:21:10.877869","status":"completed"},"tags":[]},"source":["- Ticket Médio do Período"]},{"cell_type":"code","execution_count":30,"id":"7ac8ef34","metadata":{"_cell_guid":"57bac8a4-9f0f-48b1-bf6a-b7687c859d81","_uuid":"1d086c0c-97ba-403c-b5fe-5621450cd124","execution":{"iopub.execute_input":"2023-02-26T23:21:10.955365Z","iopub.status.busy":"2023-02-26T23:21:10.954762Z","iopub.status.idle":"2023-02-26T23:21:10.961592Z","shell.execute_reply":"2023-02-26T23:21:10.960663Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.035512,"end_time":"2023-02-26T23:21:10.963451","exception":false,"start_time":"2023-02-26T23:21:10.927939","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["479.99"]},"execution_count":30,"metadata":{},"output_type":"execute_result"}],"source":["ticket = (df_ecommerce['Valor'].sum() / \n","          df_ecommerce['ID_Cliente'].count()).round(2)\n","ticket"]},{"cell_type":"markdown","id":"42aec291","metadata":{"_cell_guid":"932e336b-bc26-4a69-be6a-8c063ac6dc40","_uuid":"7cc8d098-d174-42f4-91d0-0f6953d7dec9","papermill":{"duration":0.024667,"end_time":"2023-02-26T23:21:11.013304","exception":false,"start_time":"2023-02-26T23:21:10.988637","status":"completed"},"tags":[]},"source":["O Ticket Médio é de **£479.99**."]},{"cell_type":"markdown","id":"1bbd6958","metadata":{"_cell_guid":"9e05c3d2-83c2-40fb-8329-da21ae7a450d","_uuid":"2db6b572-bccd-4acb-8090-19a468606a2b","papermill":{"duration":0.025084,"end_time":"2023-02-26T23:21:11.063293","exception":false,"start_time":"2023-02-26T23:21:11.038209","status":"completed"},"tags":[]},"source":["- Ticket Médio Mensal"]},{"cell_type":"code","execution_count":31,"id":"c880fa1e","metadata":{"_cell_guid":"1afcaaf4-69ca-4f91-b3d3-3cd86e4f33bc","_uuid":"f515cbb4-9b06-4357-a0e3-a9c0179db6fe","execution":{"iopub.execute_input":"2023-02-26T23:21:11.115366Z","iopub.status.busy":"2023-02-26T23:21:11.114986Z","iopub.status.idle":"2023-02-26T23:21:11.426032Z","shell.execute_reply":"2023-02-26T23:21:11.424614Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.339737,"end_time":"2023-02-26T23:21:11.428302","exception":false,"start_time":"2023-02-26T23:21:11.088565","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 1440x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Calculando o valor das vendas mensal\n","ticket = pd.DataFrame(df_ecommerce.groupby(by=['Ano_mes'])\n","                      ['Valor'].sum()).reset_index()\n","\n","# Calculando a quantidade de clientes mensais\n","ticket2 = pd.DataFrame(df_ecommerce.groupby(by=['Ano_mes'])\n","                       ['ID_Cliente'].count()).reset_index()\n","\n","# Unindo os dois dataframes criados \n","ticket_mensal =  pd.merge(ticket,\n","                          ticket2, on=\"Ano_mes\")\n","\n","# Calculando o valor do ticket médio mensal\n","for i in range(12):\n","    ticket_mensal['Ticket Médio Mensal'] = (ticket['Valor'] \n","                                            / ticket2['ID_Cliente']).round(2)\n","\n","# convertendo tipo do dado da coluna \"Ano_mes\" para string\n","ticket_mensal['Ano_mes'] = ticket_mensal['Ano_mes'].astype(str)\n","\n","sns.set_theme(style=\"white\", palette=None)\n","plt.figure(figsize = (20,8))\n","\n","ax = sns.lineplot(data=ticket_mensal,\n","                  x=\"Ano_mes\",\n","                  y=\"Ticket Médio Mensal\",\n","                  color=\"magenta\",\n","                  linewidth=2.5,\n","                  marker=\"o\")\n","\n","ax.set_xlabel('', fontsize=14, labelpad=10)\n","ax.set_ylabel('Valor em Libras (£)', fontsize=14, labelpad=10)\n","ax.set_title('Ticket Médio Mensal')\n","\n","# incluindo rótulos nos pontos do gráfico\n","for x, y in zip(ticket_mensal['Ano_mes'],\n","                ticket_mensal['Ticket Médio Mensal']):\n","     plt.text(x = x, # posição x\n","               y = y+10, # posição y + 30 na coordenada\n","               s = '{:.2f}'.format(y), # formato \n","               color = 'white').set_backgroundcolor('#965786') # cor da fonte e do background"]},{"cell_type":"markdown","id":"d703301d","metadata":{"_cell_guid":"dd707650-7a67-4db1-adad-21219d213878","_uuid":"fce281db-687c-476b-b984-439449019f10","papermill":{"duration":0.025181,"end_time":"2023-02-26T23:21:11.478878","exception":false,"start_time":"2023-02-26T23:21:11.453697","status":"completed"},"tags":[]},"source":["<a id='analise-coorte'></a>\n","# <font color=\"#ff009e\"> 4 - Análise de Coorte </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","Agora, iremos construir uma função que calcula o coorte e retorna o dataframe gerado.\n","\n","## O que é Análise de Coorte?\n","\n","Em Estatística, coorte é um **conjunto de pessoas** que têm em comum um **evento que se deu no mesmo período**.\n","\n","A análise do comportamento e o desempenho de grupos de clientes que possuam atributos em comum auxilia nas estratégias que deverão ser adotadas. Por exemplo, todos os clientes com a mesma data de aquisição pertencem ao mesmo coorte. \n","\n","Para este estudo iremos organizar **os clientes em grupos de data de aquisição** e iremos analisar o comportamento desses grupos de acordo com métricas como **retenção de clientes**, exclusivamente."]},{"cell_type":"code","execution_count":32,"id":"306b99ff","metadata":{"_cell_guid":"032f3828-2faa-45ad-99c4-28ae9b7eec9c","_uuid":"0b0616c3-9bd5-4a4b-b75c-639577f382cf","execution":{"iopub.execute_input":"2023-02-26T23:21:11.531584Z","iopub.status.busy":"2023-02-26T23:21:11.530943Z","iopub.status.idle":"2023-02-26T23:21:12.137087Z","shell.execute_reply":"2023-02-26T23:21:12.135956Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.635022,"end_time":"2023-02-26T23:21:12.139086","exception":false,"start_time":"2023-02-26T23:21:11.504064","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<AxesSubplot:title={'center':'Análise de Coorte para avaliação de retenção de clientes'}, xlabel='Periodo', ylabel='Coorte'>"]},"execution_count":32,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x576 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Definindo uma função para atribuuir os períodos existentes\n","def coorte_periodo(df_coorte):\n","    df_coorte['Periodo'] = np.arange(len(df_coorte)) + 1\n","    return df_coorte\n","\n","def criando_coorte(df_coorte):\n","    # usando os ID's dos clientes como índice\n","    df_coorte.set_index('ID_Cliente', inplace=True)\n","\n","    # criando o coorte de cada cliente\n","    df_coorte[\"Coorte\"] = df_coorte.groupby(level=0)['Ano_mes'].min()\n","\n","    # resetando os índices\n","    df_coorte.reset_index(inplace=True)\n","\n","    # Agrupando por Coorte e Ano_Mes das faturas\n","    coorte = df_coorte.groupby(['Coorte', 'Ano_mes'])\n","    cohorts = coorte.agg({'ID_Cliente': pd.Series.nunique,\n","                          'N°_da_fatura' : pd.Series.nunique,\n","                          'Valor': np.sum})\n","    cohorts.rename(columns={'ID_Cliente':'Total_clientes',\n","                            'N°_da_fatura':'Total_faturas'}, inplace=True)\n","\n","    cohorts = cohorts.groupby(level=0).apply(coorte_periodo)\n","\n","    # reindexando o dataframe\n","    cohorts.reset_index(inplace=True)\n","    cohorts.set_index(['Coorte', 'Periodo'], inplace=True)\n","\n","    # criando uma série para salvar o total de cada cliente por coorte\n","    coorte_grupo = cohorts['Total_clientes'].groupby(level=0).first()\n","\n","    # calculando o total de retenção dos clientes por cada grupo de coorte\n","    retencao_clientes = cohorts['Total_clientes'].unstack(0).divide(coorte_grupo, axis=1)\n","    return retencao_clientes\n","\n","# calculando a retenção dos clientes com a função criando_coorte\n","retencao_clientes = criando_coorte(df_ecommerce)\n","\n","#Aplicando o gráfico no dataframe gerado para visualizar a retenção\n","sns.color_palette(\"rocket\", as_cmap=True)\n","plt.figure(figsize=(15,8))\n","plt.title('Análise de Coorte para avaliação de retenção de clientes')\n","sns.heatmap(retencao_clientes.T,\n","            mask=retencao_clientes.T.isnull(),\n","            annot=True,\n","            fmt='.0%')"]},{"cell_type":"code","execution_count":33,"id":"20d0aca6","metadata":{"_cell_guid":"4f891f71-34b5-4211-8121-618aac4f00bc","_uuid":"91fd0aea-30b4-470c-b369-12b71f931132","execution":{"iopub.execute_input":"2023-02-26T23:21:12.197163Z","iopub.status.busy":"2023-02-26T23:21:12.196391Z","iopub.status.idle":"2023-02-26T23:21:12.765825Z","shell.execute_reply":"2023-02-26T23:21:12.764687Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.600204,"end_time":"2023-02-26T23:21:12.767969","exception":false,"start_time":"2023-02-26T23:21:12.167765","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<AxesSubplot:title={'center':'Análise de Coorte para avaliação de retenção de clientes que são do Reino Unido'}, xlabel='Periodo', ylabel='Coorte'>"]},"execution_count":33,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x576 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# copiando os dados das faturas pertencentes ao Reino Unido\n","df_coorte_UK = df_ecommerce[df_ecommerce['Pertence_UK']=='SIM'].copy()\n","\n","# calculando a retenção dos clientes com a função criando_coorte\n","retencao_clientes_UK = criando_coorte(df_coorte_UK)\n","\n","#Aplicando o gráfico no dataframe gerado para visualizar a retenção\n","sns.color_palette(\"rocket\", as_cmap=True)\n","plt.figure(figsize=(15,8))\n","plt.title('Análise de Coorte para avaliação de retenção de clientes que são do Reino Unido')\n","sns.heatmap(retencao_clientes_UK.T,\n","            mask=retencao_clientes_UK.T.isnull(),\n","            annot=True,\n","            fmt='.0%')"]},{"cell_type":"code","execution_count":34,"id":"f77dfabc","metadata":{"_cell_guid":"cdfd143f-3d48-4ab8-b053-df21c6be97ab","_uuid":"3bc68be7-9293-4e16-8195-17e643c23832","execution":{"iopub.execute_input":"2023-02-26T23:21:12.826367Z","iopub.status.busy":"2023-02-26T23:21:12.825984Z","iopub.status.idle":"2023-02-26T23:21:13.391983Z","shell.execute_reply":"2023-02-26T23:21:13.391104Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.597619,"end_time":"2023-02-26T23:21:13.393997","exception":false,"start_time":"2023-02-26T23:21:12.796378","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<AxesSubplot:title={'center':'Análise de Coorte para avaliação de retenção de clientes que não são do Reino Unido'}, xlabel='Periodo', ylabel='Coorte'>"]},"execution_count":34,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x576 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# copiando os dados das faturas que não pertencem ao Reino Unido\n","df_coorte_nao_UK = df_ecommerce[df_ecommerce['Pertence_UK']=='NÃO'].copy()\n","\n","# calculando a retenção dos clientes com a função criando_coorte\n","retencao_clientes_nao_UK = criando_coorte(df_coorte_nao_UK)\n","\n","#Aplicando o gráfico no dataframe gerado para visualizar a retenção\n","sns.color_palette(\"rocket\", as_cmap=True)\n","plt.figure(figsize=(15,8))\n","plt.title('Análise de Coorte para avaliação de retenção de clientes que não são do Reino Unido')\n","sns.heatmap(retencao_clientes_nao_UK.T,\n","            mask=retencao_clientes_nao_UK.T.isnull(),\n","            annot=True,\n","            fmt='.0%')"]},{"cell_type":"markdown","id":"75bff25c","metadata":{"_cell_guid":"7d45a0cf-be50-429c-9870-9f1b0dcad680","_uuid":"44b14611-77e3-4953-8f2f-144c12d77c53","papermill":{"duration":0.029051,"end_time":"2023-02-26T23:21:13.454165","exception":false,"start_time":"2023-02-26T23:21:13.425114","status":"completed"},"tags":[]},"source":["<a id='segmentacao'></a>\n","# <font color=\"#ff009e\"> 5 - Segmentação de Clientes usando RFM </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","A análise de RFM (Recência, Frequência e Valor Monetário) é baseada no **Princípio de Pareto** e é utilizado no  diz que 80% dos resultados vêm de 20% das causas. Da mesma forma, 20% dos clientes contribuem com 80% da sua receita total.\n","\n","O RFM pode ser representado assim:\n","\n","- **Recência:** quais são os clientes realizaram compras mais recentemente?;\n","- **Frequência:** quais são os clientes que mais comparar mais?; e\n","- **Valor monetário:** quais clientes realizaram as maiores compradas somadas ao total?\n","\n","Após categorizar e classificar cada cliente pelos resultados de encontrados é possível **determinar qual tipo de segmento que cada cliente** será definido, e após isso, **quais estratégia será aplicada para cada cliente**. \n","\n","A partir de agora iremos preparar e calcular o RFM dos clientes.\n","\n","\n","<a id='preparando-segmentacao'></a>\n","## <font color=\"#ff009e\"> 5.1 Preparar um novo conjunto de dados para gerar segmentação dos clientes </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","\n","<div class=\"alert alert-info\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">✨  Como obter:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\"> → <strong>Recência:</strong>  calculamos quantos dias foram desde a compra mais recente do cliente;</div>\n","    <div style=\"color: rgb(0, 0, 0);\"> → <strong>Frequência:</strong> calculamos quantas compras o cliente já realizou; e</div>\n","    <div style=\"color: rgb(0, 0, 0);\"> → <strong>Monetário:</strong> calculamos a soma de todas as compras realizadas pelo cliente.</div>\n","</div>"]},{"cell_type":"code","execution_count":35,"id":"d55b49ba","metadata":{"_cell_guid":"9907f4a8-c47c-421b-a764-288a5ab166b4","_uuid":"0d2ebac7-46e5-406c-8b1e-6b9a05a2e00b","execution":{"iopub.execute_input":"2023-02-26T23:21:13.513929Z","iopub.status.busy":"2023-02-26T23:21:13.513161Z","iopub.status.idle":"2023-02-26T23:21:13.890507Z","shell.execute_reply":"2023-02-26T23:21:13.889232Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.409546,"end_time":"2023-02-26T23:21:13.892664","exception":false,"start_time":"2023-02-26T23:21:13.483118","status":"completed"},"tags":[]},"outputs":[{"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>Cliente</th>\n","      <th>País</th>\n","      <th>Pertence_UK</th>\n","      <th>Coorte</th>\n","      <th>Data_ultima_compra</th>\n","      <th>Recencia</th>\n","      <th>Frequencia</th>\n","      <th>Monetario</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>17850.0</td>\n","      <td>United Kingdom</td>\n","      <td>SIM</td>\n","      <td>2020-12</td>\n","      <td>2020-12-02 15:27:00</td>\n","      <td>371</td>\n","      <td>34</td>\n","      <td>5391.21</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>13047.0</td>\n","      <td>United Kingdom</td>\n","      <td>SIM</td>\n","      <td>2020-12</td>\n","      <td>2021-11-08 12:06:00</td>\n","      <td>31</td>\n","      <td>10</td>\n","      <td>3237.54</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>12583.0</td>\n","      <td>France</td>\n","      <td>NÃO</td>\n","      <td>2020-12</td>\n","      <td>2021-12-07 08:07:00</td>\n","      <td>2</td>\n","      <td>15</td>\n","      <td>7281.38</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>13748.0</td>\n","      <td>United Kingdom</td>\n","      <td>SIM</td>\n","      <td>2020-12</td>\n","      <td>2021-09-05 09:45:00</td>\n","      <td>95</td>\n","      <td>5</td>\n","      <td>948.25</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>15100.0</td>\n","      <td>United Kingdom</td>\n","      <td>SIM</td>\n","      <td>2020-12</td>\n","      <td>2021-01-10 10:35:00</td>\n","      <td>333</td>\n","      <td>3</td>\n","      <td>876.00</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Cliente            País Pertence_UK   Coorte  Data_ultima_compra  Recencia  \\\n","0  17850.0  United Kingdom         SIM  2020-12 2020-12-02 15:27:00       371   \n","1  13047.0  United Kingdom         SIM  2020-12 2021-11-08 12:06:00        31   \n","2  12583.0          France         NÃO  2020-12 2021-12-07 08:07:00         2   \n","3  13748.0  United Kingdom         SIM  2020-12 2021-09-05 09:45:00        95   \n","4  15100.0  United Kingdom         SIM  2020-12 2021-01-10 10:35:00       333   \n","\n","   Frequencia  Monetario  \n","0          34    5391.21  \n","1          10    3237.54  \n","2          15    7281.38  \n","3           5     948.25  \n","4           3     876.00  "]},"execution_count":35,"metadata":{},"output_type":"execute_result"}],"source":["# Calculando a recencia\n","df_recencia = df_ecommerce.groupby(by='ID_Cliente',\n","                                   as_index=False)['Data_da_fatura'].max()\n","df_recencia.columns = ['Cliente', 'Data_ultima_compra']\n","\n","data_recencia = df_recencia['Data_ultima_compra'].max()\n","df_recencia['Recencia'] = df_recencia['Data_ultima_compra'].apply(lambda x:\n","                                                                  (data_recencia - x).days)\n","\n","# calculando a frequencia\n","df_frequencia = df_ecommerce.drop_duplicates().groupby(\n","                    by=['ID_Cliente'],as_index=False)['Data_da_fatura'].count()\n","df_frequencia.columns = ['Cliente', 'Frequencia']\n","\n","# calculando o monetário\n","df_monetario = df_ecommerce.groupby(by='ID_Cliente',\n","                                    as_index=False)['Valor'].sum()\n","df_monetario.columns = ['Cliente', 'Monetario']\n","\n","# criando dataframe com os dados calculados já unidos\n","df_rfm = df_recencia.merge(df_frequencia, on='Cliente')\n","df_rfm = df_rfm.merge(df_monetario, on='Cliente')\n","\n","df_ecommerce_segmentacao = df_ecommerce.copy()\n","df_ecommerce_segmentacao.drop(columns=['N°_da_fatura',\n","                                       'Data_da_fatura',\n","                                       'Quantidade',\n","                                       'Valor',\n","                                       'Ano_mes'],\n","                                inplace=True)\n","\n","# removendo duplicados\n","df_ecommerce_segmentacao.drop_duplicates(inplace=True)\n","df_ecommerce_segmentacao.rename(columns={'ID_Cliente':'Cliente'}, inplace=True)\n","\n","# unindo os DataFrames pelo ID do Cliente\n","df_rfm = df_ecommerce_segmentacao.merge(df_rfm, on='Cliente')\n","df_rfm.head()"]},{"cell_type":"markdown","id":"4fa99026","metadata":{"_cell_guid":"a3b59ab3-9049-43fc-8ff9-75b9fd77240b","_uuid":"d98c5871-de65-4872-abc0-3fd7f2826b5f","papermill":{"duration":0.028836,"end_time":"2023-02-26T23:21:13.950934","exception":false,"start_time":"2023-02-26T23:21:13.922098","status":"completed"},"tags":[]},"source":["<a id='criar-quartis'></a>\n","## <font color=\"#ff009e\"> 5.2 - Criando o quartil para realizar a classificação do cliente </font>\n","<hr color=\"#F5F5F5\" size=\"1\">"]},{"cell_type":"markdown","id":"9f8c4b25","metadata":{"_cell_guid":"46b9c9de-5716-4bbc-b0c7-0972ce659e03","_uuid":"dd8b0fda-80bc-4acc-90bf-4acf9f83ff60","papermill":{"duration":0.029118,"end_time":"2023-02-26T23:21:14.009625","exception":false,"start_time":"2023-02-26T23:21:13.980507","status":"completed"},"tags":[]},"source":["Para gerar os quartis necessários iremos analisar como é a distribuição dos dados de Recência, Frequência e Valor Monetário."]},{"cell_type":"code","execution_count":36,"id":"af84f66b","metadata":{"_cell_guid":"32f2fcad-fe50-44c2-a725-7893993d9d88","_uuid":"a97239c7-6710-4d3c-a3a2-6945cf22a9b4","execution":{"iopub.execute_input":"2023-02-26T23:21:14.071835Z","iopub.status.busy":"2023-02-26T23:21:14.071492Z","iopub.status.idle":"2023-02-26T23:21:14.086135Z","shell.execute_reply":"2023-02-26T23:21:14.085193Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.048027,"end_time":"2023-02-26T23:21:14.088391","exception":false,"start_time":"2023-02-26T23:21:14.040364","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Recencia\n","Média:  91.43961352657004\n","Mediana:  50.0\n","Moda:  0    3\n","dtype: int64\n","Frequência\n","Média:  4.2824936737980215\n","Mediana:  2.0\n","Moda:  0    1\n","dtype: int64\n","Monetário\n","Média:  2055.612300437083\n","Mediana:  675.27\n","Moda:  0    76.32\n","dtype: float64\n"]}],"source":["# gerando Média, Mediana e Moda da Recencia\n","print('Recencia')\n","print('Média: ' ,df_rfm['Recencia'].mean())\n","print('Mediana: ' ,df_rfm['Recencia'].median())\n","print('Moda: ', df_rfm['Recencia'].mode())\n","\n","# gerando Média, Mediana e Moda da Recencia\n","print('Frequência')\n","print('Média: ' ,df_rfm['Frequencia'].mean())\n","print('Mediana: ' ,df_rfm['Frequencia'].median())\n","print('Moda: ', df_rfm['Frequencia'].mode())\n","\n","# gerando Média, Mediana e Moda do Monetário\n","print('Monetário')\n","print('Média: ' ,df_rfm['Monetario'].mean())\n","print('Mediana: ' ,df_rfm['Monetario'].median())\n","print('Moda: ', df_rfm['Monetario'].mode())"]},{"cell_type":"code","execution_count":37,"id":"cb709cd8","metadata":{"_cell_guid":"4aa7830e-c1e6-40ad-9518-79d50791a314","_uuid":"9a04dbfd-58d1-45df-8b58-9636e4cf6aa7","execution":{"iopub.execute_input":"2023-02-26T23:21:14.150736Z","iopub.status.busy":"2023-02-26T23:21:14.150184Z","iopub.status.idle":"2023-02-26T23:21:14.804757Z","shell.execute_reply":"2023-02-26T23:21:14.80381Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.688203,"end_time":"2023-02-26T23:21:14.807172","exception":false,"start_time":"2023-02-26T23:21:14.118969","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 864x720 with 3 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Plot das distribuições de RFM\n","plt.figure(figsize=(12,10))\n","\n","# Distribuição da Recência\n","plt.subplot(3, 1, 1); sns.distplot(df_rfm['Recencia'])\n","\n","# Distribuição da Frequência\n","plt.subplot(3, 1, 2); sns.distplot(df_rfm['Frequencia'])\n","\n","# Distribuição do Monetário\n","plt.subplot(3, 1, 3); sns.distplot(df_rfm['Monetario'])\n","\n","plt.show()"]},{"cell_type":"markdown","id":"5e83bc11","metadata":{"_cell_guid":"cebb541f-ba66-4b1e-9549-d47507400e1e","_uuid":"ef4179d5-b999-4c4a-9f3d-3b6eec56b3d7","papermill":{"duration":0.030357,"end_time":"2023-02-26T23:21:14.870074","exception":false,"start_time":"2023-02-26T23:21:14.839717","status":"completed"},"tags":[]},"source":["Podemos perceber que eles podem ser classificados como uma distribuição normal assimétrica a direita."]},{"cell_type":"code","execution_count":38,"id":"a488ed26","metadata":{"_cell_guid":"8a5bfbad-e008-412f-bd6a-cddeb9f6c328","_uuid":"91f721e5-da09-451e-b7b0-c321cee60add","execution":{"iopub.execute_input":"2023-02-26T23:21:14.932407Z","iopub.status.busy":"2023-02-26T23:21:14.931897Z","iopub.status.idle":"2023-02-26T23:21:14.953314Z","shell.execute_reply":"2023-02-26T23:21:14.952375Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.055488,"end_time":"2023-02-26T23:21:14.955857","exception":false,"start_time":"2023-02-26T23:21:14.900369","status":"completed"},"tags":[]},"outputs":[{"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>Cliente</th>\n","      <th>Recencia</th>\n","      <th>Frequencia</th>\n","      <th>Monetario</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>4347.000000</td>\n","      <td>4347.000000</td>\n","      <td>4347.000000</td>\n","      <td>4347.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>15294.640212</td>\n","      <td>91.439614</td>\n","      <td>4.282494</td>\n","      <td>2055.612300</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>1724.722441</td>\n","      <td>99.942744</td>\n","      <td>7.722808</td>\n","      <td>8980.352817</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>12346.000000</td>\n","      <td>0.000000</td>\n","      <td>1.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>13806.500000</td>\n","      <td>17.000000</td>\n","      <td>1.000000</td>\n","      <td>307.470000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>15292.000000</td>\n","      <td>50.000000</td>\n","      <td>2.000000</td>\n","      <td>675.270000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>16776.500000</td>\n","      <td>141.000000</td>\n","      <td>5.000000</td>\n","      <td>1671.330000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>18287.000000</td>\n","      <td>373.000000</td>\n","      <td>211.000000</td>\n","      <td>280206.020000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["            Cliente     Recencia   Frequencia      Monetario\n","count   4347.000000  4347.000000  4347.000000    4347.000000\n","mean   15294.640212    91.439614     4.282494    2055.612300\n","std     1724.722441    99.942744     7.722808    8980.352817\n","min    12346.000000     0.000000     1.000000       0.000000\n","25%    13806.500000    17.000000     1.000000     307.470000\n","50%    15292.000000    50.000000     2.000000     675.270000\n","75%    16776.500000   141.000000     5.000000    1671.330000\n","max    18287.000000   373.000000   211.000000  280206.020000"]},"execution_count":38,"metadata":{},"output_type":"execute_result"}],"source":["df_rfm.describe()"]},{"cell_type":"markdown","id":"80c67469","metadata":{"_cell_guid":"5b34c9b6-2102-44c5-b5bd-f90a3d9a9f36","_uuid":"9cfc8ca4-8cc5-4cf6-8605-31c8c3a33ee6","papermill":{"duration":0.030373,"end_time":"2023-02-26T23:21:15.017525","exception":false,"start_time":"2023-02-26T23:21:14.987152","status":"completed"},"tags":[]},"source":["<div class=\"alert alert-warning\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">💭  Importante:</div></strong> <br>\n","    <div style=\"color: rgb(0, 0, 0);\"> → Para facilitar a nossa criação dos quartis necessários para realizarmos a segmentação, iremos identificar as faturas que tiveram valor total igual a £0,00 e classificar que elas tiveram Frequência igual a 0 também. </div>\n","</div>"]},{"cell_type":"code","execution_count":39,"id":"0b8e87fd","metadata":{"_cell_guid":"5197c4eb-d5f4-45b4-b34c-6a8447a667f2","_uuid":"947db4be-7855-4aea-a52d-dceba27a1c91","collapsed":true,"execution":{"iopub.execute_input":"2023-02-26T23:21:15.080954Z","iopub.status.busy":"2023-02-26T23:21:15.080549Z","iopub.status.idle":"2023-02-26T23:21:15.116305Z","shell.execute_reply":"2023-02-26T23:21:15.115337Z"},"jupyter":{"outputs_hidden":true,"source_hidden":true},"papermill":{"duration":0.070146,"end_time":"2023-02-26T23:21:15.118429","exception":false,"start_time":"2023-02-26T23:21:15.048283","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  after removing the cwd from sys.path.\n"]}],"source":["# deixando frequencia igual 0 quando monetário for igual a 0.\n","for i in df_rfm.index:\n","    if df_rfm['Monetario'][i] == 0:\n","        df_rfm['Frequencia'][i] = 0"]},{"cell_type":"code","execution_count":40,"id":"4507a516","metadata":{"_cell_guid":"4b5fb5dd-3bf2-4eb2-a2cc-4202c0343b1a","_uuid":"dc74a4b6-00dd-4ff6-9d1a-0d10cd69c29b","execution":{"iopub.execute_input":"2023-02-26T23:21:15.182502Z","iopub.status.busy":"2023-02-26T23:21:15.182119Z","iopub.status.idle":"2023-02-26T23:21:15.204451Z","shell.execute_reply":"2023-02-26T23:21:15.203587Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.057093,"end_time":"2023-02-26T23:21:15.206753","exception":false,"start_time":"2023-02-26T23:21:15.14966","status":"completed"},"tags":[]},"outputs":[{"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>Cliente</th>\n","      <th>Recencia</th>\n","      <th>Frequencia</th>\n","      <th>Monetario</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>4347.000000</td>\n","      <td>4347.000000</td>\n","      <td>4347.000000</td>\n","      <td>4347.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>15294.640212</td>\n","      <td>91.439614</td>\n","      <td>4.282264</td>\n","      <td>2055.612300</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>1724.722441</td>\n","      <td>99.942744</td>\n","      <td>7.722921</td>\n","      <td>8980.352817</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>12346.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>13806.500000</td>\n","      <td>17.000000</td>\n","      <td>1.000000</td>\n","      <td>307.470000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>15292.000000</td>\n","      <td>50.000000</td>\n","      <td>2.000000</td>\n","      <td>675.270000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>16776.500000</td>\n","      <td>141.000000</td>\n","      <td>5.000000</td>\n","      <td>1671.330000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>18287.000000</td>\n","      <td>373.000000</td>\n","      <td>211.000000</td>\n","      <td>280206.020000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["            Cliente     Recencia   Frequencia      Monetario\n","count   4347.000000  4347.000000  4347.000000    4347.000000\n","mean   15294.640212    91.439614     4.282264    2055.612300\n","std     1724.722441    99.942744     7.722921    8980.352817\n","min    12346.000000     0.000000     0.000000       0.000000\n","25%    13806.500000    17.000000     1.000000     307.470000\n","50%    15292.000000    50.000000     2.000000     675.270000\n","75%    16776.500000   141.000000     5.000000    1671.330000\n","max    18287.000000   373.000000   211.000000  280206.020000"]},"execution_count":40,"metadata":{},"output_type":"execute_result"}],"source":["df_rfm.describe()"]},{"cell_type":"markdown","id":"befe86be","metadata":{"_cell_guid":"b02bedec-ee24-4c3c-bb5e-19a19648db51","_uuid":"7a1f443c-f0bd-4384-b930-6d2c3030d74f","papermill":{"duration":0.030626,"end_time":"2023-02-26T23:21:15.268624","exception":false,"start_time":"2023-02-26T23:21:15.237998","status":"completed"},"tags":[]},"source":["Assim, agora temos os quartis definidos:\n","\n","| Categoria | Recência | Frequência | Monetário |\n","| --- | --- | --- | --- |\n","| **Min** | 0 | 0 | £0,00 |\n","| **25%** | 17 | 1 | £307,47 |\n","| **50%** | 50 | 2 | £675,27 |\n","| **75%** | 141 | 5 | £1671,33 |\n","| **Máx** | 373 | 211 | £280.206,02 |\n","\n","Com eles definidos, agora iremos criá-los no dataset."]},{"cell_type":"code","execution_count":41,"id":"9d2a8b87","metadata":{"_cell_guid":"f8e80fb9-9ea8-44d2-b4b4-875cb3807c3b","_uuid":"5de0eee7-cff5-44eb-95d0-1a4ac6048f6d","execution":{"iopub.execute_input":"2023-02-26T23:21:15.332125Z","iopub.status.busy":"2023-02-26T23:21:15.331767Z","iopub.status.idle":"2023-02-26T23:21:15.358703Z","shell.execute_reply":"2023-02-26T23:21:15.357594Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.061922,"end_time":"2023-02-26T23:21:15.361396","exception":false,"start_time":"2023-02-26T23:21:15.299474","status":"completed"},"tags":[]},"outputs":[{"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>Cliente</th>\n","      <th>País</th>\n","      <th>Pertence_UK</th>\n","      <th>Coorte</th>\n","      <th>Data_ultima_compra</th>\n","      <th>Recencia</th>\n","      <th>Frequencia</th>\n","      <th>Monetario</th>\n","      <th>r_quartil</th>\n","      <th>f_quartil</th>\n","      <th>m_quartil</th>\n","      <th>RFM</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>17850.0</td>\n","      <td>United Kingdom</td>\n","      <td>SIM</td>\n","      <td>2020-12</td>\n","      <td>2020-12-02 15:27:00</td>\n","      <td>371</td>\n","      <td>34</td>\n","      <td>5391.21</td>\n","      <td>4</td>\n","      <td>4</td>\n","      <td>4</td>\n","      <td>444</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>13047.0</td>\n","      <td>United Kingdom</td>\n","      <td>SIM</td>\n","      <td>2020-12</td>\n","      <td>2021-11-08 12:06:00</td>\n","      <td>31</td>\n","      <td>10</td>\n","      <td>3237.54</td>\n","      <td>2</td>\n","      <td>4</td>\n","      <td>4</td>\n","      <td>244</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>12583.0</td>\n","      <td>France</td>\n","      <td>NÃO</td>\n","      <td>2020-12</td>\n","      <td>2021-12-07 08:07:00</td>\n","      <td>2</td>\n","      <td>15</td>\n","      <td>7281.38</td>\n","      <td>1</td>\n","      <td>4</td>\n","      <td>4</td>\n","      <td>144</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>13748.0</td>\n","      <td>United Kingdom</td>\n","      <td>SIM</td>\n","      <td>2020-12</td>\n","      <td>2021-09-05 09:45:00</td>\n","      <td>95</td>\n","      <td>5</td>\n","      <td>948.25</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>333</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>15100.0</td>\n","      <td>United Kingdom</td>\n","      <td>SIM</td>\n","      <td>2020-12</td>\n","      <td>2021-01-10 10:35:00</td>\n","      <td>333</td>\n","      <td>3</td>\n","      <td>876.00</td>\n","      <td>4</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>433</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Cliente            País Pertence_UK   Coorte  Data_ultima_compra  Recencia  \\\n","0  17850.0  United Kingdom         SIM  2020-12 2020-12-02 15:27:00       371   \n","1  13047.0  United Kingdom         SIM  2020-12 2021-11-08 12:06:00        31   \n","2  12583.0          France         NÃO  2020-12 2021-12-07 08:07:00         2   \n","3  13748.0  United Kingdom         SIM  2020-12 2021-09-05 09:45:00        95   \n","4  15100.0  United Kingdom         SIM  2020-12 2021-01-10 10:35:00       333   \n","\n","   Frequencia  Monetario r_quartil f_quartil m_quartil  RFM  \n","0          34    5391.21         4         4         4  444  \n","1          10    3237.54         2         4         4  244  \n","2          15    7281.38         1         4         4  144  \n","3           5     948.25         3         3         3  333  \n","4           3     876.00         4         3         3  433  "]},"execution_count":41,"metadata":{},"output_type":"execute_result"}],"source":["# Criando os quartis para Recência, Frequência e Monetário\n","df_rfm['r_quartil'] = pd.qcut(df_rfm['Recencia'], 4, ['1','2','3','4'])\n","df_rfm['f_quartil'] = pd.qcut(df_rfm['Frequencia'], 4, ['1','2','3','4'])\n","df_rfm['m_quartil'] = pd.qcut(df_rfm['Monetario'], 4, ['1','2','3','4'])\n","\n","# Criando coluna \"RFM\" com a junção dos valores de Recência, Frequência e Monetário\n","df_rfm['RFM'] = df_rfm.r_quartil.astype(str) + df_rfm.f_quartil.astype(str) + df_rfm.m_quartil.astype(str)\n","df_rfm.head()"]},{"cell_type":"markdown","id":"f3f22fdf","metadata":{"_cell_guid":"1c7734b8-fbe7-4f46-9693-6330a4dcb7af","_uuid":"d850382e-4995-4750-b459-410868dea7f8","papermill":{"duration":0.031008,"end_time":"2023-02-26T23:21:15.423633","exception":false,"start_time":"2023-02-26T23:21:15.392625","status":"completed"},"tags":[]},"source":["<a id='categorizando-dataset'></a>\n","## <font color=\"#ff009e\"> 5.3 Categorizando cada segmento de cliente de acordo com RFM gerado </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","De acordo com o **[artigo da Puttler](https://www.putler.com/rfm-analysis/)** podemos utilizar as 11 seguintes descrições para cada categoria de clientes. Baseado nisso, já inclui a coluna \"RFM\" contendo os valores que utilizarei para identificar cada tipo:\n","\n","| Categoria | Descrição | RFM |\n","| --- |--- |--- |\n","| **Campeões** | compraram recentemente, compram com frequência e gastam mais | 144 |\n","| **Clientes fiéis** | gastam bem e com boa frequência. São responsivos a promoções | 134, 143, 133 |\n","| **Fiéis em potencial** | clientes recentes, mas que gastaram um bom dinheiro e já compraram mais de uma vez | 123 e 124 |\n","| **Novos clientes** | compraram recentemente, mas não com frequência | 111, 112, 113 e 114 |\n","| **Promessas** | compradores recentes, mas que não gastaram muito | 121, 122, 212 e 222 |\n","| **Clientes precisando de atenção** | recência, frequência e valor monetário acima da curva, mas podem não ter comprado tão recentemente assim | 244 e 344 |\n","| **Quase dormentes** | recência, frequência e valor monetário abaixo da média. Tendem a se perder se não forem reativados | 232, 322, 323 e 332 |\n","| **Em risco** | gastaram bastante dinheiro e compraram com frequência, mas já há bastante tempo. Precisam retornar à base de clientes | 333, 334, 343 e 433 |\n","| **Não pode perder** | fizeram compras grandes e frequentes, mas não voltaram por muito tempo | 243, 344, 434, 443 e 444 |\n","| **Hibernando** | a última compra foi há muito tempo. Gastam pouco e fazem poucos pedidos | 311, 312, 321, 412, 421 e 422 |\n","| **Perdidos** | a menor recência, frequência e valor monetário entre todos | 411 |"]},{"cell_type":"code","execution_count":42,"id":"11a3b943","metadata":{"_cell_guid":"6cd01d5f-761b-44fe-a1e1-6c728087c019","_uuid":"b1ad2f91-75bd-4bae-a234-c35b0fbb3edc","collapsed":true,"execution":{"iopub.execute_input":"2023-02-26T23:21:15.488762Z","iopub.status.busy":"2023-02-26T23:21:15.488392Z","iopub.status.idle":"2023-02-26T23:21:15.877563Z","shell.execute_reply":"2023-02-26T23:21:15.876095Z"},"jupyter":{"outputs_hidden":true,"source_hidden":true},"papermill":{"duration":0.425348,"end_time":"2023-02-26T23:21:15.879988","exception":false,"start_time":"2023-02-26T23:21:15.45464","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:77: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"]}],"source":["# Criando dicionário para facilitar a categorização no Dataframe\n","categorias_dict = {'144':'Campeões',\n","              '133':'Clientes Fiéis',\n","              '134':'Clientes Fiéis',\n","              '143':'Clientes Fiéis',\n","              '234':'Clientes Fiéis',\n","              '243':'Clientes Fiéis',\n","              '244':'Clientes Fiéis',\n","              '123':'Fiéis em Potencial',\n","              '213':'Fiéis em Potencial',\n","              '214':'Fiéis em Potencial',\n","              '223':'Fiéis em Potencial', \n","              '224':'Fiéis em Potencial', \n","              '233':'Fiéis em Potencial',             \n","              '111':'Novos Clientes',\n","              '112':'Novos Clientes', \n","              '113':'Novos Clientes',\n","              '114':'Novos Clientes',              \n","              '124':'Novos Clientes',             \n","              '121':'Promessas',\n","              '211':'Promessas',\n","              '122':'Promessas',\n","              '212':'Promessas',\n","              '221':'Promessas', \n","              '222':'Promessas',              \n","              '131':'Promessas',\n","              '132':'Promessas',\n","              '141':'Promessas',\n","              '142':'Promessas',\n","              '231':'Promessas',              \n","              '334':'Clientes Precisando de Atenção', \n","              '333':'Clientes Precisando de Atenção',           \n","              '344':'Clientes Precisando de Atenção',\n","              '423':'Clientes Precisando de Atenção',\n","              '432':'Quase Dormentes',\n","              '232':'Quase Dormentes',\n","              '313':'Quase Dormentes',\n","              '314':'Quase Dormentes',\n","              '331':'Quase Dormentes',\n","              '332':'Quase Dormentes',\n","              '322':'Quase Dormentes',\n","              '323':'Quase Dormentes',\n","              '342':'Quase Dormentes',\n","              '343':'Quase Dormentes',              \n","              '333':'Em Risco',\n","              '334':'Em Risco',\n","              '343':'Em Risco',\n","              '433':'Em Risco', \n","              '243':'Não Pode Perder',\n","              '324':'Não Pode Perder',\n","              '344':'Não Pode Perder',\n","              '443':'Não Pode Perder',\n","              '434':'Não Pode Perder',\n","              '444':'Não Pode Perder',             \n","              '311':'Hibernando',\n","              '312':'Hibernando',             \n","              '321':'Hibernando',              \n","              '413':'Hibernando',\n","              '414':'Hibernando',\n","              '412':'Hibernando',\n","              '421':'Hibernando',\n","              '422':'Hibernando',\n","              '424':'Hibernando',\n","              '431':'Hibernando',\n","              '441':'Hibernando',\n","              '442':'Hibernando',\n","              '411':'Perdidos'              \n","}   \n","\n","# Criando coluna \"Categoria\" que irá salvar a classificação\n","df_rfm['Categoria'] = ''\n","\n","# atribuindo a classificação para o cliente\n","for i in df_rfm.index:\n","    if df_rfm['RFM'][i] in categorias_dict:\n","        item = df_rfm['RFM'][i]\n","        df_rfm['Categoria'][i] = categorias_dict[item]"]},{"cell_type":"code","execution_count":43,"id":"6d3053bc","metadata":{"_cell_guid":"85485ae0-7b62-4d21-ad84-5f6b61afa90e","_uuid":"7555b7e1-cdae-4120-ba81-441f82a851b8","execution":{"iopub.execute_input":"2023-02-26T23:21:15.944561Z","iopub.status.busy":"2023-02-26T23:21:15.944116Z","iopub.status.idle":"2023-02-26T23:21:16.17656Z","shell.execute_reply":"2023-02-26T23:21:16.174849Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.267809,"end_time":"2023-02-26T23:21:16.179255","exception":false,"start_time":"2023-02-26T23:21:15.911446","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 1296x720 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# calculando a quantidade de clientes em cada categoria\n","df_categorias = df_rfm.groupby(['Categoria'], as_index=False)['RFM'].count()\n","df_categorias.rename(columns={'RFM':'Quantidade'}, inplace=True)\n","\n","# definindo uma paleta de cores\n","colors = [\n","'#6D214F', #mangenta purple\n","'#FC427B', #sasquatch socks\n","'#FD7272', #georgia peach\n","'#F97F51', #rich gardenia\n","'#25CCF7', #spiro disco ball\n","'#EAB543', #honey glow\n","'#55E6C1', #sweet garden\n","'#58B19F', #keppel\n","'#D6A2E8', #bright ubbe\n","'#82589F', #highlighter lavender\n","'#CAD3C8', #falling star\n","'#BDC581', #pine glade\n","'#F8EFBA', #sarawak white pepper\n","]\n","\n","# criando gráfico de segmentacao\n","fig, ax = plt.subplots(figsize=(18,10))\n","squarify.plot(sizes=df_categorias['Quantidade'],\n","              label=df_categorias['Categoria'],\n","              color=colors,\n","              pad=True,\n","              alpha=0.6,\n","              text_kwargs={'fontsize': 14})\n","\n","# Adicionando um título\n","plt.title('Segmentação dos Clientes',\n","          fontsize=24,\n","          fontweight=\"bold\")\n","\n","# Removendo os eixos\n","plt.axis('off')\n","\n","# Ajustando o gráfico\n","plt.tight_layout()\n","\n","plt.show()"]},{"cell_type":"markdown","id":"73a39423","metadata":{"_cell_guid":"d42eed32-dac9-4ee9-98fb-5e4b5f2fbbc2","_uuid":"2e96ddec-05d0-47b5-933b-58caf7fde50f","papermill":{"duration":0.033026,"end_time":"2023-02-26T23:21:16.245193","exception":false,"start_time":"2023-02-26T23:21:16.212167","status":"completed"},"tags":[]},"source":["## Segmentação de Clientes por Categorias"]},{"cell_type":"code","execution_count":44,"id":"97b77e48","metadata":{"_cell_guid":"6122451c-a994-41c7-ac26-ad0a3f984627","_uuid":"23e8fef3-5ec2-4eab-b46d-f54a7e5b9277","execution":{"iopub.execute_input":"2023-02-26T23:21:16.312311Z","iopub.status.busy":"2023-02-26T23:21:16.311282Z","iopub.status.idle":"2023-02-26T23:21:16.550189Z","shell.execute_reply":"2023-02-26T23:21:16.549307Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.274502,"end_time":"2023-02-26T23:21:16.552047","exception":false,"start_time":"2023-02-26T23:21:16.277545","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Text(0, 0.5, 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size 1440x576 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# selecionando o valor mínimo dos 3 maiores Montantes totais de vendas\n","minimo = min(df_categorias['Quantidade'].nlargest(n=5))\n","\n","# colorindo de azul os 3 maiores e colorindo de cinza o restante\n","clrs = [cinza if (x < minimo) else rosa for x in df_categorias['Quantidade']]\n","\n","# criando o gráfico de barras\n","sns.set_theme(style=\"white\", palette=None)\n","plt.figure(figsize = (20,8))\n","ax = sns.barplot(y=\"Categoria\",\n","                 x=\"Quantidade\",\n","                 data=df_categorias,\n","                 ci=False,\n","                 palette=clrs)\n","\n","ax.set_title('Segmentação de Clientes por Categorias')\n","ax.set_xlabel('', fontsize=14, labelpad=10)\n","ax.set_ylabel('Quantidade', fontsize=14, labelpad=10)"]},{"cell_type":"markdown","id":"a4406db4","metadata":{"_cell_guid":"ba7bd969-9f8d-4cf5-95eb-59a5f7b9161b","_uuid":"55a14821-a950-481e-b982-d3afbf0fe44b","papermill":{"duration":0.032281,"end_time":"2023-02-26T23:21:16.616639","exception":false,"start_time":"2023-02-26T23:21:16.584358","status":"completed"},"tags":[]},"source":["Os cinco maiores segmentos são: **Hibernando**, **Clientes Fiéis**, **Promessas**, **Campeões** e **Quase Dormentes**."]},{"cell_type":"code","execution_count":45,"id":"abda2898","metadata":{"_cell_guid":"3bd35e28-beb1-4ae9-b372-58284bae63ab","_uuid":"a5a4e1a3-bb9a-46af-86b5-f917fe075f93","execution":{"iopub.execute_input":"2023-02-26T23:21:16.686856Z","iopub.status.busy":"2023-02-26T23:21:16.685592Z","iopub.status.idle":"2023-02-26T23:21:17.661328Z","shell.execute_reply":"2023-02-26T23:21:17.660098Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":1.013746,"end_time":"2023-02-26T23:21:17.663844","exception":false,"start_time":"2023-02-26T23:21:16.650098","status":"completed"},"tags":[]},"outputs":[{"data":{"text/html":["        <script type=\"text/javascript\">\n","        window.PlotlyConfig = {MathJaxConfig: 'local'};\n","        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n","        if (typeof require !== 'undefined') {\n","        require.undef(\"plotly\");\n","        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de Vendas\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Categoria\"}},\"legend\":{\"tracegroupgap\":0},\"title\":{\"text\":\"Total de Vendas por Categoria\"},\"barmode\":\"relative\"},                        {\"responsive\": true}                    ).then(function(){\n","                            \n","var gd = document.getElementById('6fd643df-ab64-4896-b1b9-7820863754aa');\n","var x = new MutationObserver(function (mutations, observer) {{\n","        var display = window.getComputedStyle(gd).display;\n","        if (!display || display === 'none') {{\n","            console.log([gd, 'removed!']);\n","            Plotly.purge(gd);\n","            observer.disconnect();\n","        }}\n","}});\n","\n","// Listen for the removal of the full notebook cells\n","var notebookContainer = gd.closest('#notebook-container');\n","if (notebookContainer) {{\n","    x.observe(notebookContainer, {childList: true});\n","}}\n","\n","// Listen for the clearing of the 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px.colors.qualitative.Light24[16]])\n","fig.show()"]},{"cell_type":"code","execution_count":47,"id":"fbbf7c0d","metadata":{"_cell_guid":"4e666cf3-9279-45db-867d-f6603518c26a","_uuid":"666ff2a7-6a92-41e0-b642-ac4717035a08","execution":{"iopub.execute_input":"2023-02-26T23:21:17.86245Z","iopub.status.busy":"2023-02-26T23:21:17.861935Z","iopub.status.idle":"2023-02-26T23:21:17.866405Z","shell.execute_reply":"2023-02-26T23:21:17.865651Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.041784,"end_time":"2023-02-26T23:21:17.86847","exception":false,"start_time":"2023-02-26T23:21:17.826686","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Total de Vendas:  8935746.67\n"]}],"source":["print('Total de Vendas: ', montante['Total de Vendas'].sum())"]},{"cell_type":"code","execution_count":48,"id":"c9520e0d","metadata":{"_cell_guid":"b71b34ab-4a72-40b9-9c52-2c0b9c5a4aa4","_uuid":"b87dd9e2-ed68-4b9f-9bf2-2aca1740bcfb","execution":{"iopub.execute_input":"2023-02-26T23:21:17.937085Z","iopub.status.busy":"2023-02-26T23:21:17.936761Z","iopub.status.idle":"2023-02-26T23:21:17.943817Z","shell.execute_reply":"2023-02-26T23:21:17.94243Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.043409,"end_time":"2023-02-26T23:21:17.945719","exception":false,"start_time":"2023-02-26T23:21:17.90231","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["O faturamento da categoria Campeão:  4369518.38\n","O faturamento das outras categorias:  4566228.29\n","Percentual:  0.488993090490109\n"]}],"source":["clientes_campeoes = montante['Total de Vendas'][0]\n","print(\"O faturamento da categoria Campeão: \",clientes_campeoes)\n","print(\"O faturamento das outras categorias: \",montante['Total de Vendas'].sum()-clientes_campeoes)\n","print(\"Percentual: \",clientes_campeoes/montante['Total de Vendas'].sum())"]},{"cell_type":"code","execution_count":49,"id":"4d450ba5","metadata":{"_cell_guid":"696bf21d-e4e2-4c8c-9b36-892cb7436d9d","_uuid":"43cdd519-2c11-4917-8ea4-136f3b7246ef","execution":{"iopub.execute_input":"2023-02-26T23:21:18.015096Z","iopub.status.busy":"2023-02-26T23:21:18.014716Z","iopub.status.idle":"2023-02-26T23:21:18.020555Z","shell.execute_reply":"2023-02-26T23:21:18.019905Z"},"jupyter":{"source_hidden":true},"papermill":{"duration":0.042341,"end_time":"2023-02-26T23:21:18.022713","exception":false,"start_time":"2023-02-26T23:21:17.980372","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["O faturamento da categoria Clientes Fiéis:  1876815.57\n","Percentual:  0.21003455439275565\n"]}],"source":["clientes_fieis = montante['Total de Vendas'][1]\n","print(\"O faturamento da categoria Clientes Fiéis: \",clientes_fieis)\n","print(\"Percentual: \",clientes_fieis/(montante['Total de Vendas'].sum()))"]},{"cell_type":"markdown","id":"1cd55e92","metadata":{"_cell_guid":"7886e20c-4847-4e4d-ba89-9f2cbfc12efe","_uuid":"b913ba04-5d89-494b-be95-09ba814967e1","papermill":{"duration":0.03377,"end_time":"2023-02-26T23:21:18.090025","exception":false,"start_time":"2023-02-26T23:21:18.056255","status":"completed"},"tags":[]},"source":["<a id='recomendacoes'></a>\n","# <font color=\"#ff009e\"> Recomendações a UK Merch </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","* Considerando o Princípio de Pareto que diz que precisamos concentrar nossos esforços em <font color=\"#ff009e\"><strong>20% das atividades que geram 80% de retorno</strong></font>, então devemos avaliar quais segmentos dos clientes que causam mais retorno a UK Merch.\n","* A categoria **Campeões gerou £4.369.518,38** e isso representa **48,90% do faturamento total** que é de £8.935.746,67. \n","* Apenas **461 clientes** estão classificados como Campeões, representando em torno de **10,60% da quantidade total de clientes**.\n","* A segunda maior categoria em faturamento é **Clientes Fiéis** e **gerou £1.876.815,57**, o que dá **21% do faturamento**. Ela possui **612 clientes** ou **14,08%** dos clientes totais.\n","\n","<div class=\"alert alert-success\"> \n","<strong><div style=\"color: rgb(0, 0, 0);\">💡 O que fazer?</div></strong> <br>\n","     <div style=\"color: rgb(0, 0, 0);\">  → Podemos concluir que <strong>principais esforços devam ser concentrados</strong> nos clientes classificados como <strong>Campeões</strong>, pois apenas <mark><strong>10,60% dos clientes</strong></mark> foi responsável por <strong><mark>gerar quase 50% do faturamento</mark></strong>.</div>         \n","     <div style=\"color: rgb(0, 0, 0);\">  → Os esforços empregados na segunda maior categoria precisam ser bem avaliados, pois o seu faturamento é baixo se comparado ao faturamento da categoria Campeões.</div>\n","    <div style=\"color: rgb(0, 0, 0);\">  → Também podemos reforçar que a análise de <strong>retenção de clientes por coorte</strong> possui melhor desempenho para clientes que <strong>moram no Reino Unido e indico que esses clientes sejam priorizados</strong>.</div>\n","</div>\n","\n"]},{"cell_type":"markdown","id":"22aca120","metadata":{"_cell_guid":"3f234ae9-dc42-4e07-9860-3d9c47a4a789","_uuid":"af45ae78-f9ab-4a3e-93de-f1816b0a10f2","papermill":{"duration":0.033845,"end_time":"2023-02-26T23:21:18.158151","exception":false,"start_time":"2023-02-26T23:21:18.124306","status":"completed"},"tags":[]},"source":["## <font color=\"#ff009e\"> Recomendações adicionais para cada categoria de cliente </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","As recomendações de ações indicadas pela [Putler](https://www.putler.com/rfm-analysis/) a serem adotadas para cada categoria de clientes podem ser resumidas principalmente em:\n","\n","| Categoria | Recomendação | \n","|--- |--- |\n","| **Campeões** | Recompense-os. Os campeões podem ser _early adopters_ de novos produtos e promoverão a marca. |\n","| **Clientes fiéis** | Ofereça produtos de maior valor. Peça por reviews nos produtos e faça o possível para engajá-los. | \n","| **Fiéis em potencial** | Ofereça programas de membros ou de lealdade, além de recomendar outros produtos. |\n","| **Novos clientes** | Dê todo o suporte que precisam no onboarding, de modo que o sucesso seja atingido mais rapidamente. Comece a construir um relacionamento. |\n","| **Promessas** | Crie _awareness_ para a sua marca e ofereça testes ou avaliações gratuitas. |\n","| **Clientes precisando de atenção** | Ofereça ofertas por tempo limitado, recomendadas de acordo com compras anteriores. Assim, eles podem ser reativados. |\n","| **Quase dormentes** | Compartilhe recursos valiosos, recomende produtos ou renovações populares com desconto e reconecte-se com eles. |\n","| **Em risco** | Envie e-mails personalizados para se reconectar com eles. Ofereça renovações e proporcione recursos úteis. |\n","| **Não pode perder** | Conquiste-os novamente por meio de renovações ou de novos produtos. Converse com eles para evitar que reforcem a concorrência. |\n","| **Hibernando** | Ofereça outros produtos relevantes e descontos especiais. Assim, torna-se possível recriar o valor da marca para tais clientes. |\n","| **Perdidos** | Tente reviver seu interesse com campanhas. Se não funcionar, ignore. |"]},{"cell_type":"markdown","id":"5ae29cd7","metadata":{"_cell_guid":"31dcb74a-0c66-415b-a6dd-ca6d1a7d824a","_uuid":"0e4f72c6-668e-4ce5-85d5-385906b1084b","papermill":{"duration":0.03325,"end_time":"2023-02-26T23:21:18.22497","exception":false,"start_time":"2023-02-26T23:21:18.19172","status":"completed"},"tags":[]},"source":["<a id='referencias'></a>\n","# <font color=\"#ff009e\"> Referências importantes para o desenvolvimento deste projeto </font>\n","<hr color=\"#F5F5F5\" size=\"1\">\n","\n","[Como fazer Análise Cohort e por que ela é importante para PMs](https://www.cursospm3.com.br/blog/como-fazer-analise-cohort-e-por-que-ela-e-importante-para-pms/)\n","\n","[Como fazer: Análise Cohort com Google Colab, Pandas e Seaborn em 5 passos](https://dataholds.com/como-fazer-analise-cohort-com-google-colab-pandas-e-seaborn-em-5-passos/)\n","\n","[RFM Analysis For Sucessful Customer Segmentation](https://www.putler.com/rfm-analysis/)\n","\n","[A análise RFM para segmentação de clientes](https://vidadeproduto.com.br/analise-rfm/)\n","\n","[Introduction to Customer Segmentation in Python](https://www.datacamp.com/tutorial/introduction-customer-segmentation-python)"]}],"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":"3.7.12"},"papermill":{"default_parameters":{},"duration":25.943947,"end_time":"2023-02-26T23:21:19.179107","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2023-02-26T23:20:53.23516","version":"2.3.4"}},"nbformat":4,"nbformat_minor":5}