endava-payments-hackathon-quick-starter.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/gpreda/endava-payments-hackathon-quick-starter?scriptVersionId=126252190\" 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"},{"cell_type":"markdown","id":"6554ee6c","metadata":{"papermill":{"duration":0.008818,"end_time":"2023-04-18T09:51:30.307925","exception":false,"start_time":"2023-04-18T09:51:30.299107","status":"completed"},"tags":[]},"source":[" <h1>Endava Payments Hackathon Quick Starter</h1>\n"," <h2>Connect to a Google Cloud account, create a BigQuery client, run queries, perform preliminary analysis</h2>\n"," \n"," This Kernel demonstrates the following:  \n"," - How to connect to a Google Cloud account;  \n"," - Initialize a BigQuery client;  \n"," - Get the tables list;  \n"," - Run queries to import BigQuery tables;  \n"," - Convert the tables to dataframes;  \n"," - Perform preliminary data evaluation using pandas profiling.\n"," "]},{"cell_type":"markdown","id":"bce65330","metadata":{"papermill":{"duration":0.006749,"end_time":"2023-04-18T09:51:30.321698","exception":false,"start_time":"2023-04-18T09:51:30.314949","status":"completed"},"tags":[]},"source":["### Big Query Connector"]},{"cell_type":"code","execution_count":1,"id":"2aa84fe5","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:30.339655Z","iopub.status.busy":"2023-04-18T09:51:30.337985Z","iopub.status.idle":"2023-04-18T09:51:30.355947Z","shell.execute_reply":"2023-04-18T09:51:30.354547Z"},"papermill":{"duration":0.031327,"end_time":"2023-04-18T09:51:30.359838","exception":false,"start_time":"2023-04-18T09:51:30.328511","status":"completed"},"tags":[]},"outputs":[],"source":["from google.cloud import bigquery"]},{"cell_type":"markdown","id":"73628b9b","metadata":{"papermill":{"duration":0.007186,"end_time":"2023-04-18T09:51:30.375036","exception":false,"start_time":"2023-04-18T09:51:30.36785","status":"completed"},"tags":[]},"source":["### Connect to the project/dataset"]},{"cell_type":"code","execution_count":2,"id":"1cfa9ef8","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2023-04-18T09:51:30.392669Z","iopub.status.busy":"2023-04-18T09:51:30.392207Z","iopub.status.idle":"2023-04-18T09:51:30.39886Z","shell.execute_reply":"2023-04-18T09:51:30.397359Z"},"papermill":{"duration":0.019086,"end_time":"2023-04-18T09:51:30.401391","exception":false,"start_time":"2023-04-18T09:51:30.382305","status":"completed"},"tags":[]},"outputs":[],"source":["bigquery_client = bigquery.Client(project='endava-hackathon')\n","dataset_ref = bigquery_client.dataset(\"payments_tx\")"]},{"cell_type":"markdown","id":"9e9aec17","metadata":{"papermill":{"duration":0.006388,"end_time":"2023-04-18T09:51:30.414695","exception":false,"start_time":"2023-04-18T09:51:30.408307","status":"completed"},"tags":[]},"source":["## Set configuration"]},{"cell_type":"code","execution_count":3,"id":"0fdec395","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:30.43087Z","iopub.status.busy":"2023-04-18T09:51:30.429776Z","iopub.status.idle":"2023-04-18T09:51:30.44092Z","shell.execute_reply":"2023-04-18T09:51:30.43968Z"},"papermill":{"duration":0.021787,"end_time":"2023-04-18T09:51:30.443546","exception":false,"start_time":"2023-04-18T09:51:30.421759","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["{'debug': True,\n"," 'train_sample': 0.05,\n"," 'project': 'endava-hackathon',\n"," 'database': 'endava-hackathon',\n"," 'dataset': 'payments_tx'}"]},"execution_count":3,"metadata":{},"output_type":"execute_result"}],"source":["config = {\n","    'debug': True,\n","    'train_sample': 0.05,\n","    'project': 'endava-hackathon',\n","    'database': 'endava-hackathon',\n","    'dataset': 'payments_tx'\n","}\n","\n","config"]},{"cell_type":"markdown","id":"67440c49","metadata":{"papermill":{"duration":0.00653,"end_time":"2023-04-18T09:51:30.458599","exception":false,"start_time":"2023-04-18T09:51:30.452069","status":"completed"},"tags":[]},"source":["### Get the tables list"]},{"cell_type":"code","execution_count":4,"id":"d284d3af","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:30.475982Z","iopub.status.busy":"2023-04-18T09:51:30.474711Z","iopub.status.idle":"2023-04-18T09:51:31.178817Z","shell.execute_reply":"2023-04-18T09:51:31.177517Z"},"papermill":{"duration":0.715578,"end_time":"2023-04-18T09:51:31.181609","exception":false,"start_time":"2023-04-18T09:51:30.466031","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["customers\n","merchants\n","terminals\n","transactions_complete\n","transactions_train\n"]}],"source":["tables = list(bigquery_client.list_tables(dataset_ref))\n","\n","# Print names of all tables in the dataset (there are four!)\n","for table in tables:  \n","    print(table.table_id)"]},{"cell_type":"markdown","id":"685e4d27","metadata":{"papermill":{"duration":0.006773,"end_time":"2023-04-18T09:51:31.195564","exception":false,"start_time":"2023-04-18T09:51:31.188791","status":"completed"},"tags":[]},"source":["### Run a simple query\n","\n","\n","Get the shape of tables: \n","- customers  \n","- merchants  \n","- terminals  \n","- transaction_train  "]},{"cell_type":"code","execution_count":5,"id":"44c2d78d","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:31.212208Z","iopub.status.busy":"2023-04-18T09:51:31.210994Z","iopub.status.idle":"2023-04-18T09:51:32.257026Z","shell.execute_reply":"2023-04-18T09:51:32.255632Z"},"papermill":{"duration":1.057177,"end_time":"2023-04-18T09:51:32.259802","exception":false,"start_time":"2023-04-18T09:51:31.202625","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/google/cloud/bigquery/client.py:440: UserWarning: Cannot create BigQuery Storage client, the dependency google-cloud-bigquery-storage is not installed.\n","  \"Cannot create BigQuery Storage client, the dependency \"\n"]},{"name":"stdout","output_type":"stream","text":["Customers: 50000 rows.\n"]}],"source":["query = f\"\"\"SELECT COUNT(*) FROM `{config['database']}.{config['dataset']}.customers`\"\"\"\n","query_job = bigquery_client.query(query)\n","print(f\"Customers: {query_job.to_dataframe().values[0][0]} rows.\")"]},{"cell_type":"code","execution_count":6,"id":"d6514c49","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:32.27762Z","iopub.status.busy":"2023-04-18T09:51:32.27623Z","iopub.status.idle":"2023-04-18T09:51:33.213202Z","shell.execute_reply":"2023-04-18T09:51:33.211765Z"},"papermill":{"duration":0.948992,"end_time":"2023-04-18T09:51:33.215896","exception":false,"start_time":"2023-04-18T09:51:32.266904","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Merchants: 30452 rows.\n"]}],"source":["query = f\"\"\"SELECT COUNT(*) FROM `{config['database']}.{config['dataset']}.merchants`\"\"\"\n","query_job = bigquery_client.query(query)\n","print(f\"Merchants: {query_job.to_dataframe().values[0][0]} rows.\")"]},{"cell_type":"code","execution_count":7,"id":"ba2998e9","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:33.232539Z","iopub.status.busy":"2023-04-18T09:51:33.232099Z","iopub.status.idle":"2023-04-18T09:51:34.203978Z","shell.execute_reply":"2023-04-18T09:51:34.202558Z"},"papermill":{"duration":0.983585,"end_time":"2023-04-18T09:51:34.207022","exception":false,"start_time":"2023-04-18T09:51:33.223437","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Terminals: 5000 rows.\n"]}],"source":["query = f\"\"\"SELECT COUNT(*) FROM `{config['database']}.{config['dataset']}.terminals`\"\"\"\n","query_job = bigquery_client.query(query)\n","print(f\"Terminals: {query_job.to_dataframe().values[0][0]} rows.\")"]},{"cell_type":"code","execution_count":8,"id":"67206d05","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:34.224329Z","iopub.status.busy":"2023-04-18T09:51:34.22386Z","iopub.status.idle":"2023-04-18T09:51:35.353386Z","shell.execute_reply":"2023-04-18T09:51:35.352429Z"},"papermill":{"duration":1.140843,"end_time":"2023-04-18T09:51:35.356018","exception":false,"start_time":"2023-04-18T09:51:34.215175","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Transaction_train: 3393443 rows.\n"]}],"source":["query = f\"\"\"SELECT COUNT(*) FROM `{config['database']}.{config['dataset']}.transactions_train`\"\"\"\n","query_job = bigquery_client.query(query)\n","print(f\"Transaction_train: {query_job.to_dataframe().values[0][0]} rows.\")\n","\n","transaction_train_full_shape = int(query_job.to_dataframe().values[0][0])"]},{"cell_type":"markdown","id":"b0f7f9db","metadata":{"papermill":{"duration":0.008523,"end_time":"2023-04-18T09:51:35.372355","exception":false,"start_time":"2023-04-18T09:51:35.363832","status":"completed"},"tags":[]},"source":["## Run queries to read tables\n","\n","\n","We read the tables and convert the tables to pandas dataframes."]},{"cell_type":"code","execution_count":9,"id":"57ad47cf","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:35.389399Z","iopub.status.busy":"2023-04-18T09:51:35.388652Z","iopub.status.idle":"2023-04-18T09:51:45.246574Z","shell.execute_reply":"2023-04-18T09:51:45.245421Z"},"papermill":{"duration":9.870086,"end_time":"2023-04-18T09:51:45.249809","exception":false,"start_time":"2023-04-18T09:51:35.379723","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Query executed in: 9.83 sec. for 50000 rows, 3 cols.\n"]},{"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>CUSTOMER_ID</th>\n","      <th>x_customer_id</th>\n","      <th>y_customer_id</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>9146778701554837</td>\n","      <td>80.845748</td>\n","      <td>58.465662</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>5298159883488498</td>\n","      <td>56.205709</td>\n","      <td>83.090319</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1001491422509859</td>\n","      <td>21.440831</td>\n","      <td>41.026478</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>6293111408475835</td>\n","      <td>31.060315</td>\n","      <td>6.606118</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>5558521274211537</td>\n","      <td>75.896886</td>\n","      <td>81.742451</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        CUSTOMER_ID  x_customer_id  y_customer_id\n","0  9146778701554837      80.845748      58.465662\n","1  5298159883488498      56.205709      83.090319\n","2  1001491422509859      21.440831      41.026478\n","3  6293111408475835      31.060315       6.606118\n","4  5558521274211537      75.896886      81.742451"]},"execution_count":9,"metadata":{},"output_type":"execute_result"}],"source":["import time\n","start_time = time.time()\n","\n","query = f\"\"\"SELECT * FROM `{config['database']}.{config['dataset']}.customers`\"\"\"\n","query_job = bigquery_client.query(query)\n","customers_df = query_job.to_dataframe()\n","print(f\"Query executed in: {round(time.time() - start_time, 2)} sec. for {customers_df.shape[0]} rows, {customers_df.shape[1]} cols.\")\n","\n","customers_df.head()"]},{"cell_type":"code","execution_count":10,"id":"bb4cf3b7","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:51:45.267487Z","iopub.status.busy":"2023-04-18T09:51:45.266953Z","iopub.status.idle":"2023-04-18T09:52:05.759009Z","shell.execute_reply":"2023-04-18T09:52:05.757115Z"},"papermill":{"duration":20.504554,"end_time":"2023-04-18T09:52:05.762379","exception":false,"start_time":"2023-04-18T09:51:45.257825","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/google/cloud/bigquery/client.py:440: UserWarning: Cannot create BigQuery Storage client, the dependency google-cloud-bigquery-storage is not installed.\n","  \"Cannot create BigQuery Storage client, the dependency \"\n"]},{"name":"stdout","output_type":"stream","text":["Query executed in: 20.46 sec. for 30452 rows, 24 cols.\n"]},{"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>MERCHANT_ID</th>\n","      <th>BUSINESS_TYPE</th>\n","      <th>MCC_CODE</th>\n","      <th>LEGAL_NAME</th>\n","      <th>FOUNDATION_DATE</th>\n","      <th>TAX_EXCEMPT_INDICATOR</th>\n","      <th>VAT_NUMBER</th>\n","      <th>TRADING_NAME</th>\n","      <th>NICK_NAME</th>\n","      <th>OUTLET_TYPE</th>\n","      <th>...</th>\n","      <th>AVERAGE_TICKET_SALE_AMOUNT</th>\n","      <th>PAYMENT_PERCENTAGE_FACE_TO_FACE</th>\n","      <th>PAYMENT_PERCENTAGE_ECOM</th>\n","      <th>PAYMENT_PERCENTAGE_MOTO</th>\n","      <th>DEPOSIT_REQUIRED_PERCENTAGE</th>\n","      <th>DEPOSIT_PERCENTAGE</th>\n","      <th>DELIVERY_SAME_DAYS_PERCENTAGE</th>\n","      <th>DELIVERY_WEEK_ONE_PERCENTAGE</th>\n","      <th>DELIVERY_WEEK_TWO_PERCENTAGE</th>\n","      <th>DELIVERY_OVER_TWO_WEEKS_PERCENTAGE</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>f3bb3b06-7f40-4fab-9936-4293a68d18cf</td>\n","      <td>Limited Liability Company (LLC)</td>\n","      <td>5921</td>\n","      <td>a0755c</td>\n","      <td>2015-02-06</td>\n","      <td>False</td>\n","      <td>dbdb8a81-07f6-4257-bfa1-eaa9bb80135a</td>\n","      <td>a0755c</td>\n","      <td>a0755c</td>\n","      <td>Face to face</td>\n","      <td>...</td>\n","      <td>104</td>\n","      <td>14</td>\n","      <td>57</td>\n","      <td>29</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>29</td>\n","      <td>25</td>\n","      <td>26</td>\n","      <td>20</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>487bdf4e-2104-4797-a8bf-d1ff90e8d7be</td>\n","      <td>Corporations</td>\n","      <td>4789</td>\n","      <td>ab7ce2</td>\n","      <td>2021-12-02</td>\n","      <td>False</td>\n","      <td>bc595505-1fdc-4c71-9221-630096f6d9f9</td>\n","      <td>ab7ce2</td>\n","      <td>ab7ce2</td>\n","      <td>Ecommerce</td>\n","      <td>...</td>\n","      <td>201</td>\n","      <td>27</td>\n","      <td>59</td>\n","      <td>14</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>24</td>\n","      <td>25</td>\n","      <td>22</td>\n","      <td>29</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>5bb2f64b-525b-459a-8102-4aa31aca45f5</td>\n","      <td>Sole Proprietorships</td>\n","      <td>1750</td>\n","      <td>deaecb</td>\n","      <td>2016-09-02</td>\n","      <td>False</td>\n","      <td>f11b2cd7-43f0-4977-8912-d605c0156678</td>\n","      <td>deaecb</td>\n","      <td>deaecb</td>\n","      <td>Ecommerce</td>\n","      <td>...</td>\n","      <td>92</td>\n","      <td>28</td>\n","      <td>43</td>\n","      <td>29</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>23</td>\n","      <td>20</td>\n","      <td>21</td>\n","      <td>36</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>c4790465-b17a-4ab5-a39a-81c0857151a7</td>\n","      <td>S Corporations</td>\n","      <td>8062</td>\n","      <td>c2a2cd</td>\n","      <td>2010-10-21</td>\n","      <td>False</td>\n","      <td>e1833cde-8354-4b8b-8a59-aaca5ce701b3</td>\n","      <td>c2a2cd</td>\n","      <td>c2a2cd</td>\n","      <td>Face to face and ecommerce</td>\n","      <td>...</td>\n","      <td>157</td>\n","      <td>29</td>\n","      <td>62</td>\n","      <td>9</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>26</td>\n","      <td>28</td>\n","      <td>26</td>\n","      <td>20</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>d993e7d0-8daa-4618-9a01-45cea3c4a263</td>\n","      <td>Limited Liability Company (LLC)</td>\n","      <td>5969</td>\n","      <td>6b50c6</td>\n","      <td>2013-04-27</td>\n","      <td>False</td>\n","      <td>4b9b6673-5ad0-4876-bc21-d2357815e0a8</td>\n","      <td>6b50c6</td>\n","      <td>6b50c6</td>\n","      <td>Face to face</td>\n","      <td>...</td>\n","      <td>210</td>\n","      <td>30</td>\n","      <td>55</td>\n","      <td>15</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>20</td>\n","      <td>24</td>\n","      <td>25</td>\n","      <td>31</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 24 columns</p>\n","</div>"],"text/plain":["                            MERCHANT_ID                    BUSINESS_TYPE  \\\n","0  f3bb3b06-7f40-4fab-9936-4293a68d18cf  Limited Liability Company (LLC)   \n","1  487bdf4e-2104-4797-a8bf-d1ff90e8d7be                     Corporations   \n","2  5bb2f64b-525b-459a-8102-4aa31aca45f5             Sole Proprietorships   \n","3  c4790465-b17a-4ab5-a39a-81c0857151a7                   S Corporations   \n","4  d993e7d0-8daa-4618-9a01-45cea3c4a263  Limited Liability Company (LLC)   \n","\n","   MCC_CODE LEGAL_NAME FOUNDATION_DATE  TAX_EXCEMPT_INDICATOR  \\\n","0      5921     a0755c      2015-02-06                  False   \n","1      4789     ab7ce2      2021-12-02                  False   \n","2      1750     deaecb      2016-09-02                  False   \n","3      8062     c2a2cd      2010-10-21                  False   \n","4      5969     6b50c6      2013-04-27                  False   \n","\n","                             VAT_NUMBER TRADING_NAME NICK_NAME  \\\n","0  dbdb8a81-07f6-4257-bfa1-eaa9bb80135a       a0755c    a0755c   \n","1  bc595505-1fdc-4c71-9221-630096f6d9f9       ab7ce2    ab7ce2   \n","2  f11b2cd7-43f0-4977-8912-d605c0156678       deaecb    deaecb   \n","3  e1833cde-8354-4b8b-8a59-aaca5ce701b3       c2a2cd    c2a2cd   \n","4  4b9b6673-5ad0-4876-bc21-d2357815e0a8       6b50c6    6b50c6   \n","\n","                  OUTLET_TYPE  ... AVERAGE_TICKET_SALE_AMOUNT  \\\n","0                Face to face  ...                        104   \n","1                   Ecommerce  ...                        201   \n","2                   Ecommerce  ...                         92   \n","3  Face to face and ecommerce  ...                        157   \n","4                Face to face  ...                        210   \n","\n","  PAYMENT_PERCENTAGE_FACE_TO_FACE  PAYMENT_PERCENTAGE_ECOM  \\\n","0                              14                       57   \n","1                              27                       59   \n","2                              28                       43   \n","3                              29                       62   \n","4                              30                       55   \n","\n","   PAYMENT_PERCENTAGE_MOTO  DEPOSIT_REQUIRED_PERCENTAGE  DEPOSIT_PERCENTAGE  \\\n","0                       29                            0                   0   \n","1                       14                            0                   0   \n","2                       29                            0                   0   \n","3                        9                            0                   0   \n","4                       15                            0                   0   \n","\n","   DELIVERY_SAME_DAYS_PERCENTAGE  DELIVERY_WEEK_ONE_PERCENTAGE  \\\n","0                             29                            25   \n","1                             24                            25   \n","2                             23                            20   \n","3                             26                            28   \n","4                             20                            24   \n","\n","   DELIVERY_WEEK_TWO_PERCENTAGE  DELIVERY_OVER_TWO_WEEKS_PERCENTAGE  \n","0                            26                                  20  \n","1                            22                                  29  \n","2                            21                                  36  \n","3                            26                                  20  \n","4                            25                                  31  \n","\n","[5 rows x 24 columns]"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["start_time = time.time()\n","query = f\"\"\"SELECT * FROM `{config['database']}.{config['dataset']}.merchants`\"\"\"\n","query_job = bigquery_client.query(query)\n","merchants_df = query_job.to_dataframe()\n","print(f\"Query executed in: {round(time.time() - start_time, 2)} sec. for {merchants_df.shape[0]} rows, {merchants_df.shape[1]} cols.\")\n","merchants_df.head()"]},{"cell_type":"code","execution_count":11,"id":"e7225e5f","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:52:05.780981Z","iopub.status.busy":"2023-04-18T09:52:05.780557Z","iopub.status.idle":"2023-04-18T09:52:07.322915Z","shell.execute_reply":"2023-04-18T09:52:07.32164Z"},"papermill":{"duration":1.554359,"end_time":"2023-04-18T09:52:07.325399","exception":false,"start_time":"2023-04-18T09:52:05.77104","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/google/cloud/bigquery/client.py:440: UserWarning: Cannot create BigQuery Storage client, the dependency google-cloud-bigquery-storage is not installed.\n","  \"Cannot create BigQuery Storage client, the dependency \"\n"]},{"name":"stdout","output_type":"stream","text":["Query executed in: 1.53 sec. for 5000 rows, 3 cols.\n"]},{"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>TERMINAL_ID</th>\n","      <th>x_terminal_id</th>\n","      <th>y_terminal__id</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>09754224</td>\n","      <td>41.536730</td>\n","      <td>68.889911</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>37467861</td>\n","      <td>61.864075</td>\n","      <td>20.882662</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>20678215</td>\n","      <td>70.530677</td>\n","      <td>36.567633</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>12724021</td>\n","      <td>92.961874</td>\n","      <td>66.721471</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>02989793</td>\n","      <td>38.756717</td>\n","      <td>68.669003</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  TERMINAL_ID  x_terminal_id  y_terminal__id\n","0    09754224      41.536730       68.889911\n","1    37467861      61.864075       20.882662\n","2    20678215      70.530677       36.567633\n","3    12724021      92.961874       66.721471\n","4    02989793      38.756717       68.669003"]},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":["start_time = time.time()\n","query = f\"\"\"SELECT * FROM `{config['database']}.{config['dataset']}.terminals`\"\"\"\n","query_job = bigquery_client.query(query)\n","terminals_df = query_job.to_dataframe()\n","print(f\"Query executed in: {round(time.time() - start_time, 2)} sec. for {terminals_df.shape[0]} rows, {terminals_df.shape[1]} cols.\")\n","terminals_df.head()"]},{"cell_type":"code","execution_count":12,"id":"0179041a","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:52:07.34459Z","iopub.status.busy":"2023-04-18T09:52:07.344146Z","iopub.status.idle":"2023-04-18T09:53:50.712429Z","shell.execute_reply":"2023-04-18T09:53:50.711208Z"},"papermill":{"duration":103.389822,"end_time":"2023-04-18T09:53:50.723963","exception":false,"start_time":"2023-04-18T09:52:07.334141","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/google/cloud/bigquery/client.py:440: UserWarning: Cannot create BigQuery Storage client, the dependency google-cloud-bigquery-storage is not installed.\n","  \"Cannot create BigQuery Storage client, the dependency \"\n"]},{"name":"stdout","output_type":"stream","text":["Query executed in: 103.33 sec. for 169672 rows, 21 cols.\n"]},{"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>TX_ID</th>\n","      <th>TX_TS</th>\n","      <th>CUSTOMER_ID</th>\n","      <th>TERMINAL_ID</th>\n","      <th>TX_AMOUNT</th>\n","      <th>TX_FRAUD</th>\n","      <th>TRANSACTION_GOODS_AND_SERVICES_AMOUNT</th>\n","      <th>TRANSACTION_CASHBACK_AMOUNT</th>\n","      <th>CARD_EXPIRY_DATE</th>\n","      <th>CARD_DATA</th>\n","      <th>...</th>\n","      <th>TRANSACTION_TYPE</th>\n","      <th>TRANSACTION_STATUS</th>\n","      <th>FAILURE_CODE</th>\n","      <th>FAILURE_REASON</th>\n","      <th>TRANSACTION_CURRENCY</th>\n","      <th>CARD_COUNTRY_CODE</th>\n","      <th>MERCHANT_ID</th>\n","      <th>IS_RECURRING_TRANSACTION</th>\n","      <th>ACQUIRER_ID</th>\n","      <th>CARDHOLDER_AUTH_METHOD</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>b2bdb0d29b07925078ee975a823985924bab3c53</td>\n","      <td>2021-04-27 14:51:44+00:00</td>\n","      <td>8959186642301557</td>\n","      <td>58419023</td>\n","      <td>2.060000000</td>\n","      <td>0</td>\n","      <td>2.060000000</td>\n","      <td>0E-9</td>\n","      <td>11/21</td>\n","      <td>6011********131</td>\n","      <td>...</td>\n","      <td>Purchase</td>\n","      <td>Settled</td>\n","      <td>None</td>\n","      <td>None</td>\n","      <td>AED</td>\n","      <td>US</td>\n","      <td>e7f13b95-4efb-495d-b278-dc0bfb4501bd</td>\n","      <td>False</td>\n","      <td>ACQ3</td>\n","      <td>Offline enciphered PIN</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>311607316558f3fa3e85e5ade7f957f4b7fe9f32</td>\n","      <td>2021-06-11 18:09:17+00:00</td>\n","      <td>5810787734627040</td>\n","      <td>36528632</td>\n","      <td>1.840000000</td>\n","      <td>0</td>\n","      <td>1.840000000</td>\n","      <td>0E-9</td>\n","      <td>04/23</td>\n","      <td>3742********727</td>\n","      <td>...</td>\n","      <td>Purchase</td>\n","      <td>Settled</td>\n","      <td>None</td>\n","      <td>None</td>\n","      <td>AED</td>\n","      <td>US</td>\n","      <td>138316ab-d5f1-41d2-b444-3c4819a03c2f</td>\n","      <td>False</td>\n","      <td>ACQ2</td>\n","      <td>Offline plaintext PIN and signature</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1eac6cc663ce5cc76d12507b9b187c45a69cef2b</td>\n","      <td>2021-03-13 22:41:48+00:00</td>\n","      <td>9744656952071047</td>\n","      <td>42211721</td>\n","      <td>0.840000000</td>\n","      <td>0</td>\n","      <td>0.840000000</td>\n","      <td>0E-9</td>\n","      <td>02/23</td>\n","      <td>4716********928</td>\n","      <td>...</td>\n","      <td>Purchase</td>\n","      <td>Settled</td>\n","      <td>None</td>\n","      <td>None</td>\n","      <td>AED</td>\n","      <td>US</td>\n","      <td>09ec7a7d-d420-4013-96aa-1d9af66a2bf0</td>\n","      <td>False</td>\n","      <td>ACQ3</td>\n","      <td>Online PIN</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>095b2806b98cb0d963ca70c83064798b2288e6f4</td>\n","      <td>2021-10-21 14:03:57+00:00</td>\n","      <td>5052466705246430</td>\n","      <td>17142994</td>\n","      <td>2.120000000</td>\n","      <td>0</td>\n","      <td>2.120000000</td>\n","      <td>0E-9</td>\n","      <td>04/22</td>\n","      <td>5337********179</td>\n","      <td>...</td>\n","      <td>Purchase</td>\n","      <td>Settled</td>\n","      <td>None</td>\n","      <td>None</td>\n","      <td>AED</td>\n","      <td>US</td>\n","      <td>dbb60596-966d-4bd4-ba71-eec99232bb82</td>\n","      <td>False</td>\n","      <td>ACQ2</td>\n","      <td>Online PIN</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>5371770143f2336eaa3acf4cb11a2a68784da4b7</td>\n","      <td>2021-11-17 15:08:24+00:00</td>\n","      <td>8395937513329700</td>\n","      <td>15873857</td>\n","      <td>0.760000000</td>\n","      <td>0</td>\n","      <td>0.760000000</td>\n","      <td>0E-9</td>\n","      <td>10/22</td>\n","      <td>5337********185</td>\n","      <td>...</td>\n","      <td>Purchase</td>\n","      <td>Settled</td>\n","      <td>None</td>\n","      <td>None</td>\n","      <td>AED</td>\n","      <td>US</td>\n","      <td>f79a1501-3583-4fb3-91b6-c1d2ee1013a5</td>\n","      <td>False</td>\n","      <td>ACQ3</td>\n","      <td>No CVM performed</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 21 columns</p>\n","</div>"],"text/plain":["                                      TX_ID                     TX_TS  \\\n","0  b2bdb0d29b07925078ee975a823985924bab3c53 2021-04-27 14:51:44+00:00   \n","1  311607316558f3fa3e85e5ade7f957f4b7fe9f32 2021-06-11 18:09:17+00:00   \n","2  1eac6cc663ce5cc76d12507b9b187c45a69cef2b 2021-03-13 22:41:48+00:00   \n","3  095b2806b98cb0d963ca70c83064798b2288e6f4 2021-10-21 14:03:57+00:00   \n","4  5371770143f2336eaa3acf4cb11a2a68784da4b7 2021-11-17 15:08:24+00:00   \n","\n","        CUSTOMER_ID TERMINAL_ID    TX_AMOUNT  TX_FRAUD  \\\n","0  8959186642301557    58419023  2.060000000         0   \n","1  5810787734627040    36528632  1.840000000         0   \n","2  9744656952071047    42211721  0.840000000         0   \n","3  5052466705246430    17142994  2.120000000         0   \n","4  8395937513329700    15873857  0.760000000         0   \n","\n","  TRANSACTION_GOODS_AND_SERVICES_AMOUNT TRANSACTION_CASHBACK_AMOUNT  \\\n","0                           2.060000000                        0E-9   \n","1                           1.840000000                        0E-9   \n","2                           0.840000000                        0E-9   \n","3                           2.120000000                        0E-9   \n","4                           0.760000000                        0E-9   \n","\n","  CARD_EXPIRY_DATE        CARD_DATA  ... TRANSACTION_TYPE TRANSACTION_STATUS  \\\n","0            11/21  6011********131  ...         Purchase            Settled   \n","1            04/23  3742********727  ...         Purchase            Settled   \n","2            02/23  4716********928  ...         Purchase            Settled   \n","3            04/22  5337********179  ...         Purchase            Settled   \n","4            10/22  5337********185  ...         Purchase            Settled   \n","\n","  FAILURE_CODE FAILURE_REASON TRANSACTION_CURRENCY CARD_COUNTRY_CODE  \\\n","0         None           None                  AED                US   \n","1         None           None                  AED                US   \n","2         None           None                  AED                US   \n","3         None           None                  AED                US   \n","4         None           None                  AED                US   \n","\n","                            MERCHANT_ID IS_RECURRING_TRANSACTION  ACQUIRER_ID  \\\n","0  e7f13b95-4efb-495d-b278-dc0bfb4501bd                    False         ACQ3   \n","1  138316ab-d5f1-41d2-b444-3c4819a03c2f                    False         ACQ2   \n","2  09ec7a7d-d420-4013-96aa-1d9af66a2bf0                    False         ACQ3   \n","3  dbb60596-966d-4bd4-ba71-eec99232bb82                    False         ACQ2   \n","4  f79a1501-3583-4fb3-91b6-c1d2ee1013a5                    False         ACQ3   \n","\n","                CARDHOLDER_AUTH_METHOD  \n","0               Offline enciphered PIN  \n","1  Offline plaintext PIN and signature  \n","2                           Online PIN  \n","3                           Online PIN  \n","4                     No CVM performed  \n","\n","[5 rows x 21 columns]"]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["if config[\"debug\"]:\n","    query = f\"\"\"SELECT * FROM `{config['database']}.{config['dataset']}.transactions_train` LIMIT {int(config['train_sample'] * transaction_train_full_shape)}\"\"\"\n","else:\n","    query = f\"\"\"SELECT * FROM `{config['database']}.{config['dataset']}.transactions_train`\"\"\"\n","start_time = time.time()    \n","query_job = bigquery_client.query(query)\n","transactions_train_df = query_job.to_dataframe()\n","print(f\"Query executed in: {round(time.time() - start_time, 2)} sec. for {transactions_train_df.shape[0]} rows, {transactions_train_df.shape[1]} cols.\")\n","transactions_train_df.head()"]},{"cell_type":"markdown","id":"c19a3aa9","metadata":{"papermill":{"duration":0.008632,"end_time":"2023-04-18T09:53:50.741428","exception":false,"start_time":"2023-04-18T09:53:50.732796","status":"completed"},"tags":[]},"source":["### Query to get columns list"]},{"cell_type":"markdown","id":"0bb89fd0","metadata":{"papermill":{"duration":0.009007,"end_time":"2023-04-18T09:53:50.75922","exception":false,"start_time":"2023-04-18T09:53:50.750213","status":"completed"},"tags":[]},"source":["Get the columns names for `merchants` table."]},{"cell_type":"code","execution_count":13,"id":"f4ab097e","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:53:50.77874Z","iopub.status.busy":"2023-04-18T09:53:50.778322Z","iopub.status.idle":"2023-04-18T09:53:51.910976Z","shell.execute_reply":"2023-04-18T09:53:51.909592Z"},"papermill":{"duration":1.145885,"end_time":"2023-04-18T09:53:51.914008","exception":false,"start_time":"2023-04-18T09:53:50.768123","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.7/site-packages/google/cloud/bigquery/client.py:440: UserWarning: Cannot create BigQuery Storage client, the dependency google-cloud-bigquery-storage is not installed.\n","  \"Cannot create BigQuery Storage client, the dependency \"\n"]},{"name":"stdout","output_type":"stream","text":["Columns in `merchants` table: ['MERCHANT_ID' 'BUSINESS_TYPE' 'MCC_CODE' 'LEGAL_NAME' 'FOUNDATION_DATE'\n"," 'TAX_EXCEMPT_INDICATOR' 'VAT_NUMBER' 'TRADING_NAME' 'NICK_NAME'\n"," 'OUTLET_TYPE' 'ACTIVE_FROM' 'TRADING_FROM' 'ANNUAL_TURNOVER_CARD'\n"," 'ANNUAL_TURNOVER' 'AVERAGE_TICKET_SALE_AMOUNT'\n"," 'PAYMENT_PERCENTAGE_FACE_TO_FACE' 'PAYMENT_PERCENTAGE_ECOM'\n"," 'PAYMENT_PERCENTAGE_MOTO' 'DEPOSIT_REQUIRED_PERCENTAGE'\n"," 'DEPOSIT_PERCENTAGE' 'DELIVERY_SAME_DAYS_PERCENTAGE'\n"," 'DELIVERY_WEEK_ONE_PERCENTAGE' 'DELIVERY_WEEK_TWO_PERCENTAGE'\n"," 'DELIVERY_OVER_TWO_WEEKS_PERCENTAGE']\n"]}],"source":["query = f\"\"\"SELECT column_name FROM `{config['database']}.{config['dataset']}.INFORMATION_SCHEMA.COLUMNS` \\\n","    WHERE table_name = 'merchants'\"\"\"\n","\n","query_job = bigquery_client.query(query)\n","query_df = query_job.to_dataframe()\n","print(f\"Columns in `merchants` table: {query_df.column_name.values}\")"]},{"cell_type":"markdown","id":"34b2cd58","metadata":{"papermill":{"duration":0.008777,"end_time":"2023-04-18T09:53:51.931881","exception":false,"start_time":"2023-04-18T09:53:51.923104","status":"completed"},"tags":[]},"source":["Get the columns names for terminals table."]},{"cell_type":"code","execution_count":14,"id":"744db50e","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:53:51.953329Z","iopub.status.busy":"2023-04-18T09:53:51.952062Z","iopub.status.idle":"2023-04-18T09:53:53.009599Z","shell.execute_reply":"2023-04-18T09:53:53.008576Z"},"papermill":{"duration":1.071109,"end_time":"2023-04-18T09:53:53.011994","exception":false,"start_time":"2023-04-18T09:53:51.940885","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Columns in `terminals` table: ['TERMINAL_ID' 'x_terminal_id' 'y_terminal__id']\n"]}],"source":["query = f\"\"\"SELECT column_name FROM `{config['database']}.{config['dataset']}.INFORMATION_SCHEMA.COLUMNS` \\\n","    WHERE table_name = 'terminals'\"\"\"\n","\n","query_job = bigquery_client.query(query)\n","query_df = query_job.to_dataframe()\n","print(f\"Columns in `terminals` table: {query_df.column_name.values}\")"]},{"cell_type":"markdown","id":"f8451728","metadata":{"papermill":{"duration":0.008539,"end_time":"2023-04-18T09:53:53.029875","exception":false,"start_time":"2023-04-18T09:53:53.021336","status":"completed"},"tags":[]},"source":["## Data profiling using pandas_profiling\n","\n","We use the option to run a minimal analysis."]},{"cell_type":"code","execution_count":15,"id":"75de0907","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:53:53.049956Z","iopub.status.busy":"2023-04-18T09:53:53.049311Z","iopub.status.idle":"2023-04-18T09:53:56.270322Z","shell.execute_reply":"2023-04-18T09:53:56.269212Z"},"papermill":{"duration":3.234104,"end_time":"2023-04-18T09:53:56.27286","exception":false,"start_time":"2023-04-18T09:53:53.038756","status":"completed"},"tags":[]},"outputs":[],"source":["from pandas_profiling import ProfileReport"]},{"cell_type":"code","execution_count":16,"id":"3076c55a","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:53:56.294015Z","iopub.status.busy":"2023-04-18T09:53:56.293376Z","iopub.status.idle":"2023-04-18T09:53:58.434069Z","shell.execute_reply":"2023-04-18T09:53:58.432561Z"},"papermill":{"duration":2.159099,"end_time":"2023-04-18T09:53:58.441461","exception":false,"start_time":"2023-04-18T09:53:56.282362","status":"completed"},"tags":[]},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"6c7da7a0a5e34d3d9a0eb3b9006f82b8","version_major":2,"version_minor":0},"text/plain":["Summarize dataset:   0%|          | 0/5 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"38402966c80f4c399ffa0d1981a2e1ba","version_major":2,"version_minor":0},"text/plain":["Generate report structure:   0%|          | 0/1 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"0e7da77ddff54335a085a9417f073cfd","version_major":2,"version_minor":0},"text/plain":["Render HTML:   0%|          | 0/1 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"fd21e10b719f4b869190b85d02c0e8c9","version_major":2,"version_minor":0},"text/plain":["Export report to file:   0%|          | 0/1 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"}],"source":["profile = ProfileReport(customers_df, minimal=True)\n","profile.to_file(output_file=\"customers_profile.html\")"]},{"cell_type":"code","execution_count":17,"id":"196434b7","metadata":{"execution":{"iopub.execute_input":"2023-04-18T09:53:58.463078Z","iopub.status.busy":"2023-04-18T09:53:58.462607Z","iopub.status.idle":"2023-04-18T09:54:05.654871Z","shell.execute_reply":"2023-04-18T09:54:05.653623Z"},"papermill":{"duration":7.21262,"end_time":"2023-04-18T09:54:05.664024","exception":false,"start_time":"2023-04-18T09:53:58.451404","status":"completed"},"tags":[]},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"c383a5a2aed14d35941c43f17dd9ac72","version_major":2,"version_minor":0},"text/plain":["Summarize dataset:   0%|          | 0/5 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"1cc761a2628b4f04ba446a05dd0ed823","version_major":2,"version_minor":0},"text/plain":["Generate report structure:   0%|          | 0/1 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