code: def create_joined_df(gdf, everdf, **kwargs):
      chronometer = Chronometer.makeStarted()
      tables = {"perf": gdf, "everdf": everdf}
  
      query = """
          SELECT perf.loan_id as loan_id,
              perf.monthly_reporting_period as mrp_timestamp,
              EXTRACT(MONTH FROM perf.monthly_reporting_period)
                  as timestamp_month,
              EXTRACT(YEAR FROM perf.monthly_reporting_period)
                  as timestamp_year,
              perf.current_loan_delinquency_status as delinquency_12,
              perf.current_actual_upb as upb_12,
              everdf.ever_30 as ever_30,
              everdf.ever_90 as ever_90,
              everdf.ever_180 as ever_180,
              everdf.delinquency_30 as delinquency_30,
              everdf.delinquency_90 as delinquency_90,
              everdf.delinquency_180 as delinquency_180
          FROM main.perf as perf
          LEFT OUTER JOIN main.everdf as everdf
          ON perf.loan_id = everdf.loan_id
      """
  
      results = pyblazing.run_query(query, tables)
  
      results.columns["upb_12"] = results.columns["upb_12"].fillna(
          999999999
      )
      results.columns["delinquency_12"] = results.columns[
          "delinquency_12"
      ].fillna(-1)
      results.columns["ever_30"] = results.columns["ever_30"].fillna(-1)
      results.columns["ever_90"] = results.columns["ever_90"].fillna(-1)
      results.columns["ever_180"] = results.columns["ever_180"].fillna(
          -1
      )
      results.columns["delinquency_30"] = results.columns[
          "delinquency_30"
      ].fillna(-1)
      results.columns["delinquency_90"] = results.columns[
          "delinquency_90"
      ].fillna(-1)
      results.columns["delinquency_180"] = results.columns[
          "delinquency_180"
      ].fillna(-1)
  
      Chronometer.show(chronometer, "Create Joined DF")
      return results
  
imports: import time
  from collections import OrderedDict
  import numpy
  import pandas
  import pyblazing
  from pyblazing import DriverType, FileSystemType, SchemaFrom, get_dtype_values
  from sklearn.model_selection import train_test_split
  import xgboost
  from Configuration import Settings
  from DemoTest.chronometer import Chronometer
  from Utils import Execution
label_desc: Use image node_id 15 for calling a global function with example usage: create_joined_df(gdf, everdf) and returns: results