code: def upcast_to_float(df):
      for name in df.columns:
          if np.issubdtype(df[name].dtype, np.bool_):
              df[name] = df[name].astype(np.float32)
          elif np.issubdtype(df[name].dtype, np.timedelta64):
              # issue: cannot astype a timedelta from [timedelta64[ns]] to [float64]
              # so first cast from timedelta64[ns] to timedelta64[ms] and after to np.float64
              df[name] = df[name].astype("timedelta64[ms]")
              df[name] = df[name].astype(np.float64)
          elif np.issubdtype(df[name].dtype, np.integer):
              df[name] = df[name].astype(np.float64)
      return df
  
imports: import json
  import logging
  import os
  import re
  import time
  import yaml
  import numpy
  import pandas
  import blazingsql
  from blazingsql import DataType
  from BlazingLogging import loggingHandler
  from Configuration import ExecutionMode
  from Configuration import Settings
  from DataBase import createSchema
label_desc: Use image node_id 3 for calling a global function with example usage: upcast_to_float(df) and returns: df