code: def drop_duplicate_columns(df):
      count_cols_to_drop = 0
      cols = list(df.columns)
      for idx, item in enumerate(df.columns):
          if item in df.columns[:idx]:
              print(
                  "#####################################################"
              )
              print(
                  "We found a duplicate column, and will be removing it"
              )
              print(
                  "If you intended to send in two different pieces of information, please make sure they have different column names"
              )
              print("Here is the duplicate column:")
              print(item)
              print(
                  "#####################################################"
              )
              cols[idx] = "DROPME"
              count_cols_to_drop += 1
  
      if count_cols_to_drop > 0:
          df.columns = cols
  
          df.drop("DROPME", axis=1, inplace=True)
      return df
  
imports: import csv
  import datetime
  import numbers
  import os
  import pkg_resources
  import numpy
  import pandas
  import scipy
  from sklearn.datasets import load_boston
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import LabelEncoder
  from sklearn.utils.metaestimators import if_delegate_has_method
  from sklearn.utils import column_or_1d
  from auto_ml._version import __version__
label_desc: Use image node_id 5 for calling a global function with example usage: drop_duplicate_columns(df) and returns: df