code: def safely_drop_columns(df, cols_to_drop):
      safe_cols_to_drop = []
      for col in cols_to_drop:
          if col in df.columns:
              safe_cols_to_drop.append(col)
  
      df.drop(safe_cols_to_drop, 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 4 for calling a global function with example usage: safely_drop_columns(df, cols_to_drop) and returns: df