text: import numpy as np
  import pandas as pd
  
  def check_for_nulls(input_dataframe, null_value=np.NaN, form='string'):
      """
      Checks the passed dataframe for null values.
      Changing the form parameter allows for different return types
  
      Parameters:
      input_dataframe (pd.DataFrame): The dataframe to be checked for null values
      null_value (object): 
      form (string): The form type of the return
          options:
          'boolean': returns true or false if the dataframe contains a null value
          'string': returns a string output of "(#) null values in dataframe"
          'series': returns a series of (index, column) which are null values
          'dataframe': returns a copy of the dataframe where null values are True,
              while all other values are false
  
      Return:
      returns the null information in the format specified by the parameter 'form'
      """
      if(form== 'boolean'):
          if(input_dataframe.isnull().any()):
              return True
          else:
              return False
      elif(form== 'string'):
          return ('{} null values in dataframe'.format(input_dataframe.isnull().sum()))
      elif(form== 'series'):
          nulls = []
  
          for y in input_dataframe.columns:
              for x in input_dataframe.index:
                  a = input_dataframe.at[x,y]
                  if(a == null_value or a == None):
                      nulls.append([x,y])
          return nulls
      elif(form== 'dataframe'):
          input_dataframe.applymap(lambda x : np.NaN if x == null_value else x)
          return input_dataframe.isnull()
  
  def split_dates(input_date):
      """
      Given a string in the format of "MM/DD/YYYY", will split into three compnents
  
      Parameters:
      input_date (string): string in the form of "MM/DD/YYYY"
  
      Return:
      returns a list of [MM, DD, YYYY]
      """
      return input_date.split(sep='/')
  
  def make_giraffe(x):
      return 'Giraffed'
  