text: """This contains the functions for Module 1 assignment. A number of basic helper functions to practice on."""
  
  def null_count(df):
      """Check a dataframe for nulls and return the number of missing values."""
      return df.isnull().sum().sum()
  
  def train_test_split(df, frac):
      """A Train/Test split function for a dataframe that returns both the Training and Testing sets. Frac refers to the percent of data you would like to set aside for Training."""
      df = df.copy()
  
      # Retrieve the length of the dataframe and calculate the length of the 'frac' for Training data (train_length)
      df_length =  len(df)
      train_length = round(df_length * frac, 0)
  
      # Split the dataframe into Train and Test based on the train_length
      df_train = df.iloc[:train_length]
      df_test = df.iloc[train_length:]
  
      return df_train, df_test
  
  def randomize(df):
      """Randomization function that randomizes all of a dataframes cells then returns that randomized dataframe."""
      # TODO - Implement
      return 'randomize'
  
  def addy_split(add_series): 
      """Splits addresses into three columns (df['city'], df['state'], and df['zip'])"""
      # TODO - Implement
      return 'addy_split'
  
  def abbr_2_st(state_series, abbr_2_state=True):
      """Return a new column with the full name from a State abbreviation column -> An input of FL would return Florida. 
      This function should also take a boolean (abbr_2_state) and when False takes full state names and return state abbreviations. 
      -> An input of Florida would return Fl.
      """
      # TODO - Implement
      return 'abbr_2_st'
  
  def list_2_series(list_2_series, df):
      """Single function to take a list and dataframe then turn the list into a series and add it to the inputted dataframe as a new column."""
      # TODO - Implement
      return 'list_2_series'
  
  def rm_outlier(df):
      """A 1.5*Interquartile range outlier detection/removal function that gets rid of outlying rows and returns that outlier cleaned dataframe."""
      # TODO - Implement
      return 'rm_outlier'
  
  def split_dates(date_series):
      """Function to split dates of format "MM/DD/YYYY" into multiple columns (df['month'], df['day'], df['year']) 
      and then return the same dataframe with those additional columns.
      """
      # TODO - Implement
      return 'split_dates'