original_docstring: Prepares target features (i.e., labels) from California housing data set.
  
    Args:
      california_housing_dataframe: A Pandas DataFrame expected to contain data
        from the California housing data set.
    Returns:
      A DataFrame that contains the target feature.
    
docstring: Prepares target features  from California housing data set.
docstring_tokens: Prepares target features from California housing data set .
code: def preprocess_targets(california_housing_dataframe):
    """Prepares target features (i.e., labels) from California housing data set.
  
    Args:
      california_housing_dataframe: A Pandas DataFrame expected to contain data
        from the California housing data set.
    Returns:
      A DataFrame that contains the target feature.
    """
    output_targets = pd.DataFrame()
    # Scale the target to be in units of thousands of dollars.
    output_targets["median_house_value"] = (
      california_housing_dataframe["median_house_value"] / 1000.0)
    return output_targets
code_tokens: def preprocess_targets ( california_housing_dataframe ) : output_targets = pd . DataFrame ( ) output_targets [ "median_house_value" ] = ( california_housing_dataframe [ "median_house_value" ] / 1000.0 ) return output_targets
short_docstring: Prepares target features (i.e., labels) from California housing data set.
short_docstring_tokens: Prepares target features ( i . e . labels ) from California housing data set .
comment: """Prepares target features (i.e., labels) from California housing data set.
  
    Args:
      california_housing_dataframe: A Pandas DataFrame expected to contain data
        from the California housing data set.
    Returns:
      A DataFrame that contains the target feature.
    """$SEP$# Scale the target to be in units of thousands of dollars.