class_docstr: Calculates the trend of a column over time.
  
  Description:
      Given a list of values and a corresponding list of
      datetimes, calculate the slope of the linear trend
      of values.
  
  Examples:
      >>> from datetime import datetime
      >>> trend = Trend()
      >>> times = [datetime(2010, 1, 1, 11, 45, 0),
      ...          datetime(2010, 1, 1, 11, 55, 15),
      ...          datetime(2010, 1, 1, 11, 57, 30),
      ...          datetime(2010, 1, 1, 11, 12),
      ...          datetime(2010, 1, 1, 11, 12, 15)]
      >>> round(trend([1, 2, 3, 4, 5], times), 3)
      -0.053
code: def get_function(self, agg_type=Library.PANDAS):
      def pd_trend(y, x):
          return calculate_trend(
              pd.Series(data=y.values, index=x.values)
          )
  
      return pd_trend
  
file_path: featuretools/featuretools/primitives/standard/aggregation/trend.py
imports: import pandas
  from woodwork.column_schema import ColumnSchema
  from woodwork.logical_types import Datetime
  from featuretools.primitives.base.aggregation_primitive_base import AggregationPrimitive
  from featuretools.utils import calculate_trend
  from featuretools.utils.gen_utils import Library
label_desc: Use image node_id 1 for calling the Trend obj's underlying member method code with example usage: obj.get_function(agg_type) and returns: pd_trend, calculate_trend