Adds documentation showing scalar creation & input

Functions can create or take in scalars. Adding this to the
example so that people can see that more explicitly.

examples/hello_world/my_functions.py

@@ -9,3 +9,13 @@ def avg_3wk_spend(spend: pd.Series) -> pd.Series:
 def spend_per_signup(spend: pd.Series, signups: pd.Series) -> pd.Series:
     """The cost per signup in relation to spend."""
     return spend / signups
+
+
+def single_avg(spend: pd.Series) -> float:
+    """Shows function creating a scalar."""
+    return spend.mean()
+
+
+def spend_per_signup_time_average(single_avg: float, spend_per_signup: pd.Series) -> pd.Series:
+    """Shows a function that takes in a scalar."""
+    return single_avg * spend_per_signup

examples/hello_world/my_script.py

@@ -8,6 +8,7 @@
 logger = logging.getLogger(__name__)
 logging.basicConfig(stream=sys.stdout)
 initial_columns = {  # load from actuals or wherever -- this is our initial data we use as input.
+    # Note: these values don't have to be all series, they could be a scalar.
     'signups': pd.Series([1, 10, 50, 100, 200, 400]),
     'spend': pd.Series([10, 10, 20, 40, 40, 50]),
 }
@@ -21,6 +22,7 @@
     'signups',
     'avg_3wk_spend',
     'spend_per_signup',
+    'spend_per_signup_time_average'
 ]
 # let's create the dataframe!
 df = dr.execute(output_columns, display_graph=True)