Switched to internally use a series instead of a data frame.

toarstats/input_checks.py

@@ -212,8 +212,7 @@ def check_data(data_in, datetimes_in, values_in):
                             null values
                           - the index and values have different lengths
 
-    :return: A data frame with a datetime index and a column of float or
-             int values
+    :return: A series with a datetime index and float or int values
     """
     if data_in is not None:
         if isinstance(data_in, (pd.DataFrame, pd.Series)):
@@ -230,7 +229,7 @@ def check_data(data_in, datetimes_in, values_in):
         raise ValueError("Datetime index and values must have the same length")
     if index_out.tz:
         index_out = index_out.tz_localize(None)
-    return pd.DataFrame({"values": values_out}, index=index_out)
+    return pd.Series(values_out, index_out)
 
 
 def is_in_range(parameter, min_valid, max_valid):

toarstats/interface.py

@@ -9,7 +9,7 @@ import pandas as pd
 from toarstats import stats, ozone_metrics
 from toarstats.defaults import DEFAULT_CROPS, DEFAULT_DATA_CAPTURE
 from toarstats.input_checks import check_input_parameters
-from toarstats.stats_utils import (create_reference_data_frame, get_seasons,
+from toarstats.stats_utils import (create_reference_series, get_seasons,
                                    harmonize_time)
 
 
@@ -124,20 +124,19 @@ def calculate_statistics(
         else DEFAULT_CROPS, input_parameters.required.seasons,
         input_parameters.required.crops
     )
-    reference_data_frame = create_reference_data_frame(
-        input_parameters.data.index
-    )
+    ref = create_reference_series(input_parameters.data.index)
     resample_rule = ("seasonal" if input_parameters.sampling == "vegseason"
                      else input_parameters.sampling)
     data_capture_value = (input_parameters.data_capture
                           if input_parameters.data_capture is not None else 0.5
                           if "diurnal_cycle" in input_parameters.statistics
                           else DEFAULT_DATA_CAPTURE)
+
     results = []
     for i, stat in enumerate(input_parameters.statistics):
         results.extend(
             getattr(stats, stat, getattr(ozone_metrics, stat, None))(
-                input_parameters.data, reference_data_frame, resample_rule,
+                input_parameters.data, ref, resample_rule,
                 input_parameters.metadata, seasons_per_statistic[i],
                 data_capture_value
             )
@@ -146,4 +145,4 @@ def calculate_statistics(
         results, resample_rule,
         "H" if "diurnal_cycle" in input_parameters.statistics else None
     )
-    return pd.DataFrame({res["name"]: res["df"]["values"] for res in results})
+    return pd.DataFrame({res["name"]: res["ser"] for res in results})