@@ -1074,12 +1074,12 @@ def seasonality_from_temperature_timeseries(
10741074 dbt .drop ((2 , 29 ), axis = 0 , inplace = True )
10751075 except KeyError :
10761076 pass
1077- dbt .index = pd .date_range ("2017-01-01 00:00:00" , freq = "60T " , periods = 8760 )
1077+ dbt .index = pd .date_range ("2017-01-01 00:00:00" , freq = "60min " , periods = 8760 )
10781078 dbt .name = "dbt"
10791079
10801080 # prepare a 3-year dataset using the aggregate year from the input data and drop leap days if included
10811081 dbt_3year = pd .Series (
1082- index = pd .date_range ("2016-01-01 00:00:00" , freq = "60T " , periods = len (dbt ) * 3 ),
1082+ index = pd .date_range ("2016-01-01 00:00:00" , freq = "60min " , periods = len (dbt ) * 3 ),
10831083 data = np .array ([[i ] * 3 for i in dbt .values ]).T .flatten (),
10841084 )
10851085
@@ -1709,7 +1709,7 @@ def longest_day(epw: EPW) -> datetime:
17091709 The longest day in the year associated with this epw object."""
17101710
17111711 sunpath = Sunpath .from_location (epw .location )
1712- idx = pd .date_range ("2017-01-01 00:00:00" , "2018-01-01 00:00:00" , freq = "1T " )
1712+ idx = pd .date_range ("2017-01-01 00:00:00" , "2018-01-01 00:00:00" , freq = "1min " )
17131713 suns = [sunpath .calculate_sun_from_date_time (i ) for i in idx ][:- 1 ]
17141714
17151715 s = pd .Series ([i .altitude for i in suns ], index = idx [:- 1 ])
@@ -1722,7 +1722,7 @@ def shortest_day(epw: EPW) -> datetime:
17221722 The shortest day in the year associated with this epw object."""
17231723
17241724 sunpath = Sunpath .from_location (epw .location )
1725- idx = pd .date_range ("2017-01-01 00:00:00" , "2018-01-01 00:00:00" , freq = "1T " )
1725+ idx = pd .date_range ("2017-01-01 00:00:00" , "2018-01-01 00:00:00" , freq = "1min " )
17261726 suns = [sunpath .calculate_sun_from_date_time (i ) for i in idx ][:- 1 ]
17271727
17281728 s = pd .Series ([i .altitude for i in suns ], index = idx [:- 1 ])
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