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Expand file tree Collapse file tree Original file line number Diff line number Diff line change @@ -91,68 +91,6 @@ def stacked_bar_plot(totals):
9191
9292 return fig1 , fig2
9393
94- def get_ioos_regional_data ():
95- e = ERDDAP (
96- server = "https://erddap.ioos.us/erddap" ,
97- protocol = "tabledap" ,
98- )
99-
100- e .response = "csv"
101- e .dataset_id = "gts_regional_statistics"
102-
103- df = e .to_pandas (
104- index_col = "time (UTC)" ,
105- parse_dates = True
106- )
107- return df
108-
109- def get_ioos_regional_yearly_stats ():
110-
111- df = get_ioos_regional_data ()
112-
113- groups = df .groupby ([pd .Grouper (
114- freq = "YE" ,
115- ),'region' ])
116-
117- totals = groups [
118- ["met" , "wave" ]
119- ].sum () # reducing the columns so the summary is digestable
120-
121- #totals = s.assign(total=s["met"] + s["wave"])
122- totals .index = totals .reset_index ().set_index ('time (UTC)' ).index .to_period ('Y' )
123-
124- # Not returning summarized table by year and RA...
125-
126- return totals
127-
128- def get_ioos_regional_stats ():
129-
130- e = ERDDAP (
131- server = "https://erddap.ioos.us/erddap" ,
132- protocol = "tabledap" ,
133- )
134-
135- e .response = "csv"
136- e .dataset_id = "gts_regional_statistics"
137-
138- df = e .to_pandas (
139- index_col = "time (UTC)" ,
140- parse_dates = True
141- )
142-
143- groups = df .groupby (pd .Grouper (
144- freq = "ME" ,
145- ))
146-
147- s = groups [
148- ["met" , "wave" ]
149- ].sum () # reducing the columns so the summary is digestable
150-
151- totals = s .assign (total = s ["met" ] + s ["wave" ])
152- totals .index = totals .index .to_period ("M" )
153-
154- return totals , e
155-
15694def get_ndbc_full_stats ():
15795
15896 e = ERDDAP (
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