import intake
import hvplot.pandas
import hvplot.xarray
import cook_inlet_catalogs as cic
import holoviews as hv
CTD Profiles (EcoFOCI): Shelikof Strait¶
CTD Casts taken as part of the EcoFOCI project.
EcoFOCI project page: https://www.ecofoci.noaa.gov/
Data page: https://data.pmel.noaa.gov/pmel/erddap/tabledap/Shelikof_line8_3695_0ada_d066.html
PMEL ERDDAP: https://data.pmel.noaa.gov/pmel/erddap/index.html
cat = intake.open_catalog(cic.utils.cat_path("ctd_profiles_ecofoci"))
Plot all datasets in catalog¶
dd, ddlabels = cic.utils.combine_datasets_for_map(cat)
dd.hvplot(**cat.metadata["map"]) * ddlabels.hvplot(**cat.metadata["maplabels"])
List available datasets in the catalog¶
dataset_ids = list(cat)
dataset_ids
['di853a0062',
'di853a0064',
'di853a0065',
'di853a0066',
'di853a0068',
'di853a0069',
'di853a0070',
'di857a0030',
'di857a0031',
'di857a0032',
'di857a0033',
'di857a0034',
'di857a0035',
'di857a0036',
'dy0808c001',
'dy0808c002',
'dy0808c003',
'dy0808c004',
'dy0808c005',
'dy0808c006',
'dy0808c007',
'dy0808c008',
'dy0808c009',
'dy0808c010',
'dy0808c011',
'dy0808c012',
'dy0808c013',
'dy1204c002',
'dy1204c003',
'dy1204c004',
'dy1204c005',
'dy1204c006',
'dy1204c007',
'dy1204c008',
'fw848a0001',
'fw848a0002',
'fw848a0003',
'fw848a0004',
'fw848a0005',
'fw848a0006',
'fw848a0007',
'fw848a0008',
'fw848a0009',
'fw848a0010',
'fw848a0011',
'fw848a0012',
'gp0101c067',
'gp0101c068',
'gp0101c069',
'gp0201c075',
'gp0201c076',
'gp0201c077',
'la9802c046',
'la9802c047',
'la9802c048',
'mf0008c001',
'mf0008c002',
'mf0008c003',
'mf0105004',
'mf0105005',
'mf0105006',
'mf0105007',
'mf0105008',
'mf0105009',
'mf0201c005',
'mf0201c006',
'mf0201c007',
'mf0201c008',
'mf0201c009',
'mf0201c010',
'mf0201c011',
'mf0207c001',
'mf0207c002',
'mf0207c003',
'mf0207c004',
'mf0207c005',
'mf0207c006',
'mf0303c002',
'mf0309bc013',
'mf0309bc014',
'mf0309bc015',
'mf0309bc016',
'mf0309bc017',
'mf0309bc018',
'mf0309bc019',
'mf0312c004',
'mf0312c005',
'mf0312c006',
'mf0312c007',
'mf0312c008',
'mf0312c009',
'mf0312c010',
'mf0312c011',
'mf0312c012',
'mf0404c025',
'mf0404c026',
'mf0404c027',
'mf0404c029',
'mf0404c030',
'mf0404c031',
'mf0404c032',
'mf0404c033',
'mf0404c034',
'mf0404c035',
'mf0405bc001',
'mf0407c001',
'mf0407c002',
'mf0407c003',
'mf0407c004',
'mf0407c005',
'mf0407c006',
'mf0504c003',
'mf0504c004',
'mf0504c005',
'mf0504c006',
'mf0504c007',
'mf0504c008',
'mf0504c009',
'mf0504c010',
'mf0504c011',
'mf0504c012',
'mf0508c002',
'mf0508c003',
'mf0508c004',
'mf0508c005',
'mf0508c006',
'mf0508c007',
'mf0602c003',
'mf0602c004',
'mf0602c005',
'mf0602c006',
'mf0602c008',
'mf0602c009',
'mf0602c010',
'mf0602c011',
'mf0602c012',
'mf0702c003',
'mf0702c004',
'mf0702c005',
'mf0702c006',
'mf0702c007',
'mf0702c008',
'mf0702c009',
'mf0708c003',
'mf0708c004',
'mf0708c005',
'mf0708c006',
'mf0708c007',
'mf0708c008',
'mf0802bc036',
'mf0802bc037',
'mf0802bc038',
'mf0802bc039',
'mf0802bc040',
'mf0802bc041',
'mf813b0021',
'mf813b0022',
'mf813b0023',
'mf813b0024',
'mf813b0025',
'mf814a0021',
'mf814a0022',
'mf814a0023',
'mf814a0024',
'mf814a0049',
'mf815a0021',
'mf815a0022',
'mf815a0023',
'mf815a0024',
'mf815a0025',
'mf853a0006',
'mf853a0008',
'mf853a0009',
'mf853a0010',
'mf853a0011',
'mf853a0012',
'mf854a0008',
'mf854a0009',
'mf854a0010',
'mf854a0011',
'mf854a0012',
'mf854a0013',
'mf854a0014',
'mf855a0001',
'mf855a0002',
'mf855a0003',
'mf855a0004',
'mf855a0005',
'mf855a0006',
'mf855a0007',
'mf855a0008',
'mf85aa0130',
'mf85aa0131',
'mf85aa0132',
'mf85aa0133',
'mf85aa0134',
'mf85aa0135',
'mf85aa0136',
'mf862a0001',
'mf862a0002',
'mf862a0003',
'mf862a0004',
'mf862a0005',
'mf862a0006',
'mf862a0007',
'mf863a0001',
'mf863a0002',
'mf863a0003',
'mf863a0004',
'mf863a0005',
'mf863a0006',
'mf863a0007',
'mf863a0008',
'mf863a0009',
'mf863a0010',
'mf863a0011',
'mf863a0012',
'mf863a0013',
'mf863a0014',
'mf865a0008',
'mf865a0009',
'mf865a0010',
'mf865a0011',
'mf865a0012',
'mf865a0013',
'mf865a0014',
'mf865a0070',
'mf865a0071',
'mf865a0072',
'mf865a0073',
'mf865a0074',
'mf865a0075',
'mf865a0076',
'mf865a0077',
'mf873a0001',
'mf873a0002',
'mf873a0003',
'mf873a0004',
'mf873a0005',
'mf873a0006',
'mf873a0007',
'mf874a0001',
'mf874a0002',
'mf874a0003',
'mf874a0004',
'mf874a0005',
'mf874a0006',
'mf874a0007',
'mf874a0008',
'mf874a0009',
'mf874a0012',
'mf878a0001',
'mf878a0006',
'mf878a0007',
'mf878a0008',
'mf878a0009',
'mf878a0010',
'mf878a0011',
'mf878a0012',
'mf883a0001',
'mf883a0002',
'mf883a0003',
'mf883a0004',
'mf883a0005',
'mf883a0006',
'mf883a0007',
'mf893a0001',
'mf893a0002',
'mf893a0003',
'mf893a0004',
'mf893a0005',
'mf893a0006',
'mf893a0007',
'mf894a0001',
'mf894a0002',
'mf894a0003',
'mf894a0004',
'mf894a0005',
'mf894a0006',
'mf894a0007',
'mf894b0001',
'mf894b0002',
'mf894b0003',
'mf894b0004',
'mf894b0005',
'mf894b0006',
'mf894b0007',
'mf894b0008',
'mf904z0009',
'mf904z0010',
'mf904z0011',
'mf904z0012',
'mf904z0013',
'mf904z0014',
'mf904z0015',
'mf905a0075',
'mf905a0076',
'mf905a0077',
'mf905a0078',
'mf905a0079',
'mf905a0080',
'mf905a0081',
'mf905a0082',
'mf905b0001',
'mf905b0002',
'mf905b0003',
'mf905b0004',
'mf905b0005',
'mf905b0006',
'mf905b0007',
'mf905b0008',
'mf905c0018',
'mf905c0019',
'mf905c0020',
'mf905c0021',
'mf905c0022',
'mf905c0023',
'mf905c0024',
'mf914a0001',
'mf914a0002',
'mf914a0003',
'mf914a0004',
'mf914a0005',
'mf914a0006',
'mf914a0007',
'mf914a0008',
'mf914a0009',
'mf914a0010',
'mf914a0011',
'mf914a0012',
'mf914a0013',
'mf914a0014',
'mf914a0015',
'mf914a0016',
'mf914a0017',
'mf914b0001',
'mf914b0002',
'mf914b0003',
'mf914b0004',
'mf914b0005',
'mf914b0006',
'mf914b0007',
'mf914b0008',
'mf914b0009',
'mf914b0010',
'mf914b0011',
'mf914b0012',
'mf914b0013',
'mf914b0014',
'mf91aa0001',
'mf91aa0002',
'mf91aa0003',
'mf91aa0004',
'mf91aa0005',
'mf91aa0006',
'mf91aa0007',
'mf91aa0008',
'mf91aa0009',
'mf91aa0010',
'mf92030001',
'mf92030002',
'mf92030003',
'mf92030004',
'mf92030005',
'mf92030006',
'mf92030007',
'mf92030008',
'mf92030009',
'mf92030010',
'mf92030011',
'mf9205001',
'mf9205002',
'mf9205003',
'mf9205004',
'mf9205005',
'mf9205006',
'mf9205007',
'mf9205008',
'mf9205009',
'mf9205010',
'mf9206026',
'mf9206027',
'mf9206028',
'mf9206029',
'mf9206030',
'mf9206031',
'mf9206032',
'mf9304001',
'mf9304004',
'mf9304005',
'mf9304006',
'mf9304007',
'mf9304008',
'mf9304009',
'mf9306034',
'mf9306035',
'mf9306036',
'mf9306037',
'mf9306038',
'mf9306039',
'mf9308003',
'mf9308004',
'mf9308005',
'mf9308006',
'mf9401007',
'mf9401008',
'mf9401009',
'mf9401010',
'mf9403c016',
'mf9403c021',
'mf9403c022',
'mf9403c023',
'mf9403c024',
'mf9403c025',
'mf9403c026',
'mf9403c027',
'mf9403c028',
'mf9404002',
'mf9404003',
'mf9404004',
'mf9405003',
'mf9405004',
'mf9405005',
'mf9405006',
'mf9405007',
'mf9405008',
'mf9405009',
'mf9405010',
'mf9405011',
'mf9405012',
'mf9508c029',
'mf9508c030',
'mf9508c031',
'mf9508c032',
'mf9508c033',
'mf9508c034',
'mf9604c003',
'mf9604c004',
'mf9604c005',
'mf9607c042',
'mf9607c043',
'mf9608c016',
'mf9608c017',
'mf9608c018',
'mf9608c019',
'mf9608c020',
'mf9608c021',
'mf9608c022',
'mf9610c003',
'mf9610c004',
'mf9610c005',
'mf9610c008',
'mf9610c009',
'mf9610c010',
'mf9610c012',
'mf9614c039',
'mf9614c040',
'mf9614c041',
'mf9614c042',
'mf9614c043',
'mf9614c044',
'mf9704c001',
'mf9704c002',
'mf9704c003',
'mf9704c004',
'mf9704c005',
'mf9704c006',
'mf9704c007',
'mf9706c006',
'mf9706c007',
'mf9706c008',
'mf9706c009',
'mf9706c010',
'mf9706c011',
'mf9801c001',
'mf9801c002',
'mf9801c003',
'mf9801c004',
'mf9801c005',
'mf9801c006',
'mf9801c007',
'mf9801c008',
'mf9801c009',
'mf9801c010',
'mf9805ac001',
'mf9805ac002',
'mf9805ac003',
'mf9805ac004',
'mf9805ac006',
'mf9805ac007',
'mf9806c006',
'mf9806c007',
'mf9806c008',
'mf9806c009',
'mf9806c010',
'mf9806c011',
'mf9806c012',
'rb0103a002',
'rb0103a004',
'w9905bc001',
'w9905bc002',
'w9905bc003',
'w9905bc004',
'w9905bc005',
'w9905bc006',
'w9905bc007',
'we9806bc001',
'we9806bc002',
'we9806bc003',
'we9806bc004',
'we9806bc005',
'we9806bc006',
'we9806bc007',
'we9806bc008',
'we9806bc009']
Select one dataset to investigate¶
try:
dataset_id = dataset_ids[2]
except:
dataset_id = dataset_ids[0]
print(dataset_id)
dd = cat[dataset_id].read()
dd
di853a0065
| id | cast | cruise | time (UTC) | longitude (degrees_east) | latitude (degrees_north) | depth (m) | ocean_temperature_1 (Degree_C) | ocean_practical_salinity_1 (PSU) | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 0.0 | 3.07 | NaN |
| 1 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 1.0 | 3.07 | NaN |
| 2 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 2.0 | 3.07 | NaN |
| 3 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 3.0 | 3.07 | NaN |
| 4 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 4.0 | 3.07 | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 228 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 228.0 | 5.79 | NaN |
| 229 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 229.0 | 5.79 | NaN |
| 230 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 230.0 | 5.78 | NaN |
| 231 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 231.0 | 5.78 | NaN |
| 232 | di853a0065 | 65 | DI853A | 1985-03-16T12:05:00Z | -155.0433 | 57.628334 | 232.0 | 5.79 | NaN |
233 rows × 9 columns
Plot one dataset¶
keys = list(cat[dataset_id].metadata["plots"].keys())
print(keys)
plots = []
for key in keys:
plot_kwargs = cat[dataset_id].metadata["plots"][key]
if "clim" in plot_kwargs and isinstance(plot_kwargs["clim"], list):
plot_kwargs["clim"] = tuple(plot_kwargs["clim"])
if "dynamic" in plot_kwargs:
plot_kwargs["dynamic"] = False
plots.append(cat[dataset_id].ToHvPlot(**plot_kwargs).read())
hv.Layout(plots).cols(1)
['data']
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[6], line 11
9 if "dynamic" in plot_kwargs:
10 plot_kwargs["dynamic"] = False
---> 11 plots.append(cat[dataset_id].ToHvPlot(**plot_kwargs).read())
12 hv.Layout(plots).cols(1)
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/intake/readers/readers.py:121, in BaseReader.read(self, *args, **kwargs)
119 kw.update(kwargs)
120 args = kw.pop("args", ()) or args
--> 121 return self._read(*args, **kw)
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/intake/readers/convert.py:629, in Pipeline._read(self, discover, **kwargs)
627 kw = kwargs if i == len(self.steps) else {}
628 if i:
--> 629 data = self._read_stage_n(i, data=data, **kw)
630 else:
631 data = self._read_stage_n(i, discover=discover, **kw)
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/intake/readers/convert.py:615, in Pipeline._read_stage_n(self, stage, discover, **kwargs)
613 return func(metadata=self.metadata).discover(*arg, **kw2)
614 else:
--> 615 return func(metadata=self.metadata).read(*arg, **kw2)
616 elif isinstance(func, BaseReader):
617 if discover:
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/intake/readers/readers.py:121, in BaseReader.read(self, *args, **kwargs)
119 kw.update(kwargs)
120 args = kw.pop("args", ()) or args
--> 121 return self._read(*args, **kw)
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/intake/readers/convert.py:62, in BaseConverter._read(self, data, *args, **kwargs)
60 if isinstance(data, BaseReader):
61 data = data.read()
---> 62 return self.run(data, *args, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/intake/readers/convert.py:192, in ToHvPlot.run(self, data, explorer, **kw)
189 if explorer:
190 # this is actually a hvplot.ui:hvPlotExplorer and only allows tabular data
191 return hvplot.explorer(data, **kw)
--> 192 return hvplot.hvPlot(data, **kw)()
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/hvplot/plotting/core.py:95, in hvPlotBase.__call__(self, x, y, kind, **kwds)
92 plot = self._get_converter(x, y, kind, **kwds)(kind, x, y)
93 return pn.panel(plot, **panel_dict)
---> 95 return self._get_converter(x, y, kind, **kwds)(kind, x, y)
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/hvplot/converter.py:2066, in HoloViewsConverter.__call__(self, kind, x, y)
2063 dataset = Dataset(data)
2064 dataset = redim_(dataset, **self._redim)
-> 2066 obj = method(x, y)
2067 obj._dataset = dataset
2069 if self.crs and self.project:
2070 # Apply projection before rasterizing
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/hvplot/converter.py:2601, in HoloViewsConverter.line(self, x, y, data)
2599 def line(self, x=None, y=None, data=None):
2600 self._error_if_unavailable('line')
-> 2601 return self.chart(Curve, x, y, data)
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/hvplot/converter.py:2588, in HoloViewsConverter.chart(self, element, x, y, data)
2586 charts = []
2587 for c in y:
-> 2588 ydim = hv.Dimension(c, label=self.value_label)
2589 kdims, vdims = self._get_dimensions([x], [ydim])
2590 chart = element(data, kdims, vdims)
File ~/checkouts/readthedocs.org/user_builds/cook-inlet-catalogs/conda/latest/lib/python3.11/site-packages/holoviews/core/dimension.py:285, in Dimension.__init__(self, spec, **params)
283 raise ValueError('Dimension name cannot be empty')
284 if not all_params['label']:
--> 285 raise ValueError('Dimension label cannot be empty')
287 values = params.get('values', [])
288 if isinstance(values, str) and values == 'initial':
ValueError: Dimension label cannot be empty