noaa_coops is a Python wrapper for the NOAA CO-OPS Tides & Currents Data
and Metadata APIs.
This package is an evolution of py_noaa, the main addition being the creation of a Station class that is central to
noaa_coops and provides distinct advantages over py_noaa.
All data and metadata is handled using a Station class with methods and
attributes for retrieving metadata, observed data, and predicted data.
All available metadata for a desired station (identifed by unique stationid)
is automagically generated when a Station object is initialzed. Station IDs
can be found using the mapping interface at https://tidesandcurrents.noaa.gov/.
All metadata is stored as a dictionary in the .metadata attribute of a
Station object for easy exploration (e.g. seattle.metadata). Additionally,
the keys of the metadata attribute dictionary are also assigned as attributes
of the station object itself (easily explored using tab-completion in your IDE).
For example:
>>> from pprint import pprint # For pretty printing
>>> import noaa_coops as nc
>>> seattle = nc.Station(9447130)
>>> pprint(seattle.lat_lon['lat'])
47.601944
>>> pprint(seattle.lat_lon['lon'])
-122.339167Station data can be retrieved using the .get_data method on a Station
class object. Data is returned as a Pandas DataFrame for easy use and analysis.
Data types are listed on the NOAA CO-OPS Data API. The data types currently supported for retrieval with noaa_coops are:
- Currents
- Observed water levels
- Observered daily high and low water levels (use `product="high_low"`)
- Predicted water levels
- Predicted high and low water levels
- Winds
- Air pressure
- Air temperature
- Water temperature
Compatibility with other data products may exist, but is not guaranteed at this time. Feel free to submit a pull request if you would like to add addtional functionality.
In the example below, water level data is retrieved for the Seattle station (stationid=9447130) for a 3 month period.
>>> import noaa_coops as nc
>>> seattle = nc.Station(9447130)
>>> df_water_levels = seattle.get_data(
... begin_date="20150101",
... end_date="20150331",
... product="water_level",
... datum="MLLW",
... units="metric",
... time_zone="gmt")
>>> df_water_levels.head() # doctest: +NORMALIZE_WHITESPACE
water_level sigma flags QC
date_time
2015-01-01 00:00:00 1.799 0.023 0,0,0,0 v
2015-01-01 00:06:00 1.718 0.018 0,0,0,0 v
2015-01-01 00:12:00 1.639 0.013 0,0,0,0 v
2015-01-01 00:18:00 1.557 0.012 0,0,0,0 v
2015-01-01 00:24:00 1.473 0.014 0,0,0,0 vFor use:
- requests
- numpy
- pandas
- zeep
For development/contributions:
- pytest
- pytest-cov
See issues for a list of issues and to add issues of your own.
All contributions are welcome, feel free to submit a pull request if you have a valuable addition to the package or constructive feedback.
Many thanks to the following contributors!