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'])
-122.339167

Station 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  v

For 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!

• @delgadom
• @CraigHarter
• @jcconnel
• @fabaff
• @taataam