Source code for dataretrieval.nwis

"""Functions for downloading data from the `National Water Information System (NWIS)`_.

.. _National Water Information System (NWIS): https://waterdata.usgs.gov/nwis


.. todo::

    * Create a test to check whether functions pull multiple sites
    * Work on multi-index capabilities.
    * Check that all timezones are handled properly for each service.

"""

import re
import warnings
from io import StringIO
from typing import List, Optional, Tuple, Union

import pandas as pd
import requests

from dataretrieval.utils import BaseMetadata, format_datetime, to_str

from .utils import query

try:
    import geopandas as gpd
except ImportError:
    gpd = None

WATERDATA_BASE_URL = 'https://nwis.waterdata.usgs.gov/'
WATERDATA_URL = WATERDATA_BASE_URL + 'nwis/'
WATERSERVICE_URL = 'https://waterservices.usgs.gov/nwis/'
PARAMCODES_URL = 'https://help.waterdata.usgs.gov/code/parameter_cd_nm_query?'
ALLPARAMCODES_URL = 'https://help.waterdata.usgs.gov/code/parameter_cd_query?'

WATERSERVICES_SERVICES = ['dv', 'iv', 'site', 'stat']
WATERDATA_SERVICES = [
    'qwdata',
    'gwlevels',
    'measurements',
    'peaks',
    'pmcodes',
    'water_use',
    'ratings',
]
_CRS = "EPSG:4236"


[docs] def format_response( df: pd.DataFrame, service: Optional[str] = None, **kwargs ) -> pd.DataFrame: """Setup index for response from query. This function formats the response from the NWIS web services, in particular it sets the index of the data frame. This function tries to convert the NWIS response into pandas datetime values localized to UTC, and if possible, uses these timestamps to define the data frame index. Parameters ---------- df: ``pandas.DataFrame`` The data frame to format service: string, optional, default is None The NWIS service that was queried, important because the 'peaks' service returns a different format than the other services. **kwargs: optional Additional keyword arguments, e.g., 'multi_index' Returns ------- df: ``pandas.DataFrame`` The formatted data frame """ mi = kwargs.pop('multi_index', True) if service == 'peaks': df = preformat_peaks_response(df) if gpd is not None: if "dec_lat_va" in list(df): geoms = gpd.points_from_xy( df.dec_long_va.values, df.dec_lat_va.values ) df = gpd.GeoDataFrame(df, geometry=geoms, crs=_CRS) # check for multiple sites: if 'datetime' not in df.columns: # XXX: consider making site_no index return df elif len(df['site_no'].unique()) > 1 and mi: # setup multi-index df.set_index(['site_no', 'datetime'], inplace=True) if hasattr(df.index.levels[1], 'tzinfo') and df.index.levels[1].tzinfo is None: df = df.tz_localize('UTC', level=1) else: df.set_index(['datetime'], inplace=True) if hasattr(df.index, 'tzinfo') and df.index.tzinfo is None: df = df.tz_localize('UTC') return df.sort_index()
[docs] def preformat_peaks_response(df: pd.DataFrame) -> pd.DataFrame: """Datetime formatting for the 'peaks' service response. Function to format the datetime column of the 'peaks' service response. Parameters ---------- df: ``pandas.DataFrame`` The data frame to format Returns ------- df: ``pandas.DataFrame`` The formatted data frame """ df['datetime'] = pd.to_datetime(df.pop('peak_dt'), errors='coerce') df.dropna(subset=['datetime'], inplace=True) return df
[docs] def get_qwdata( sites: Optional[Union[List[str], str]] = None, start: Optional[str] = None, end: Optional[str] = None, multi_index: bool = True, wide_format: bool = True, datetime_index: bool = True, ssl_check: bool = True, **kwargs, ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Get water sample data from qwdata service. .. warning:: WARNING: Beginning in March 2024 the NWIS qw data endpoint will not deliver new data or updates to existing data. Eventually the endpoint will be retired. For updated information visit: https://waterdata.usgs.gov.nwis/qwdata For additional details, see the R package vignette: https://doi-usgs.github.io/dataRetrieval/articles/Status.html If you have additional questions about the qw data service, email CompTools@usgs.gov. Parameters ---------- sites: string or list of strings, optional, default is None If the qwdata parameter site_no is supplied, it will overwrite the sites parameter start: string, optional, default is None If the qwdata parameter begin_date is supplied, it will overwrite the start parameter (YYYY-MM-DD) end: string, optional, default is None If the qwdata parameter end_date is supplied, it will overwrite the end parameter (YYYY-MM-DD) multi_index: bool, optional If False, a dataframe with a single-level index (datetime) is returned, default is True wide_format : bool, optional If True, return data in wide format with multiple samples per row and one row per time, default is True datetime_index : bool, optional If True, create a datetime index, default is True ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Returns ------- df: ``pandas.DataFrame`` Times series data from the NWIS JSON md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # get water sample information for site 11447650 >>> df, md = dataretrieval.nwis.get_qwdata( ... sites='11447650', start='2010-01-01', end='2010-02-01' ... ) """ warnings.warn(('WARNING: Starting in March 2024, the NWIS qw data endpoint is ' 'retiring and no longer receives updates. For more information, ' 'refer to https://waterdata.usgs.gov.nwis/qwdata and ' 'https://doi-usgs.github.io/dataRetrieval/articles/Status.html ' 'or email CompTools@usgs.gov.')) _check_sites_value_types(sites) kwargs['site_no'] = kwargs.pop('site_no', sites) kwargs['begin_date'] = kwargs.pop('begin_date', start) kwargs['end_date'] = kwargs.pop('end_date', end) kwargs['multi_index'] = multi_index if wide_format: kwargs['qw_sample_wide'] = 'qw_sample_wide' payload = { 'agency_cd': 'USGS', 'format': 'rdb', 'pm_cd_compare': 'Greater than', 'inventory_output': '0', 'rdb_inventory_output': 'file', 'TZoutput': '0', 'rdb_qw_attributes': 'expanded', 'date_format': 'YYYY-MM-DD', 'rdb_compression': 'value', 'submitted_form': 'brief_list', } # check for parameter codes, and reformat query args qwdata_parameter_code_field = 'parameterCd' if kwargs.get(qwdata_parameter_code_field): parameter_codes = kwargs.pop(qwdata_parameter_code_field) parameter_codes = to_str(parameter_codes) kwargs['multiple_parameter_cds'] = parameter_codes kwargs['param_cd_operator'] = 'OR' search_criteria = kwargs.get('list_of_search_criteria') if search_criteria: kwargs['list_of_search_criteria'] = '{},{}'.format( search_criteria, 'multiple_parameter_cds' ) else: kwargs['list_of_search_criteria'] = 'multiple_parameter_cds' kwargs.update(payload) warnings.warn( 'NWIS qw web services are being retired. ' + 'See this note from the R package for more: ' + 'https://doi-usgs.github.io/dataRetrieval/articles/qwdata_changes.html', category=DeprecationWarning, ) response = query_waterdata('qwdata', ssl_check=ssl_check, **kwargs) df = _read_rdb(response.text) if datetime_index is True: df = format_datetime(df, 'sample_dt', 'sample_tm', 'sample_start_time_datum_cd') return format_response(df, **kwargs), NWIS_Metadata(response, **kwargs)
[docs] def get_discharge_measurements( sites: Optional[Union[List[str], str]] = None, start: Optional[str] = None, end: Optional[str] = None, ssl_check: bool = True, **kwargs, ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Get discharge measurements from the waterdata service. Parameters ---------- sites: string or list of strings, optional, default is None If the qwdata parameter site_no is supplied, it will overwrite the sites parameter start: string, optional, default is None If the qwdata parameter begin_date is supplied, it will overwrite the start parameter (YYYY-MM-DD) end: string, optional, default is None If the qwdata parameter end_date is supplied, it will overwrite the end parameter (YYYY-MM-DD) ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Returns ------- df: ``pandas.DataFrame`` Times series data from the NWIS JSON md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get discharge measurements for site 05114000 >>> df, md = dataretrieval.nwis.get_discharge_measurements( ... sites='05114000', start='2000-01-01', end='2000-01-30' ... ) >>> # Get discharge measurements for sites in Alaska >>> df, md = dataretrieval.nwis.get_discharge_measurements( ... start='2012-01-09', end='2012-01-10', stateCd='AK' ... ) """ _check_sites_value_types(sites) kwargs['site_no'] = kwargs.pop('site_no', sites) kwargs['begin_date'] = kwargs.pop('begin_date', start) kwargs['end_date'] = kwargs.pop('end_date', end) if 'format' not in kwargs: kwargs['format'] = 'rdb' response = query_waterdata( 'measurements', ssl_check=ssl_check, **kwargs ) return _read_rdb(response.text), NWIS_Metadata(response, **kwargs)
[docs] def get_discharge_peaks( sites: Optional[Union[List[str], str]] = None, start: Optional[str] = None, end: Optional[str] = None, multi_index: bool = True, ssl_check: bool = True, **kwargs, ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Get discharge peaks from the waterdata service. Parameters ---------- sites: string or list of strings, optional, default is None If the waterdata parameter site_no is supplied, it will overwrite the sites parameter start: string, optional, default is None If the waterdata parameter begin_date is supplied, it will overwrite the start parameter (YYYY-MM-DD) end: string, optional, default is None If the waterdata parameter end_date is supplied, it will overwrite the end parameter (YYYY-MM-DD) multi_index: bool, optional If False, a dataframe with a single-level index (datetime) is returned, default is True ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Returns ------- df: ``pandas.DataFrame`` Times series data from the NWIS JSON md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get discharge peaks for site 01491000 >>> df, md = dataretrieval.nwis.get_discharge_peaks( ... sites='01491000', start='1980-01-01', end='1990-01-01' ... ) >>> # Get discharge peaks for sites in Hawaii >>> df, md = dataretrieval.nwis.get_discharge_peaks( ... start='1980-01-01', end='1980-01-02', stateCd='HI' ... ) """ _check_sites_value_types(sites) kwargs['site_no'] = kwargs.pop('site_no', sites) kwargs['begin_date'] = kwargs.pop('begin_date', start) kwargs['end_date'] = kwargs.pop('end_date', end) kwargs['multi_index'] = multi_index response = query_waterdata('peaks', format='rdb', ssl_check=ssl_check, **kwargs) df = _read_rdb(response.text) return format_response(df, service='peaks', **kwargs), NWIS_Metadata( response, **kwargs )
[docs] def get_gwlevels( sites: Optional[Union[List[str], str]] = None, start: str = '1851-01-01', end: Optional[str] = None, multi_index: bool = True, datetime_index: bool = True, ssl_check: bool = True, **kwargs, ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Queries the groundwater level service from waterservices Parameters ---------- sites: string or list of strings, optional, default is None If the waterdata parameter site_no is supplied, it will overwrite the sites parameter start: string, optional, default is '1851-01-01' If the waterdata parameter begin_date is supplied, it will overwrite the start parameter end: string, optional, default is None If the waterdata parameter end_date is supplied, it will overwrite the end parameter (YYYY-MM-DD) multi_index: bool, optional If False, a dataframe with a single-level index (datetime) is returned, default is True datetime_index : bool, optional If True, create a datetime index, default is True ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Returns ------- df: ``pandas.DataFrame`` Times series data from the NWIS JSON md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get groundwater levels for site 434400121275801 >>> df, md = dataretrieval.nwis.get_gwlevels(sites='434400121275801') """ _check_sites_value_types(sites) # Make kwargs backwards compatible with waterservices # vocabulary if 'startDT' in kwargs: kwargs['begin_date'] = kwargs.pop('startDT') if 'endDT' in kwargs: kwargs['end_date'] = kwargs.pop('endDT') if 'sites' in kwargs: kwargs['site_no'] = kwargs.pop('sites') if 'stateCd'in kwargs: kwargs['state_cd'] = kwargs.pop('stateCd') kwargs['begin_date'] = kwargs.pop('begin_date', start) kwargs['end_date'] = kwargs.pop('end_date', end) kwargs['site_no'] = kwargs.pop('site_no', sites) kwargs['multi_index'] = multi_index response = query_waterdata('gwlevels', format = 'rdb', ssl_check=ssl_check, **kwargs) df = _read_rdb(response.text) if datetime_index is True: df = format_datetime(df, 'lev_dt', 'lev_tm', 'lev_tz_cd') return format_response(df, **kwargs), NWIS_Metadata(response, **kwargs)
[docs] def get_stats( sites: Optional[Union[List[str], str]] = None, ssl_check: bool = True, **kwargs ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Queries water services statistics information. For more information about the water services statistics service, visit https://waterservices.usgs.gov/docs/statistics/statistics-details/ Parameters ---------- sites: string or list of strings, optional, default is None USGS site number (or list of site numbers) ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Keyword Arguments --------------------- statReportType: string daily (default), monthly, or annual statTypeCd: string all, mean, max, min, median Returns ------- df: ``pandas.DataFrame`` Statistics data from the statistics service md: :obj:`dataretrieval.utils.Metadata` A custom metadata object .. todo:: fix date parsing Examples -------- .. doctest:: >>> # Get annual water statistics for a site >>> df, md = dataretrieval.nwis.get_stats( ... sites='01646500', statReportType='annual', statYearType='water' ... ) >>> # Get monthly statistics for a site >>> df, md = dataretrieval.nwis.get_stats( ... sites='01646500', statReportType='monthly' ... ) """ _check_sites_value_types(sites) response = query_waterservices( service='stat', sites=sites, ssl_check=ssl_check, **kwargs ) return _read_rdb(response.text), NWIS_Metadata(response, **kwargs)
[docs] def query_waterdata( service: str, ssl_check: bool = True, **kwargs ) -> requests.models.Response: """ Queries waterdata. Parameters ---------- service: string Name of the service to query: 'site', 'stats', etc. ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Returns ------- request: ``requests.models.Response`` The response object from the API request to the web service """ major_params = ['site_no', 'state_cd'] bbox_params = [ 'nw_longitude_va', 'nw_latitude_va', 'se_longitude_va', 'se_latitude_va', ] if not any(key in kwargs for key in major_params + bbox_params): raise TypeError('Query must specify a major filter: site_no, stateCd, bBox') elif any(key in kwargs for key in bbox_params) and not all( key in kwargs for key in bbox_params ): raise TypeError('One or more lat/long coordinates missing or invalid.') if service not in WATERDATA_SERVICES: raise TypeError('Service not recognized') url = WATERDATA_URL + service return query(url, payload=kwargs, ssl_check=ssl_check)
[docs] def query_waterservices( service: str, ssl_check: bool = True, **kwargs ) -> requests.models.Response: """ Queries waterservices.usgs.gov For more documentation see https://waterservices.usgs.gov/docs/ .. note:: User must specify one major filter: sites, stateCd, or bBox Parameters ---------- service: string Name of the service to query: 'site', 'stats', etc. ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Keyword Arguments ---------------- bBox: string 7-digit Hydrologic Unit Code (HUC) startDT: string Start date (e.g., '2017-12-31') endDT: string End date (e.g., '2018-01-01') modifiedSince: string Used to return only sites where attributes or period of record data have changed during the request period. String expected to be formatted in ISO-8601 duration format (e.g., 'P1D' for one day, 'P1Y' for one year) Returns ------- request: ``requests.models.Response`` The response object from the API request to the web service """ if not any( key in kwargs for key in ['sites', 'stateCd', 'bBox', 'huc', 'countyCd'] ): raise TypeError( 'Query must specify a major filter: sites, stateCd, bBox, huc, or countyCd' ) if service not in WATERSERVICES_SERVICES: raise TypeError('Service not recognized') if 'format' not in kwargs: kwargs['format'] = 'rdb' url = WATERSERVICE_URL + service return query(url, payload=kwargs, ssl_check=ssl_check)
[docs] def get_dv( sites: Optional[Union[List[str], str]] = None, start: Optional[str] = None, end: Optional[str] = None, multi_index: bool = True, ssl_check: bool = True, **kwargs, ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Get daily values data from NWIS and return it as a ``pandas.DataFrame``. .. note: If no start or end date are provided, only the most recent record is returned. Parameters ---------- sites: string or list of strings, optional, default is None USGS site number (or list of site numbers) start: string, optional, default is None If the waterdata parameter startDT is supplied, it will overwrite the start parameter (YYYY-MM-DD) end: string, optional, default is None If the waterdata parameter endDT is supplied, it will overwrite the end parameter (YYYY-MM-DD) multi_index: bool, optional If True, return a multi-index dataframe, if False, return a single-index dataframe, default is True ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Returns ------- df: ``pandas.DataFrame`` Times series data from the NWIS JSON md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get mean statistic daily values for site 04085427 >>> df, md = dataretrieval.nwis.get_dv( ... sites='04085427', start='2012-01-01', end='2012-06-30', statCd='00003' ... ) >>> # Get the latest daily values for site 01646500 >>> df, md = dataretrieval.nwis.get_dv(sites='01646500') """ _check_sites_value_types(sites) kwargs['startDT'] = kwargs.pop('startDT', start) kwargs['endDT'] = kwargs.pop('endDT', end) kwargs['sites'] = kwargs.pop('sites', sites) kwargs['multi_index'] = multi_index response = query_waterservices('dv', format='json', ssl_check=ssl_check, **kwargs) df = _read_json(response.json()) return format_response(df, **kwargs), NWIS_Metadata(response, **kwargs)
[docs] def get_info(ssl_check: bool = True, **kwargs) -> Tuple[pd.DataFrame, BaseMetadata]: """ Get site description information from NWIS. **Note:** *Must specify one major parameter.* For additional parameter options see https://waterservices.usgs.gov/docs/site-service/site-service-details/ Parameters ---------- ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Keyword Arguments ---------------- sites: string or list of strings A list of site numbers. Sites may be prefixed with an optional agency code followed by a colon. stateCd: string U.S. postal service (2-digit) state code. Only 1 state can be specified per request. huc: string or list of strings A list of hydrologic unit codes (HUC) or aggregated watersheds. Only 1 major HUC can be specified per request, or up to 10 minor HUCs. A major HUC has two digits. bBox: string or list of strings A contiguous range of decimal latitude and longitude, starting with the west longitude, then the south latitude, then the east longitude, and then the north latitude with each value separated by a comma. The product of the range of latitude range and longitude cannot exceed 25 degrees. Whole or decimal degrees must be specified, up to six digits of precision. Minutes and seconds are not allowed. countyCd: string or list of strings A list of county numbers, in a 5 digit numeric format. The first two digits of a county's code are the FIPS State Code. (url: https://help.waterdata.usgs.gov/code/county_query?fmt=html) startDt: string Selects sites based on whether data was collected at a point in time beginning after startDt (start date). Dates must be in ISO-8601 Calendar Date format (for example: 1990-01-01). endDt: string The end date for the period of record. Dates must be in ISO-8601 Calendar Date format (for example: 1990-01-01). period: string Selects sites based on whether they were active between now and a time in the past. For example, period=P10W will select sites active in the last ten weeks. modifiedSince: string Returns only sites where site attributes or period of record data have changed during the request period. parameterCd: string or list of strings Returns only site data for those sites containing the requested USGS parameter codes. siteType: string or list of strings Restricts sites to those having one or more major and/or minor site types, such as stream, spring or well. For a list of all valid site types see https://help.waterdata.usgs.gov/site_tp_cd For example, siteType='ST' returns streams only. siteOutput: string ('basic' or 'expanded') Indicates the richness of metadata you want for site attributes. Note that for visually oriented formats like Google Map format, this argument has no meaning. Note: for performance reasons, siteOutput=expanded cannot be used if seriesCatalogOutput=true or with any values for outputDataTypeCd. seriesCatalogOutput: bool A switch that provides detailed period of record information for certain output formats. The period of record indicates date ranges for a certain kind of information about a site, for example the start and end dates for a site's daily mean streamflow. Returns ------- df: ``pandas.DataFrame`` Site data from the NWIS web service md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get site information for a single site >>> df, md = dataretrieval.nwis.get_info(sites='05114000') >>> # Get site information for multiple sites >>> df, md = dataretrieval.nwis.get_info(sites=['05114000', '09423350']) """ seriesCatalogOutput = kwargs.pop('seriesCatalogOutput', None) if seriesCatalogOutput in ['True', 'TRUE', 'true', True]: warnings.warn(('WARNING: Starting in March 2024, the NWIS qw data endpoint is ' 'retiring and no longer receives updates. For more information, ' 'refer to https://waterdata.usgs.gov.nwis/qwdata and ' 'https://doi-usgs.github.io/dataRetrieval/articles/Status.html ' 'or email CompTools@usgs.gov.')) # convert bool to string if necessary kwargs['seriesCatalogOutput'] = 'True' else: # cannot have both seriesCatalogOutput and the expanded format kwargs['siteOutput'] = 'Expanded' response = query_waterservices('site', ssl_check=ssl_check, **kwargs) return _read_rdb(response.text), NWIS_Metadata(response, **kwargs)
[docs] def get_iv( sites: Optional[Union[List[str], str]] = None, start: Optional[str] = None, end: Optional[str] = None, multi_index: bool = True, ssl_check: bool = True, **kwargs, ) -> Tuple[pd.DataFrame, BaseMetadata]: """Get instantaneous values data from NWIS and return it as a DataFrame. .. note:: If no start or end date are provided, only the most recent record is returned. Parameters ---------- sites: string or list of strings, optional, default is None If the waterdata parameter site_no is supplied, it will overwrite the sites parameter start: string, optional, default is None If the waterdata parameter startDT is supplied, it will overwrite the start parameter (YYYY-MM-DD) end: string, optional, default is None If the waterdata parameter endDT is supplied, it will overwrite the end parameter (YYYY-MM-DD) multi_index: bool, optional If False, a dataframe with a single-level index (datetime) is returned, default is True ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Returns ------- df: ``pandas.DataFrame`` Times series data from the NWIS JSON md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get instantaneous discharge data for site 05114000 >>> df, md = dataretrieval.nwis.get_iv( ... sites='05114000', ... start='2013-11-03', ... end='2013-11-03', ... parameterCd='00060', ... ) """ _check_sites_value_types(sites) kwargs['startDT'] = kwargs.pop('startDT', start) kwargs['endDT'] = kwargs.pop('endDT', end) kwargs['sites'] = kwargs.pop('sites', sites) kwargs['multi_index'] = multi_index response = query_waterservices( service='iv', format='json', ssl_check=ssl_check, **kwargs ) df = _read_json(response.json()) return format_response(df, **kwargs), NWIS_Metadata(response, **kwargs)
[docs] def get_pmcodes( parameterCd: Union[str, List[str]] = 'All', partial: bool = True, ssl_check: bool = True, ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Return a ``pandas.DataFrame`` containing all NWIS parameter codes. Parameters ---------- parameterCd: string or list of strings, default is 'All' Accepts parameter codes or names partial: bool, optional Default is True (partial querying). If False, the function will query only exact matches, default is True ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True Returns ------- df: ``pandas.DataFrame`` Data retrieved from the NWIS web service. md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get information about the '00060' pcode >>> df, md = dataretrieval.nwis.get_pmcodes(parameterCd='00060', partial=False) >>> # Get information about all 'Discharge' pcodes >>> df, md = dataretrieval.nwis.get_pmcodes( ... parameterCd='Discharge', partial=True ... ) """ payload = {'fmt': 'rdb'} url = PARAMCODES_URL if isinstance(parameterCd, str): # when a single code or name is given if parameterCd.lower() == 'all': payload.update({'group_cd': '%'}) url = ALLPARAMCODES_URL response = query(url, payload, ssl_check=ssl_check) return _read_rdb(response.text), NWIS_Metadata(response) else: parameterCd = [parameterCd] if not isinstance(parameterCd, list): raise TypeError( 'Parameter information (code or name) must be type string or list' ) # Querying with a list of parameters names, codes, or mixed return_list = [] for param in parameterCd: if isinstance(param, str): if partial: param = f'%{param}%' payload.update({'parm_nm_cd': param}) response = query(url, payload, ssl_check=ssl_check) if len(response.text.splitlines()) < 10: # empty query raise TypeError( 'One of the parameter codes or names entered does not' 'return any information, please try a different value' ) return_list.append(_read_rdb(response.text)) else: raise TypeError('Parameter information (code or name) must be type string') return pd.concat(return_list), NWIS_Metadata(response)
[docs] def get_water_use( years: Union[str, List[str]] = 'ALL', state: Optional[str] = None, counties: Union[str, List[str]] = 'ALL', categories: Union[str, List[str]] = 'ALL', ssl_check: bool = True, ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Water use data retrieval from USGS (NWIS). Parameters ---------- years: string or list of strings List or comma delimited string of years. Must be years ending in 0 or 5, or "ALL", which retrieves all available years, default is "ALL" state: string, optional, default is None full name, abbreviation or id counties: string or list of strings County IDs from county lookup or "ALL", default is "ALL" categories: string or list of strings List or comma delimited string of Two-letter category abbreviations, default is "ALL" ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True Returns ------- df: ``pandas.DataFrame`` Data from NWIS md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get total population for RI from the NWIS water use service >>> df, md = dataretrieval.nwis.get_water_use( ... years='2000', state='RI', categories='TP' ... ) >>> # Get the national total water use for livestock in Bgal/day >>> df, md = dataretrieval.nwis.get_water_use(years='2010', categories='L') >>> # Get 2005 domestic water use for Apache County in Arizona >>> df, md = dataretrieval.nwis.get_water_use( ... years='2005', state='Arizona', counties='001', categories='DO' ... ) """ if years: if not isinstance(years, list) and not isinstance(years, str): raise TypeError('years must be a string or a list of strings') if counties: if not isinstance(counties, list) and not isinstance(counties, str): raise TypeError('counties must be a string or a list of strings') if categories: if not isinstance(categories, list) and not isinstance(categories, str): raise TypeError('categories must be a string or a list of strings') payload = { 'rdb_compression': 'value', 'format': 'rdb', 'wu_year': years, 'wu_category': categories, 'wu_county': counties, } url = WATERDATA_URL + 'water_use' if state is not None: url = WATERDATA_BASE_URL + state + '/nwis/water_use' payload.update({'wu_area': 'county'}) response = query(url, payload, ssl_check=ssl_check) return _read_rdb(response.text), NWIS_Metadata(response)
[docs] def get_ratings( site: Optional[str] = None, file_type: str = 'base', ssl_check: bool = True, **kwargs, ) -> Tuple[pd.DataFrame, BaseMetadata]: """ Rating table for an active USGS streamgage retrieval. Reads current rating table for an active USGS streamgage from NWISweb. Data is retrieved from https://waterdata.usgs.gov/nwis. Parameters ---------- site: string, optional, default is None USGS site number. This is usually an 8 digit number as a string. If the nwis parameter site_no is supplied, it will overwrite the site parameter file_type: string, default is "base" can be "base", "corr", or "exsa" ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Return ------ df: ``pandas.DataFrame`` Formatted requested data md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # Get the rating table for USGS streamgage 01594440 >>> df, md = dataretrieval.nwis.get_ratings(site='01594440') """ site = kwargs.pop('site_no', site) payload = {} url = WATERDATA_BASE_URL + 'nwisweb/get_ratings/' if site is not None: payload.update({'site_no': site}) if file_type is not None: if file_type not in ['base', 'corr', 'exsa']: raise ValueError( f'Unrecognized file_type: {file_type}, must be "base", "corr" or "exsa"' ) payload.update({'file_type': file_type}) response = query(url, payload, ssl_check=ssl_check) return _read_rdb(response.text), NWIS_Metadata(response, site_no=site)
[docs] def what_sites(ssl_check: bool = True, **kwargs) -> Tuple[pd.DataFrame, BaseMetadata]: """ Search NWIS for sites within a region with specific data. Parameters ---------- ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional Accepts the same parameters as :obj:`dataretrieval.nwis.get_info` Return ------ df: ``pandas.DataFrame`` Formatted requested data md: :obj:`dataretrieval.utils.Metadata` A custom metadata object Examples -------- .. doctest:: >>> # get information about a single site >>> df, md = dataretrieval.nwis.what_sites(sites='05114000') >>> # get information about sites with phosphorus in Ohio >>> df, md = dataretrieval.nwis.what_sites(stateCd='OH', parameterCd='00665') """ response = query_waterservices(service='site', ssl_check=ssl_check, **kwargs) df = _read_rdb(response.text) return df, NWIS_Metadata(response, **kwargs)
[docs] def get_record( sites: Optional[Union[List[str], str]] = None, start: Optional[str] = None, end: Optional[str] = None, multi_index: bool = True, wide_format: bool = True, datetime_index: bool = True, state: Optional[str] = None, service: str = 'iv', ssl_check: bool = True, **kwargs, ) -> pd.DataFrame: """ Get data from NWIS and return it as a ``pandas.DataFrame``. .. note:: If no start or end date are provided, only the most recent record is returned. Parameters ---------- sites: string or list of strings, optional, default is None List or comma delimited string of site. start: string, optional, default is None Starting date of record (YYYY-MM-DD) end: string, optional, default is None Ending date of record. (YYYY-MM-DD) multi_index: bool, optional If False, a dataframe with a single-level index (datetime) is returned, default is True wide_format : bool, optional If True, return data in wide format with multiple samples per row and one row per time, default is True datetime_index : bool, optional If True, create a datetime index. default is True state: string, optional, default is None full name, abbreviation or id service: string, default is 'iv' - 'iv' : instantaneous data - 'dv' : daily mean data - 'qwdata' : discrete samples - 'site' : site description - 'measurements' : discharge measurements - 'peaks': discharge peaks - 'gwlevels': groundwater levels - 'pmcodes': get parameter codes - 'water_use': get water use data - 'ratings': get rating table - 'stat': get statistics ssl_check: bool, optional If True, check SSL certificates, if False, do not check SSL, default is True **kwargs: optional If supplied, will be used as query parameters Returns ------- ``pandas.DataFrame`` containing requested data Examples -------- .. doctest:: >>> # Get latest instantaneous data from site 01585200 >>> df = dataretrieval.nwis.get_record(sites='01585200', service='iv') >>> # Get latest daily mean data from site 01585200 >>> df = dataretrieval.nwis.get_record(sites='01585200', service='dv') >>> # Get all discrete sample data from site 01585200 >>> df = dataretrieval.nwis.get_record(sites='01585200', service='qwdata') >>> # Get site description for site 01585200 >>> df = dataretrieval.nwis.get_record(sites='01585200', service='site') >>> # Get discharge measurements for site 01585200 >>> df = dataretrieval.nwis.get_record(sites='01585200', service='measurements') >>> # Get discharge peaks for site 01585200 >>> df = dataretrieval.nwis.get_record(sites='01585200', service='peaks') >>> # Get latest groundwater level for site 434400121275801 >>> df = dataretrieval.nwis.get_record( ... sites='434400121275801', service='gwlevels' ... ) >>> # Get information about the discharge parameter code >>> df = dataretrieval.nwis.get_record(service='pmcodes', parameterCd='00060') >>> # Get water use data for livestock nationally in 2010 >>> df = dataretrieval.nwis.get_record( ... service='water_use', years='2010', categories='L' ... ) >>> # Get rating table for USGS streamgage 01585200 >>> df = dataretrieval.nwis.get_record(sites='01585200', service='ratings') >>> # Get annual statistics for USGS station 01646500 >>> df = dataretrieval.nwis.get_record( ... sites='01646500', ... service='stat', ... statReportType='annual', ... statYearType='water', ... ) """ _check_sites_value_types(sites) if service not in WATERSERVICES_SERVICES + WATERDATA_SERVICES: raise TypeError(f'Unrecognized service: {service}') if service == 'iv': df, _ = get_iv( sites=sites, startDT=start, endDT=end, multi_index=multi_index, ssl_check=ssl_check, **kwargs, ) return df elif service == 'dv': df, _ = get_dv( sites=sites, startDT=start, endDT=end, multi_index=multi_index, ssl_check=ssl_check, **kwargs, ) return df elif service == 'qwdata': df, _ = get_qwdata( site_no=sites, begin_date=start, end_date=end, multi_index=multi_index, wide_format=wide_format, ssl_check=ssl_check, **kwargs, ) return df elif service == 'site': df, _ = get_info(sites=sites, ssl_check=ssl_check, **kwargs) return df elif service == 'measurements': df, _ = get_discharge_measurements( site_no=sites, begin_date=start, end_date=end, ssl_check=ssl_check, **kwargs ) return df elif service == 'peaks': df, _ = get_discharge_peaks( site_no=sites, begin_date=start, end_date=end, multi_index=multi_index, ssl_check=ssl_check, **kwargs, ) return df elif service == 'gwlevels': df, _ = get_gwlevels( sites=sites, startDT=start, endDT=end, multi_index=multi_index, datetime_index=datetime_index, ssl_check=ssl_check, **kwargs, ) return df elif service == 'pmcodes': df, _ = get_pmcodes(ssl_check=ssl_check, **kwargs) return df elif service == 'water_use': df, _ = get_water_use(state=state, ssl_check=ssl_check, **kwargs) return df elif service == 'ratings': df, _ = get_ratings(site=sites, ssl_check=ssl_check, **kwargs) return df elif service == 'stat': df, _ = get_stats(sites=sites, ssl_check=ssl_check, **kwargs) return df else: raise TypeError(f'{service} service not yet implemented')
[docs] def _read_json(json): """ Reads a NWIS Water Services formatted JSON into a ``pandas.DataFrame``. Parameters ---------- json: dict A JSON dictionary response to be parsed into a ``pandas.DataFrame`` Returns ------- df: ``pandas.DataFrame`` Times series data from the NWIS JSON md: :obj:`dataretrieval.utils.Metadata` A custom metadata object """ merged_df = pd.DataFrame(columns=['site_no', 'datetime']) site_list = [ ts['sourceInfo']['siteCode'][0]['value'] for ts in json['value']['timeSeries'] ] # create a list of indexes for each change in site no # for example, [0, 21, 22] would be the first and last indeces index_list = [0] index_list.extend( [i + 1 for i, (a, b) in enumerate(zip(site_list[:-1], site_list[1:])) if a != b] ) index_list.append(len(site_list)) for i in range(len(index_list) - 1): start = index_list[i] # [0] end = index_list[i + 1] # [21] # grab a block containing timeseries 0:21, # which are all from the same site site_block = json['value']['timeSeries'][start:end] if not site_block: continue site_no = site_block[0]['sourceInfo']['siteCode'][0]['value'] site_df = pd.DataFrame(columns=['datetime']) for timeseries in site_block: param_cd = timeseries['variable']['variableCode'][0]['value'] # check whether min, max, mean record XXX option = timeseries['variable']['options']['option'][0].get('value') # loop through each parameter in timeseries, then concat to the merged_df for parameter in timeseries['values']: col_name = param_cd method = parameter['method'][0]['methodDescription'] # if len(timeseries['values']) > 1 and method: if method: # get method, format it, and append to column name method = method.strip('[]()').lower() col_name = f'{col_name}_{method}' if option: col_name = f'{col_name}_{option}' record_json = parameter['value'] if not record_json: # no data in record continue # should be able to avoid this by dumping record_json = str(record_json).replace("'", '"') # read json, converting all values to float64 and all qualifiers # Lists can't be hashed, thus we cannot df.merge on a list column record_df = pd.read_json( StringIO(record_json), orient='records', dtype={'value': 'float64', 'qualifiers': 'unicode'}, convert_dates=False, ) record_df['qualifiers'] = ( record_df['qualifiers'].str.strip('[]').str.replace("'", '') ) record_df.rename( columns={ 'value': col_name, 'dateTime': 'datetime', 'qualifiers': col_name + '_cd', }, inplace=True, ) site_df = site_df.merge(record_df, how='outer', on='datetime') # end of site loop site_df['site_no'] = site_no merged_df = pd.concat([merged_df, site_df]) # convert to datetime, normalizing the timezone to UTC when doing so if 'datetime' in merged_df.columns: merged_df['datetime'] = pd.to_datetime(merged_df['datetime'], utc=True) return merged_df
[docs] def _read_rdb(rdb): """ Convert NWIS rdb table into a ``pandas.dataframe``. Parameters ---------- rdb: string A string representation of an rdb table Returns ------- df: ``pandas.dataframe`` A formatted pandas data frame """ count = 0 for line in rdb.splitlines(): # ignore comment lines if line.startswith('#'): count = count + 1 else: break fields = re.split('[\t]', rdb.splitlines()[count]) fields = [field.replace(',', '') for field in fields] dtypes = { 'site_no': str, 'dec_long_va': float, 'dec_lat_va': float, 'parm_cd': str, 'parameter_cd': str, } df = pd.read_csv( StringIO(rdb), delimiter='\t', skiprows=count + 2, names=fields, na_values='NaN', dtype=dtypes, ) df = format_response(df) return df
def _check_sites_value_types(sites): if sites: if not isinstance(sites, list) and not isinstance(sites, str): raise TypeError('sites must be a string or a list of strings')
[docs] class NWIS_Metadata(BaseMetadata): """Metadata class for NWIS service, derived from BaseMetadata. Attributes ---------- url : str Response url query_time: datetme.timedelta Response elapsed time header: requests.structures.CaseInsensitiveDict Response headers comments: str | None Metadata comments, if any site_info: tuple[pd.DataFrame, NWIS_Metadata] | None Site information if the query included `site_no`, `sites`, `stateCd`, `huc`, `countyCd` or `bBox`. `site_no` is preferred over `sites` if both are present. variable_info: tuple[pd.DataFrame, NWIS_Metadata] | None Variable information if the query included `parameterCd`. """
[docs] def __init__(self, response, **parameters) -> None: """Generates a standard set of metadata informed by the response with specific metadata for NWIS data. Parameters ---------- response: Response Response object from requests module parameters: unpacked dictionary Unpacked dictionary of the parameters supplied in the request Returns ------- md: :obj:`dataretrieval.nwis.NWIS_Metadata` A ``dataretrieval`` custom :obj:`dataretrieval.nwis.NWIS_Metadata` object. """ super().__init__(response) comments = '' for line in response.text.splitlines(): if line.startswith('#'): comments += line.lstrip('#') + '\n' if comments: self.comment = comments self._parameters = parameters
@property def site_info(self) -> Optional[Tuple[pd.DataFrame, BaseMetadata]]: """ Return ------ df: ``pandas.DataFrame`` Formatted requested data from calling `nwis.what_sites` md: :obj:`dataretrieval.nwis.NWIS_Metadata` A NWIS_Metadata object """ if 'site_no' in self._parameters: return what_sites(sites=self._parameters['site_no']) elif 'sites' in self._parameters: return what_sites(sites=self._parameters['sites']) elif 'stateCd' in self._parameters: return what_sites(stateCd=self._parameters['stateCd']) elif 'huc' in self._parameters: return what_sites(huc=self._parameters['huc']) elif 'countyCd' in self._parameters: return what_sites(countyCd=self._parameters['countyCd']) elif 'bBox' in self._parameters: return what_sites(bBox=self._parameters['bBox']) else: return None # don't set metadata site_info attribute @property def variable_info(self) -> Optional[Tuple[pd.DataFrame, BaseMetadata]]: # define variable_info metadata based on parameterCd if available if 'parameterCd' in self._parameters: return get_pmcodes(parameterCd=self._parameters['parameterCd'])