Export dataframe to csv
Dan Howe
7 years ago
parent
23789a8942
commit
4d19214d2e
@ -1,125 +1,131 @@
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import requests
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import requests
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import pandas as pd
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import pandas as pd
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from io import StringIO
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from io import StringIO
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def pointdata(variables,
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def pointdata(variables,
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api_key,
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api_key,
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start,
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start,
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finish,
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finish,
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station=None,
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station=None,
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lat=None,
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lat=None,
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lon=None,
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lon=None,
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units=True):
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units=True,
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"""Request point data from SILO.
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output=None):
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"""Request point data from SILO.
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Args:
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variables: list containing variable name strings
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Args:
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api_key: SILO api key
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variables: list containing variable name strings
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start: start date (yyyymmdd)
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api_key: SILO api key
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finish: finish date (yyyymmdd)
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start: start date (yyyymmdd)
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station: weather station ID (or use 'lat' and 'lon')
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finish: finish date (yyyymmdd)
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lat: latitude (between -44° and -10°, in increments of 0.05°)
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station: weather station ID (or use 'lat' and 'lon')
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lon: longitude (between 112° and 154°, in increments of 0.05°)
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lat: latitude (between -44° and -10°, in increments of 0.05°)
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units: include units in dataframe column names
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lon: longitude (between 112° and 154°, in increments of 0.05°)
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units: include units in dataframe column names
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Returns:
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Dataframe containing climate data time series
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Returns:
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Dataframe containing climate data time series
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API tutorial:
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https://silo.longpaddock.qld.gov.au/api-documentation/tutorial
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API tutorial:
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https://silo.longpaddock.qld.gov.au/api-documentation/tutorial
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API documentation:
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https://silo.longpaddock.qld.gov.au/api-documentation/reference
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API documentation:
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https://silo.longpaddock.qld.gov.au/api-documentation/reference
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API key registration:
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https://silo.longpaddock.qld.gov.au/register
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API key registration:
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https://silo.longpaddock.qld.gov.au/register
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Variable info:
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Variable info:
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Code Units Name
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---------------------------------------------------------------------------
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Code Units Name
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daily_rain mm Daily rainfall
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---------------------------------------------------------------------------
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monthly_rain mm Monthly rainfall
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daily_rain mm Daily rainfall
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max_temp Celsius Maximum temperature
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monthly_rain mm Monthly rainfall
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min_temp Celsius Minimum temperature
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max_temp Celsius Maximum temperature
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vp hPa Vapour pressure
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min_temp Celsius Minimum temperature
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vp_deficit hPa Vapour pressure deficit
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vp hPa Vapour pressure
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evap_pan mm Evaporation - Class A pan
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vp_deficit hPa Vapour pressure deficit
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evap_syn mm Evaporation - synthetic estimate
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evap_pan mm Evaporation - Class A pan
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evap_comb mm Evaporation - combination (synthetic estimate
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evap_syn mm Evaporation - synthetic estimate
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pre-1970, class A pan 1970 onwards)
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evap_comb mm Evaporation - combination (synthetic estimate
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evap_morton_lake mm Evaporation - Morton's shallow lake evap.
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pre-1970, class A pan 1970 onwards)
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radiation MJm-2 Solar radiation - total incoming downward
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evap_morton_lake mm Evaporation - Morton's shallow lake evap.
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shortwave radiation on a horizontal surface
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radiation MJm-2 Solar radiation - total incoming downward
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rh_tmax % Relative humidity at the time of max. temp.
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shortwave radiation on a horizontal surface
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rh_tmin % Relative humidity at the time of min. temp.
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rh_tmax % Relative humidity at the time of max. temp.
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et_short_crop mm Evapotranspiration - FAO56 short crop
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rh_tmin % Relative humidity at the time of min. temp.
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et_tall_crop mm Evapotranspiration - ASCE tall crop
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et_short_crop mm Evapotranspiration - FAO56 short crop
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et_morton_actual mm Evapotranspiration - Morton's areal actual
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et_tall_crop mm Evapotranspiration - ASCE tall crop
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evapotranspiration
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et_morton_actual mm Evapotranspiration - Morton's areal actual
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et_morton_potential mm Evapotranspiration - Morton's potential
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evapotranspiration
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evapotranspiration
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et_morton_potential mm Evapotranspiration - Morton's potential
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et_morton_wet mm Evapotranspiration - Morton's wet-environment
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evapotranspiration
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areal evapotranspiration over land
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et_morton_wet mm Evapotranspiration - Morton's wet-environment
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mslp hPa Mean sea level pressure
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areal evapotranspiration over land
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mslp hPa Mean sea level pressure
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"""
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"""
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unit_defs = {
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'daily_rain': 'mm',
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unit_defs = {
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'monthly_rain': 'mm',
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'daily_rain': 'mm',
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'max_temp': 'Celsius',
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'monthly_rain': 'mm',
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'min_temp': 'Celsius',
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'max_temp': 'Celsius',
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'vp': 'hPa',
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'min_temp': 'Celsius',
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'vp_deficit': 'hPa',
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'vp': 'hPa',
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'evap_pan': 'mm',
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'vp_deficit': 'hPa',
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'evap_syn': 'mm',
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'evap_pan': 'mm',
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'evap_comb': 'mm',
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'evap_syn': 'mm',
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'evap_morton_lake': 'mm',
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'evap_comb': 'mm',
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'radiation': 'MJm-2',
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'evap_morton_lake': 'mm',
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'rh_tmax': '%',
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'radiation': 'MJm-2',
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'rh_tmin': '%',
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'rh_tmax': '%',
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'et_short_crop': 'mm',
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'rh_tmin': '%',
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'et_tall_crop': 'mm',
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'et_short_crop': 'mm',
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'et_morton_actual': 'mm',
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'et_tall_crop': 'mm',
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'et_morton_potential': 'mm',
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'et_morton_actual': 'mm',
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'et_morton_wet': 'mm',
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'et_morton_potential': 'mm',
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'mslp': 'hPa',
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'et_morton_wet': 'mm',
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}
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'mslp': 'hPa',
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}
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# Validate inputs
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if (type(lat) and type(lon)) == type(station):
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# Validate inputs
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raise ValueError(
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if (type(lat) and type(lon)) == type(station):
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"'lat' and 'lon' must be provided if 'station' is not specified.")
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raise ValueError(
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"'lat' and 'lon' must be provided if 'station' is not specified.")
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params = {
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'apikey': api_key,
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params = {
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'format': 'csv',
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'apikey': api_key,
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'start': start,
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'format': 'csv',
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'finish': finish,
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'start': start,
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'variables': ','.join(variables)
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'finish': finish,
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}
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'variables': ','.join(variables)
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}
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if station is not None:
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# Get observations from specified weather station
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if station is not None:
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params['station'] = station
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# Get observations from specified weather station
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else:
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params['station'] = station
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# Get observations from specified coordinates
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else:
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params['lat'] = lat
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# Get observations from specified coordinates
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params['lon'] = lon
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params['lat'] = lat
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params['lon'] = lon
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base_url = 'https://siloapi.longpaddock.qld.gov.au/pointdata'
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r = requests.get(base_url, params=params)
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base_url = 'https://siloapi.longpaddock.qld.gov.au/pointdata'
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text = r.content.decode()
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r = requests.get(base_url, params=params)
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df = pd.read_csv(StringIO(text))
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text = r.content.decode()
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df = pd.read_csv(StringIO(text), parse_dates=['date'])
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# Add units to columns names
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df = df.set_index('date')
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if units:
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labels = {}
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# Add units to columns names
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for key, val in unit_defs.items():
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if units:
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labels[key] = '{}_{}'.format(key, val)
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labels = {}
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df = df.rename(columns=labels)
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for key, val in unit_defs.items():
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labels[key] = '{}_{}'.format(key, val)
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return df
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df = df.rename(columns=labels)
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# Write to csv
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if output:
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df.to_csv(output)
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return df
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