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dbhydro_py.py
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import pandas as pd
def get_river(period='1week', dbkey='91686/91687/91401/91399/91656/AL760/WH036',):
'''
period: options are 'year', 'month', '1week', '3day', 'today',
'uspec&v_start_date=YYYYMMDD&v_end_date=YYYYMMDD'
dbkey: dbhydro code for var/station. to get other codes see link on dbkeys
________________________________________________________
documentation : pages 87-89 https://www.sfwmd.gov/sites/default/files/dbhydro_browser_user_documentation.pdf
dbkeys: https://my.sfwmd.gov/dbhydroplsql/show_dbkey_info.show_dbkeys_matched?v_station=L001&v_js_flag=N
________________________________________________________
'''
link = [
"http://my.sfwmd.gov/dbhydroplsql/web_io.report_process?"+
"v_period=%s&" % period+
"v_report_type=format6&"+
"v_target_code=file_csv&"+
"v_run_mode=onLine&v_js_flag=Y&"+
"v_dbkey=%s" % dbkey
]
print(link)
skip = len(dbkey.split('/'))+2 # the number of blabla lines will be the number of variables + 2
df = pd.read_csv(link[0], skiprows=skip, parse_dates=['Daily Date'])
df.to_csv('raw.csv')
# [ 'S65EX1_S', 'S65E_S', 'S84_S', 'S84XS', 'S154C_C', 'S154_C', 'G34_C', ]
var_key = {
'91686': 'Mean flow [cfs] S84X_S',
'91687': 'Mean flow [cfs] S84_S',
'91401': 'Mean flow [cfs] S154_C',
'91399': 'Mean flow [cfs] S154C_C',
'91656': 'Mean flow [cfs] S65E_S',
'AL760': 'Mean flow [cfs] S65EX1_S',
'WH036': 'Mean flow [cfs] FISHCR',
'AL761': 'Flow [cfs] S65EX1_S',
}
frames = []
for ID in df['DBKEY'].unique():
sub = df.loc[df['DBKEY']==ID].set_index('Daily Date')
cname = sub['Station']
flow = sub['Data Value'].rename(cname[0])
# sub = sub.loc[~sub.index.duplicated(keep='first')]
frames.append(flow)
return pd.concat(frames, axis=1)
def get_ts(period='1week', station='L001', dvar=['Date', 'Val'], dbkey='IX837/IX845/IX847'):
'''
period: options are 'year', 'month', '1week', '3day', 'today',
'uspec&v_start_date=YYYYMMDD&v_end_date=YYYYMMDD'
dbkey: (Optional, is station is not given) dbhydro code for var/station. to get other codes see link on dbkeys
station: Optional. to get a pre selected subset of data from a station.
Optios are: L001, L005
________________________________________________________
documentation : pages 87-89 https://www.sfwmd.gov/sites/default/files/dbhydro_browser_user_documentation.pdf
dbkeys: https://my.sfwmd.gov/dbhydroplsql/show_dbkey_info.show_dbkeys_matched?v_station=L001&v_js_flag=N
________________________________________________________
'''
if station is 'L001':
dbkey = 'IX837/IX845/IX847/UT737/KV264/KV247'
elif station is 'L005':
dbkey = 'IX857/IX864/IX866/UT739/KV266/KV249/'
else:
if not dbkey:
print('Only L001 and L005 stations preset. Provide station or dbkey.')
link = [
"http://my.sfwmd.gov/dbhydroplsql/web_io.report_process?"+
"v_period=%s&" % period+
"v_report_type=format6&"+
"v_target_code=file_csv&"+
"v_run_mode=onLine&v_js_flag=Y&"+
"v_dbkey=%s" % dbkey
]
print(link)
skip = len(dbkey.split('/'))+2 # the number of blabla lines will be the number of variables + 2
df = pd.read_csv(link[0], skiprows=skip,
usecols=[0,2,3,],
names = [dvar[0], 'DBKEY', dvar[1]],
parse_dates=[dvar[0]]
)
var_key = {
# L001
'IX837': 'Air Temp [ºC]',
'IX845': 'Rain [in]',
'IX847': 'Wind speed [mph]',
'UT737': 'Wind direction [degrees clockwise from North]',
'KV264': 'VECTOR WIND DIRECTION',
'KV247': 'VECTOR WIND SPEED',
#L005
'IX857': 'Air Temp [ºC]',
'IX864': 'Rain [in]',
'IX866': 'Wind speed [mph]',
'UT739': 'Wind direction [degrees clockwise from North]',
'KV266': 'VECTOR WIND DIRECTION',
'KV249': 'VECTOR WIND SPEED',
# '12515': 'Rain [in/day]'
}
df.replace({'DBKEY': var_key}, inplace=True)
frames = []
for name in df['DBKEY'].unique():
sub = df.loc[df['DBKEY']==name].rename(columns={dvar[1]: name}).set_index(dvar[0])
sub = sub.loc[~sub.index.duplicated(keep='first')]
frames.append(sub.drop(columns='DBKEY'))
return pd.concat(frames, axis=1)