Download data as anonymous user
from https://hydrometrie.wallonie.be/ calling Kisters webservices
@author : Pierre Archambeau - 2024
Load modules
from datetime import datetime as dt
import matplotlib.pyplot as plt
import pandas as pd
from wolfhece.hydrometry import kiwis
from wolfhece.hydrometry.kiwis import hydrometry, station_fields as sf, timeseries_fields as ts
Create anonymous access to SPW web services
db = hydrometry()
Print available columns in stations
print(db)
Columns in stations :
site_no
station_no
station_name
station_id
station_local_x
station_local_y
station_latitude
station_longitude
river_name
station_gauge_datum
CATCHMENT_SIZE
BV_DCE
Get all stations with flow rate measurements
“Official” groups
Available fields :
station_name == name used on hydrometrie.wallonie.be
station_no == code identified on hydrometrie.wallonie.be
station_id == internal index
ts_id == id of the timeserie
ts_name == name of the timeserie
parametertype_id
parametertype_id
Return :
pandas dataframe
stations = db.get_timeseries_group('flowrate','1h')
print(stations.columns)
Index(['station_name', 'station_no', 'station_id', 'ts_id', 'ts_name',
'parametertype_id', 'parametertype_name'],
dtype='object')
Get ts_id for a specific station
amay_byname = stations[stations[sf.STATION_NAME.value]=='AMAY']
amay_byid = stations[stations[sf.STATION_ID.value]=='7132']
tsid = int(amay_byname[ts.TS_ID.value][0])
print(tsid)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
File D:\ProgrammationGitLab\python3.10\lib\site-packages\pandas\core\indexes\base.py:3805, in Index.get_loc(self, key)
3804 try:
-> 3805 return self._engine.get_loc(casted_key)
3806 except KeyError as err:
File index.pyx:167, in pandas._libs.index.IndexEngine.get_loc()
File index.pyx:196, in pandas._libs.index.IndexEngine.get_loc()
File pandas\\_libs\\hashtable_class_helper.pxi:2606, in pandas._libs.hashtable.Int64HashTable.get_item()
File pandas\\_libs\\hashtable_class_helper.pxi:2630, in pandas._libs.hashtable.Int64HashTable.get_item()
KeyError: 0
The above exception was the direct cause of the following exception:
KeyError Traceback (most recent call last)
Cell In[5], line 4
1 amay_byname = stations[stations[sf.STATION_NAME.value]=='AMAY']
2 amay_byid = stations[stations[sf.STATION_ID.value]=='7132']
----> 4 tsid = int(amay_byname[ts.TS_ID.value][0])
6 print(tsid)
File D:\ProgrammationGitLab\python3.10\lib\site-packages\pandas\core\series.py:1112, in Series.__getitem__(self, key)
1109 return self._values[key]
1111 elif key_is_scalar:
-> 1112 return self._get_value(key)
1114 # Convert generator to list before going through hashable part
1115 # (We will iterate through the generator there to check for slices)
1116 if is_iterator(key):
File D:\ProgrammationGitLab\python3.10\lib\site-packages\pandas\core\series.py:1228, in Series._get_value(self, label, takeable)
1225 return self._values[label]
1227 # Similar to Index.get_value, but we do not fall back to positional
-> 1228 loc = self.index.get_loc(label)
1230 if is_integer(loc):
1231 return self._values[loc]
File D:\ProgrammationGitLab\python3.10\lib\site-packages\pandas\core\indexes\base.py:3812, in Index.get_loc(self, key)
3807 if isinstance(casted_key, slice) or (
3808 isinstance(casted_key, abc.Iterable)
3809 and any(isinstance(x, slice) for x in casted_key)
3810 ):
3811 raise InvalidIndexError(key)
-> 3812 raise KeyError(key) from err
3813 except TypeError:
3814 # If we have a listlike key, _check_indexing_error will raise
3815 # InvalidIndexError. Otherwise we fall through and re-raise
3816 # the TypeError.
3817 self._check_indexing_error(key)
KeyError: 0
Get time serie between 2 dates
Info : maximum download = 250.000 values The routine will split the interval if necessary.
Return :
pandas timeserie
ts = db.timeseries(fromdate=dt(1960,1,1), todate=dt(2022,2,1), ts_id = tsid)
1960-01-01 00:00:00 1982-10-25 08:00:00
1982-10-25 08:00:00 2005-08-18 16:00:00
2005-08-18 16:00:00 2022-02-01 00:00:00
ts.plot()
<AxesSubplot: xlabel='Timestamp'>
Exploring the database more deeply
#Get all time series available for a specific station
id,df = db.timeseries_list(stationcode='7132')
# id,df = db.timeseries_list(stationname='AMAY')
#Select only flow rate "Q" (other possibilities : "H" or "v")
flowrate_ts = df[df['parametertype_name']=='Q']['ts_name']
flowrate_ts[flowrate_ts.str.contains('Complet')]
14 05a-Debit ultrason.Complet.Alarmes
17 05-Debit ultrason.Complet
Name: ts_name, dtype: object
Get data
fromdate=dt(2021,1,1)
todate=dt(2022,2,1)
ts = db.timeseries(stationname='AMAY', fromdate=fromdate, todate=todate, ts_name='05-Debit ultrason.Complet')
ts_off = db.timeseries(fromdate=fromdate, todate=todate, ts_id = tsid)
fig, ax = plt.subplots(1,2)
fig.set_size_inches(20,8)
ax[0].plot(ts)
ax[1].plot(ts_off)
[<matplotlib.lines.Line2D at 0x2253606d120>]
