Example notebook lizard

docs/examples.rst

@@ -11,7 +11,7 @@ Importing a single CSV-file downloaded from DINOLoket::
 
    import hydropandas as hpd
    fname = './tests/data/2019-Dino-test/Grondwaterstanden_Put/B33F0080001_1.csv'
-   gw = hpd.GroundwaterObs.from_dino(fname=fname, verbose=True)
+   gw = hpd.GroundwaterObs.from_dino(path=fname)
 
 
 Or for a zipfile::
@@ -22,8 +22,7 @@ Or for a zipfile::
                                          subdir='Grondwaterstanden_Put',
                                          suffix='1.csv',
                                          ObsClass=hpd.GroundwaterObs,
-                                         keep_all_obs=False,
-                                         verbose=False)
+                                         keep_all_obs=False)
 
 Example notebooks
 -----------------

docs/examples/06_lizard.nblink

@@ -0,0 +1,3 @@
+{
+    "path": "../../examples/06_lizard.ipynb"
+}

docs/index.rst

@@ -12,14 +12,15 @@ Supported data sources
 Currently supported datasources that can be read:
 
 - `BRO <https://www.broloket.nl>`_
-- `FEWS PI-XML <https://publicwiki.deltares.nl/display/FEWSDOC/The+Delft-Fews+Published+Interface>`_
 - `DINOLoket CSV <www.dinoloket.nl>`_
-- WISKI csv files
-- `Pastastore <https://github.com/pastas/pastastore>`_, for managing Pastas timeseries and models
+- `FEWS PI-XML <https://publicwiki.deltares.nl/display/FEWSDOC/The+Delft-Fews+Published+Interface>`_
+- IMOD groundwater models
 - `KNMI data <https://www.knmi.nl/kennis-en-datacentrum/achtergrond/data-ophalen-vanuit-een-script>`_
+- `Lizard <https://vitens.lizard.net>`_
 - MODFLOW groundwater models
-- IMOD groundwater models
+- `Pastastore <https://github.com/pastas/pastastore>`_, for managing Pastas timeseries and models
 - `Waterinfo <https://waterinfo.rws.nl>`_
+- WISKI csv files
 
 ObsCollection can be exported to:
 

hydropandas/extensions/accessor.py

@@ -1,4 +1,5 @@
 """Copied from ./pandas/core/accessor.py."""
+
 import warnings
 
 

hydropandas/extensions/plots.py

@@ -243,7 +243,7 @@ def interactive_map(
 
         # create map if no map is given
         if m is None:
-            m = folium.Map([northing, easting], zoom_start=zoom_start)
+            m = folium.Map([northing, easting], zoom_start=zoom_start, tiles=tiles)
 
         # get oc name if no legend name is given
         if legend_name is None:

hydropandas/io/knmi.py

@@ -10,6 +10,7 @@
  - read_knmi_timeseries_file: read a knmi txt file
 
 """
+
 import datetime as dt
 import logging
 import os

readme.md

@@ -32,10 +32,11 @@ The HydroPandas package also provides convenient read functions for Dutch hydrol
 - [DINO](https://www.dinoloket.nl)
 - FEWS PI-XML
 - [KNMI](https://www.knmi.nl/kennis-en-datacentrum/achtergrond/data-ophalen-vanuit-een-script)
+- [Lizard](https://vitens.lizard.net/)
 - MODFLOW groundwater models
 - IMOD groundwater models
 - [Pastastore](https://github.com/pastas/pastastore)
-- [waterinfo](https://waterinfo.rws.nl/)
+- [Waterinfo](https://waterinfo.rws.nl/)
 - WISKI csv files
 
 ## Install

tests/test_000_run_notebooks.py

@@ -1,4 +1,5 @@
 """run notebooks in the examples directory."""
+
 import os
 
 import nbformat

tests/test_003_calculations.py

@@ -49,9 +49,9 @@ def test_get_nearest_point():
     # every point must find itself as the nearest point
     dino_gw = ttf.test_obscollection_dinozip_gw()
     fl = ttf.test_obscollection_dinozip_wl()
-    dino_gw[
-        ["nearest point", "distance nearest point"]
-    ] = dino_gw.geo.get_nearest_point(fl)
+    dino_gw[["nearest point", "distance nearest point"]] = (
+        dino_gw.geo.get_nearest_point(fl)
+    )
 
 
 def test_get_nearest_polygon():
@@ -82,9 +82,9 @@ def test_get_nearest_polygon():
     )
     gdf = gpd.GeoDataFrame({"name": [1, 2], "geometry": [polygon1, polygon2]})
 
-    dino_gw[
-        ["nearest polygon", "distance nearest polygon"]
-    ] = dino_gw.geo.get_nearest_polygon(gdf)
+    dino_gw[["nearest polygon", "distance nearest polygon"]] = (
+        dino_gw.geo.get_nearest_polygon(gdf)
+    )
     assert (dino_gw["nearest polygon"] == 0.0).all()
     assert (dino_gw["distance nearest polygon"] == 0.0).all()