Fixed plot title

notebooks/environment.ipynb

@@ -92,7 +92,63 @@
    "outputs": [],
    "source": [
     "col = 'airtemp °C'\n",
-    "stations.join(air_quality).dropna(subset=[col]).hvplot(geo=True, tiles='StamenToner', c=col, size=500, title=col.title())"
+    "stations = stations.join(air_quality).dropna(subset=[col])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stations.hvplot(geo=True, tiles='StamenToner', c=col, size=500, title=col.title())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from holoviews.selection import link_selections"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "my_map = stations.hvplot(geo=True, tiles='CartoLight', c=col, cmap='Viridis', size=200, title=col.title(), width=400, height=250)\n",
+    "my_scatter = pd.DataFrame(stations).hvplot.scatter(x='airtemp °C', y='windspeed kmh', width=250, height=250)\n",
+    "my_hist = pd.DataFrame(stations).hvplot.hist('airtemp °C', width=250, height=250)\n",
+    "link_selections(my_map + my_hist + my_scatter , index_cols=['id'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import panel as pn"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def my_plot(my_col='airtemp °C'):\n",
+    "    try: \n",
+    "        my_map = stations.hvplot(geo=True, tiles='CartoLight', c=my_col, cmap='Viridis', size=200, title=my_col, width=400, height=250)\n",
+    "        my_hist = pd.DataFrame(stations).hvplot.hist(my_col, title=my_col, width=250, height=250)\n",
+    "        return link_selections(my_map + my_hist, index_cols=['id']) \n",
+    "    except:\n",
+    "        pass\n",
+    "kw = dict(my_col=air_quality.columns)\n",
+    "pn.interact(my_plot, **kw)"
    ]
   },
   {
@@ -105,7 +161,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -119,7 +175,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.8"
+   "version": "3.7.15"
   }
  },
  "nbformat": 4,

notebooks/geocoding.ipynb

@@ -107,7 +107,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "kw = dict(user_input=\"Giefinggasse 2, 1210 Wien\", buffer_meters=(0,10000))\n",
+    "kw = dict(user_input=\"Giefinggasse 2, 1210 Wien\", buffer_meters=(1,10000))\n",
     "pn.interact(my_plot, **kw)"
    ]
   },
@@ -147,7 +147,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.12"
+   "version": "3.7.15"
   }
  },
  "nbformat": 4,

notebooks/utils/dataaccess.py

@@ -133,7 +133,7 @@ def get_uber_movement_gdf():
     gdf['MOVEMENT_ID'] = gdf['MOVEMENT_ID'].astype(int)
     gdf.set_index('MOVEMENT_ID', inplace=True)
 
-    file = 'uber_vienna-statistical_areas-2020-1-All-MonthlyAggregate.zip'
+    file = 'data/uber_vienna-statistical_areas-2020-1-All-MonthlyAggregate.zip'
     url = 'https://github.com/anitagraser/ogd-at-lab-data/raw/main/uber/vienna-statistical_areas-2020-1-All-MonthlyAggregate.zip'
     if not exists(file):
         urlretrieve(url, file)

notebooks/wien-ogd.ipynb

@@ -8,9 +8,10 @@
     "\n",
     "[![Binder](http://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/anitagraser/ogd-at-lab/main?urlpath=lab/tree/notebooks/wien-ogd.ipynb)\n",
     "\n",
-    "\n",
     "<a href=\"https://www.data.gv.at/auftritte/?organisation=stadt-wien\"><img align=\"right\" src=\"./img/stadt-wien.png\"></a>\n",
     "\n",
+    "This notebook demonstrates the use of vector data provided via WFS. For instructions on using WMS, see the [webmapping notebook](webmapping.ipynb).\n",
+    "\n",
     "For more information on open government data in Vienna visit [digitales.wien.gv.at](https://digitales.wien.gv.at/site/open-data/)\n",
     "\n",
     "For a full list of available datasets go to [data.gv.at](https://www.data.gv.at/auftritte/?organisation=stadt-wien&searchterm=&formatFilter%5B%5D=WFS)\n",
@@ -95,7 +96,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "hvplot_with_buffer(gdf, 100, title='Citybike Stations') + hvplot_with_buffer(gdf2, 100, title='EV Charging Stations')"
+    "hvplot_with_buffer(gdf, 100, title='Bike Sharing Stations') + hvplot_with_buffer(gdf2, 100, title='EV Charging Stations')"
    ]
   },
   {
@@ -118,7 +119,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -132,7 +133,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.8"
+   "version": "3.7.15"
   }
  },
  "nbformat": 4,