removes geopandas from some examples

docs/source/examples/assignment_workflows/plot_route_choice_basics.py

@@ -169,11 +169,10 @@
 # let's define a function to plot assignment results
 def plot_results(link_loads):
     import folium
-    import geopandas as gpd
 
     link_loads = link_loads[link_loads.tot > 0]
     max_load = link_loads["tot"].max()
-    links = gpd.GeoDataFrame(project.network.links.data, crs=4326)
+    links = project.network.links.data
     loaded_links = links.merge(link_loads, on="link_id", how="inner")
 
     loads_lyr = folium.FeatureGroup("link_loads")

docs/source/examples/assignment_workflows/plot_route_choice_set.py

@@ -101,7 +101,6 @@
 # %%
 # Now we will plot the paths we just created for the second OD pair
 import folium
-import geopandas as gpd
 
 # %%
 # Let's create a separate for each route so we can visualize one at a time
@@ -115,8 +114,8 @@
 
 # %%
 # We get the data we will use for the plot: Links, Nodes and the route choice set
-links = gpd.GeoDataFrame(project.network.links.data, crs=4326)
-nodes = gpd.GeoDataFrame(project.network.nodes.data, crs=4326)
+links = project.network.links.data
+nodes = project.network.nodes.data
 
 plot_routes = choice_set[(choice_set["origin id"] == 77011)]["route set"].values
 

docs/source/examples/assignment_workflows/plot_subarea_analysis.py

@@ -17,7 +17,6 @@
 import itertools
 
 import pandas as pd
-import geopandas as gpd
 import numpy as np
 import folium
 
@@ -110,7 +109,7 @@
 # # the union of their geometry. It's best to choose a polygon that avoids any unnecessary intersections with links as
 # the resource requirements of this approach grow quadratically with the number of links cut.
 zones_of_interest = [29, 30, 31, 32, 33, 34, 37, 38, 39, 40, 49, 50, 51, 52, 57, 58, 59, 60]
-zones = gpd.GeoDataFrame(project.zoning.data).set_index("zone_id")
+zones = project.zoning.data.set_index("zone_id")
 zones = zones.loc[zones_of_interest]
 zones.head()
 
@@ -164,7 +163,7 @@
 def plot_results(link_loads):
     link_loads = link_loads[link_loads.tot > 0]
     max_load = link_loads["tot"].max()
-    links = gpd.GeoDataFrame(project.network.links.data, crs=4326)
+    links = project.network.links.data
     loaded_links = links.merge(link_loads, on="link_id", how="inner")
 
     loads_lyr = folium.FeatureGroup("link_loads")
@@ -202,18 +201,18 @@ def plot_results(link_loads):
 
 # %%
 # We take the union of this GeoDataFrame as our polygon.
-poly = zones.unary_union
+poly = zones.union_all()
 poly
 
 # %%
 # It's useful later on to know which links from the network cross our polygon.
-links = gpd.GeoDataFrame(project.network.links.data)
+links = project.network.links.data
 inner_links = links[links.crosses(poly.boundary)].sort_index()
 inner_links.head()
 
 # %%
 # As well as which nodes are interior.
-nodes = gpd.GeoDataFrame(project.network.nodes.data).set_index("node_id")
+nodes = project.network.nodes.data.set_index("node_id")
 inside_nodes = nodes.sjoin(zones, how="inner").sort_index()
 inside_nodes.head()
 

docs/source/examples/creating_models/plot_create_from_layer.py

@@ -132,37 +132,12 @@
     new_link.save()
 
 # %%
-# We grab all the links data as a Pandas DataFrame so we can process it easier
+# We grab all the links data as a geopandas GeoDataFrame so we can process it easier
 links = project.network.links.data
 
 # %%
-# We create a Folium layer
-network_links = folium.FeatureGroup("links")
-
-#%%
-# We do some Python magic to transform this dataset into the format required by Folium.
-# We are only getting `link_id` and `link_type` into the map, but we could get other pieces of info as well
-
-# %%
-for i, row in links.iterrows():
-    points = row.geometry.wkt.replace("LINESTRING ", "").replace("(", "").replace(")", "").split(", ")
-    points = "[[" + "],[".join([p.replace(" ", ", ") for p in points]) + "]]"
-    # We need to take from x/y to lat/long
-    points = [[x[1], x[0]] for x in eval(points)]
-
-    line = folium.vector_layers.PolyLine(
-        points, popup=f"<b>link_id: {row.link_id}</b>", tooltip=f"{row.link_type}", color="blue", weight=10
-    ).add_to(network_links)
-
-# %%
-# We get the center of the region we are working with some SQL magic
-curr = project.conn.cursor()
-curr.execute("select avg(xmin), avg(ymin) from idx_links_geometry")
-long, lat = curr.fetchone()
-
-# %%
-map_osm = folium.Map(location=[lat, long], zoom_start=15)
-network_links.add_to(map_osm)
+# Let's plot our network!
+map_osm = links.explore(color="blue", weight=10, tooltip="link_type", popup="link_id", name="links")
 folium.LayerControl().add_to(map_osm)
 map_osm
 

docs/source/examples/creating_models/plot_create_from_osm.py

@@ -37,41 +37,18 @@
 project.network.create_from_osm(place_name="Nauru")
 
 # %%
-# We can also choose to create a model from a polygon (which must be in `EPSG:4326`)
-# Or from a Polygon defined by a bounding box, for example.
+# We can also choose to create a model from a polygon (which must be in ``EPSG:4326``)
+# or from a Polygon defined by a bounding box, for example.
 
 # project.network.create_from_osm(model_area=box(-112.185, 36.59, -112.179, 36.60))
 
 # %%
-# We grab all the links data as a Pandas DataFrame so we can process it easier
+# We grab all the links data as a geopandas GeoDataFrame so we can process it easier
 links = project.network.links.data
 
 # %%
-# We create a Folium layer
-network_links = folium.FeatureGroup("links")
-
-# %%
-# We do some Python magic to transform this dataset into the format required by Folium.
-# We are only getting link_id and link_type into the map, but we could get other pieces of info as well.
-for i, row in links.iterrows():
-    points = row.geometry.wkt.replace("LINESTRING ", "").replace("(", "").replace(")", "").split(", ")
-    points = "[[" + "],[".join([p.replace(" ", ", ") for p in points]) + "]]"
-    # we need to take from x/y to lat/long
-    points = [[x[1], x[0]] for x in eval(points)]
-
-    line = folium.vector_layers.PolyLine(
-        points, popup=f"<b>link_id: {row.link_id}</b>", tooltip=f"{row.link_type}", color="blue", weight=10
-    ).add_to(network_links)
-
-# %%
-# We get the center of the region we are working with some SQL magic
-curr = project.conn.cursor()
-curr.execute("select avg(xmin), avg(ymin) from idx_links_geometry")
-long, lat = curr.fetchone()
-
-# %%
-map_osm = folium.Map(location=[lat, long], zoom_start=14)
-network_links.add_to(map_osm)
+# Let's plot our network!
+map_osm = links.explore(color="blue", weight=10, tooltip="link_type", popup="link_id", name="links")
 folium.LayerControl().add_to(map_osm)
 map_osm
 

docs/source/examples/visualization/plot_display.py

@@ -29,7 +29,7 @@
 project = create_example(fldr, "nauru")
 
 # %%
-# We grab all the links data as a Pandas dataframe so we can process it easier
+# We grab all the links data as a geopandas GeoDataFrame so we can process it easier
 links = project.network.links.data
 nodes = project.network.nodes.data