geopandas scatter examples

Author: nicolaskruchten

doc/python/choropleth-maps.md

@@ -166,7 +166,7 @@ fig.show()
 
 ### Using GeoPandas Data Frames
 
-`px.choropleth` accepts the `geometry` of a GeoPandas data frame as the input to `geojson`.
+`px.choropleth` accepts the `geometry` of a GeoPandas data frame as the input to `geojson` if the `geometry` contains polygons.
 
 ```python
 import plotly.express as px

doc/python/mapbox-county-choropleth.md

@@ -139,9 +139,27 @@ fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
 fig.show()
 ```
 
+### Discrete Colors
+
+In addition to [continuous colors](/python/colorscales/), we can [discretely-color](/python/discrete-color/) our choropleth maps by setting `color` to a non-numerical column, like the name of the winner of an election.
+
+```python
+import plotly.express as px
+
+df = px.data.election()
+geojson = px.data.election_geojson()
+
+fig = px.choropleth_mapbox(df, geojson=geojson, color="winner",
+                           locations="district", featureidkey="properties.district",
+                           center={"lat": 45.5517, "lon": -73.7073},
+                           mapbox_style="carto-positron", zoom=9)
+fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
+fig.show()
+```
+
 ### Using GeoPandas Data Frames
 
-`px.choropleth_mapbox` accepts the `geometry` of a GeoPandas data frame as the input to `geojson`.
+`px.choropleth_mapbox` accepts the `geometry` of a GeoPandas data frame as the input to `geojson` if the `geometry` contains polygons.
 
 ```python
 import plotly.express as px
@@ -163,24 +181,6 @@ fig = px.choropleth_mapbox(geo_df,
 fig.show()
 ```
 
-### Discrete Colors
-
-In addition to [continuous colors](/python/colorscales/), we can [discretely-color](/python/discrete-color/) our choropleth maps by setting `color` to a non-numerical column, like the name of the winner of an election.
-
-```python
-import plotly.express as px
-
-df = px.data.election()
-geojson = px.data.election_geojson()
-
-fig = px.choropleth_mapbox(df, geojson=geojson, color="winner",
-                           locations="district", featureidkey="properties.district",
-                           center={"lat": 45.5517, "lon": -73.7073},
-                           mapbox_style="carto-positron", zoom=9)
-fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
-fig.show()
-```
-
 ### Choropleth map using plotly.graph_objects and carto base map (no token needed)
 
 If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Choroplethmapbox` class from `plotly.graph_objects`](/python/graph-objects/).

doc/python/scatter-plots-on-maps.md

@@ -5,8 +5,8 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.1'
-      jupytext_version: 1.1.1
+      format_version: '1.2'
+      jupytext_version: 1.4.2
   kernelspec:
     display_name: Python 3
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.6.7
+    version: 3.7.7
   plotly:
     description: How to make scatter plots on maps in Python. Scatter plots on maps
       highlight geographic areas and can be colored by value.
@@ -66,6 +66,24 @@ fig = px.scatter_geo(df, locations="iso_alpha",
 fig.show()
 ```
 
+### Basic Example with GeoPandas
+
+`px.scatter_geo` can work well with GeoPandas dataframes whose `geometry` is of type `Point`.
+
+```python
+import plotly.express as px
+import geopandas as gpd
+
+geo_df = gpd.read_file(gpd.datasets.get_path('naturalearth_cities'))
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+fig = px.scatter_geo(geo_df, 
+                    lat=geo_df.geometry.y, 
+                    lon=geo_df.geometry.x,
+                    hover_name="name")
+fig.show()
+```
+
 ### U.S. Airports Map
 
 Here we show how to use `go.Scattergeo` from `plotly.graph_objects`.

doc/python/scattermapbox.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.2'
-      jupytext_version: 1.3.2
+      jupytext_version: 1.4.2
   kernelspec:
     display_name: Python 3
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.7.3
+    version: 3.7.7
   plotly:
     description: How to make scatter plots on Mapbox maps in Python.
     display_as: maps
@@ -52,6 +52,25 @@ fig = px.scatter_mapbox(df, lat="centroid_lat", lon="centroid_lon",     color="p
 fig.show()
 ```
 
+### Basic Example with GeoPandas
+
+`px.scatter_mapbox` can work well with GeoPandas dataframes whose `geometry` is of type `Point`.
+
+```python
+import plotly.express as px
+import geopandas as gpd
+
+geo_df = gpd.read_file(gpd.datasets.get_path('naturalearth_cities'))
+
+px.set_mapbox_access_token(open(".mapbox_token").read())
+fig = px.scatter_mapbox(geo_df, 
+                        lat=geo_df.geometry.y, 
+                        lon=geo_df.geometry.x,
+                        hover_name="name",
+                        zoom=1)
+fig.show()
+```
+
 #### Basic Example
 
 ```python
@@ -228,4 +247,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/scattermapbox/ for more information and options!
+See https://plotly.com/python/reference/scattermapbox/ for more information and options!