reformat

content/course/modelisation/0_preprocessing.Rmd

@@ -166,7 +166,7 @@ En l'occurrence, on peut utiliser `plotly` pour tenir compte de la population:
 
 ```{python, include = TRUE, echo=TRUE}
 import plotly
-import plotly.graph_objects as go
+import plotly.graph_objects as pgo
 import pandas as pd
 import geopandas as gpd
 
@@ -195,20 +195,31 @@ colors = ['#FF0000', '#0000FF']
 df['color'] = df['winner'].replace(color_dict)
 df['size'] = df['CENSUS_2010_POP']/6000
 
-fig_plotly = go.Figure(data=go.Scattergeo(
-              locationmode = 'USA-states',
-    lon=df["lon"], lat=df["lat"],
-    text = df["text"],
-    mode = 'markers',
-    marker_color = df["color"],
-    marker_size = df['size'],
+df['color'] = df['winner'].replace(color_dict)
+df['size'] = df['CENSUS_2010_POP']/6000
+df['text'] = df["county_name"] + '<br>Population ' + (df['CENSUS_2010_POP']/1e3).astype(str)+' thousands'
+
+fig_plotly = pgo.Figure(
+  data=pgo.Scattergeo(
+      locationmode = 'USA-states',
+      lon=df["lon"], lat=df["lat"],
+      text = df["text"],
+      mode = 'markers',
+      marker_color = df["color"],
+      marker_size = df['size']
+    )
+)
+```
+
+```{python, include = TRUE, echo=TRUE}
+fig_plotly.update_traces(
                   marker = dict(
               opacity=0.5,
               line_color='rgb(40,40,40)',
               line_width=0.5,
               sizemode = 'area'
                   )
-    ))
+)
 
 fig_plotly.update_layout(
         title_text = "Reproduction of the \"Acres don't vote, people do\" map <br>(Click legend to toggle traces)",