Update app.py

app.py

@@ -1,58 +1,23 @@
+import altair as alt
 import streamlit as st
-import json
-import geopandas as gpd
-import pyproj
-import plotly.graph_objs as go
-polygon = gpd.read_file(r"\Downloads\CityBoundaries.shp")
 
-# project geopandas dataframe
-map_df = polygon
-map_df.to_crs(pyproj.CRS.from_epsg(4326), inplace=True)
-
-# reading in the points shapefile
-points = gpd.read_file(r"Downloads\USA_Major_Cities.shp")
-
-# project geopandas dataframe
-points.to_crs(pyproj.CRS.from_epsg(4326), inplace=True)
-
-# define lat, long for ponints
-Lat = points['Lat']
-Long = points['Long']
-
-# leases to geojson
-path = r"C:\Users\project\geojson.json"
-
-map_df.to_file(path, driver = "GeoJSON")
-with open(path) as geofile:
-    j_file = json.load(geofile)
-
-#index geojson
-i=1
-for feature in j_file["features"]:
-    feature ['id'] = str(i).zfill(2)
-    i += 1
-    
-# mapbox token
-mapboxt = 'MapBox Token'
-
-# define layers and plot map
-choro = go.Choroplethmapbox(z=map_df['STFIPS'], locations = map_df.index, colorscale = 'Viridis', geojson = j_file, text = map_df['NAME'], marker_line_width=0.1)
-     # Your choropleth data here
-
-
-scatt = go.Scattermapbox(lat=Lat,lon=Long,mode='markers+text',below='False', marker=dict( size=12, color ='rgb(56, 44, 100)'))
-     # Your scatter data here
-
-layout = go.Layout(title_text ='USA Cities', title_x =0.5, width=950, height=700,mapbox = dict(center= dict(lat=37, lon=-95),accesstoken= mapboxt, zoom=4,style="stamen-terrain"))
-    
-
-# streamlit multiselect widget
-layer1 = st.multiselect('Layer Selection', [choro, scatt], format_func=lambda x: 'Polygon' if x==choro else 'Points')
-
-
-#st.write('Layer 1:', layer1)
-fig = go.Figure(data=layer1, layout=layout)
-
-
-# display streamlit
-st.plotly_chart(fig)
+african_countries = alt.topo_feature(
+        "https://raw.githubusercontent.com/deldersveld/topojson/master/continents/africa.json",
+        "continent_Africa_subunits",
+    )
+africa_chart = (
+    alt.Chart(african_countries)
+    .mark_geoshape(stroke="white", strokeWidth=2)
+    .encode(
+        color="value:Q",
+        tooltip=[
+            alt.Tooltip("properties.geounit:O", title="Country name"),
+            alt.Tooltip("value:Q", title="Indicator value"),
+        ],
+    )
+    .transform_lookup(
+        lookup="properties.geounit",
+        from_=alt.LookupData(filtered_data, "Geo Name", ["value"]),
+    )
+)
+st.altair_chart(africa_chart)