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processdata/maps.py

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+# File for creation of plotly maps(figs).
+# You can use the plotly builtin fig.show() method to map locally.
+import json
+from urllib.request import urlopen
+
+import plotly.graph_objs as go
+from plotly.offline import plot
+
+from . import getdata
+
+
+def usa_map():
+    # Map of USA subdivided by FIPS-codes (counties), showing cases per-capita basis
+    # Reference: https://plotly.com/python/reference/#choroplethmapbox
+    with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
+        counties = json.load(response)
+
+    df = getdata.usa_counties()
+    df.drop([2311], inplace=True)
+
+    fig = go.Figure(
+        go.Choroplethmapbox(
+            geojson = counties, 
+            locations = df.fips,
+            z = df['cases/capita'],
+            marker_opacity = 0.75,
+            marker_line_width = 0,
+            colorscale = [[0, '#FFFAF4'], [.005, '#FFE4CC'], [.030, '#DC654F'], [.060, '#CA3328'], [.080, '#B80000'], [.100, '#7C100C'], [.150, '#580000'], [.175, '#300000'], [1, '#170707']]
+        )
+    )
+
+    fig.update_layout(
+        mapbox_style = 'carto-positron', 
+        paper_bgcolor='rgba(0,0,0,0)', 
+        mapbox_zoom=2.75, 
+        mapbox_center = {'lat': 37.0902, 'lon': -95.7129}, 
+        margin = dict(t=0, l=0, r=0, b=0)
+    )
+    plot_div = plot(fig, include_plotlyjs=False, output_type='div', config={'displayModeBar': False})
+
+    return plot_div