I am trying to create a map showing the progressive lockdown measures globally using a date slider. So far I was able to create the map for a static date but my attempt at the slider doesn't work because it seems to only accept integers or floats instead of a date range (Date_slider = pnw.IntSlider(start=0,end=365,value=0)
Essentially, i want to create the map found here: https://www.bsg.ox.ac.uk/research/research-projects/coronavirus-government-response-tracker
import pandas as pd
import geopandas as gpd
import json
import matplotlib as mpl
import pylab as plt
from bokeh.io import output_file, show, output_notebook, export_png
from bokeh.models import ColumnDataSource, GeoJSONDataSource, LinearColorMapper, ColorBar
from bokeh.plotting import figure
from bokeh.palettes import brewer
import panel as pn
import panel.widgets as pnw
import descartes
output_notebook()
pn.extension()
Read shape file
shapefile = '/Users/sam/Desktop/ne_110m_admin_0_countries/ne_110m_admin_0_countries.shp'
gdf = gpd.read_file(shapefile)[['ADMIN', 'ADM0_A3', 'geometry']]
gdf.columns = ['country', 'country_code', 'geometry']
gdf = gdf.drop(gdf.index[159])
Read data
def get_dataset(name,key=None,Date=None):
df = pd.read_csv(r'/Users/sam/Desktop/Big Data Project/covid-stringency-index-2.csv')
if Date is not None:
df = df[df['Date'] == Date]
#Merge dataframes gdf and df_2016.
if key is None:
key = df.columns[2]
merged = gdf.merge(df, left_on = 'country', right_on = 'Entity', how = 'left')
merged[key] = merged[key].fillna(0)
return merged, key
plot with matplotlib
datasetname='Lockdown Measures'
df,key = get_dataset(datasetname, Date='Jul 10, 2020')
fig, ax = plt.subplots(1, figsize=(14, 8))
df.plot(column=key, cmap='OrRd', linewidth=1.0, ax=ax, edgecolor='Black')
ax.axis('off')
ax.set_title('%s Jul 10, 2020' %datasetname, fontsize=25)
plt.tight_layout()
plt.savefig('test_map.png',dpi=150)
Output: https://i.stack.imgur.com/6GrbF.png
Plot with Bokeh
def get_geodatasource(gdf):
"""Get getjsondatasource from geopandas object"""
json_data = json.dumps(json.loads(gdf.to_json()))
return GeoJSONDataSource(geojson = json_data)
def map_dash():
"""Map dashboard"""
from bokeh.models.widgets import DataTable
map_pane = pn.pane.Bokeh(width=600)
data_select = pnw.Select(name='dataset',options=list(df))
Date_slider = pnw.IntSlider(start=0,end=365,value=0)
def update_map(event):
gdf,key = get_dataset(name=data_select.value,Date=Date_slider.value)
map_pane.object = bokeh_plot_map(gdf, key)
return
Date_slider.param.watch(update_map,'value')
Date_slider.param.trigger('value')
data_select.param.watch(update_map,'value')
app = pn.Column(pn.Row(data_select,Date_slider),map_pane)
return app
app = map_dash()
app
