Python 交互式地图不'；我没有出现

我想创建一个像X一样有标记的地图

因此，我尝试使用

geoviews

绘制地图：

import os, numpy as np, pandas as pd, cartopy.crs as ccrs, bokeh
import holoviews as hv, geoviews as gv, datashader as ds

from colorcet import bmy
from holoviews.util import Dynamic
from holoviews.operation.datashader import rasterize, datashade

hv.extension('bokeh', width=100)

from ast import literal_eval
dictlist = literal_eval(df.results[0])
candidates = [result['name'] for result in dictlist]

def isolate_result(candidate,df_results):
    '''get results of a candidate'''
    for index, value in df_results.items():
        result = [result['pct'] for result in literal_eval(value) if result['name'] == candidate][0]
        df_results.at[index] = result

def get_df(candidate):
    df = gpd.read_file('./data/2012-Election.json')
    df['results'] = get_result(candidate, df['results'])
    return df

def get_plot(ticker):
    df = get_df(ticker)
    merged_json = json.loads(df.to_json())#Convert to String like object.
    json_data = json.dumps(merged_json)
    geosource = GeoJSONDataSource(geojson = json_data)

    #Input GeoJSON source that contains features for plotting.
    palette = brewer['YlGnBu'][8]#Reverse color order so that dark blue is highest turnout.
    palette = palette[::-1]#Instantiate LinearColorMapper that linearly maps numbers in a range, into a sequence of colors.
    color_mapper = LinearColorMapper(palette = palette, low = 0, high = 40)#Define custom tick labels for color bar.
    tick_labels = {'0': '0%', '5': '5%', '10':'10%', '15':'15%', '20':'20%', '25':'25%', '30':'30%','35':'35%', '40': '>40%'}#Create color bar. 
    color_bar = ColorBar(color_mapper=color_mapper, label_standoff=8,width = 500, height = 20,
    border_line_color=None,location = (0,0), orientation = 'horizontal', major_label_overrides = tick_labels)#Create figure object.

    p = figure(title = 'Election Results', plot_height = 600 , plot_width = 950, toolbar_location = None)
    p.xgrid.grid_line_color = None
    p.ygrid.grid_line_color = None#Add patch renderer to figure. 
    p.patches('xs','ys', source = geosource,fill_color = {'field' :'resuts', 'transform' : color_mapper},
              line_color = 'black', line_width = 0.25, fill_alpha = 1)#Specify figure layout.
    p.add_layout(color_bar, 'below')#Display figure inline in Jupyter Notebook.
    output_notebook()#Display figure.
    show(p)
    return p

interact = pn.interact(get_plot, ticker=candidates)

pn.Row(
    pn.Column(title, interact[0]),
    interact[1]
)

但是，当我使用

get\u plot（）

绘制地图时，效果非常好