我是这里的新手，我是一名刚开始进行Web开发的在校学生。目前，我正在使用Django，但无法弄清楚如何在首页上显示存储在“ views.py”中的数据可视化库。
应该只将每个图形存储在模型中，还是可以在'views.py'中遍历每个函数并将其输出到首页。我正在尝试使独立示例中的首页像this。
抱歉，这听起来太基础了，但是我已经被卡住了很长时间了！ 非常感谢你！
{ def simple_chart（request）：
plot = figure()
plot.circle([1,2], [3,4])
# select the tools we want
TOOLS = "pan,wheel_zoom,box_zoom,reset,save"
script, div = components(plot, CDN)
return render(request, "Bokeh/bokeh_chart.html", {"the_script": script, "the_div": div})
def hexbin_chart（request）：
n = 500
x = 2 + 2*np.random.standard_normal(n)
y = 2 + 2*np.random.standard_normal(n)
p = figure(title="Hexbin for 500 points", match_aspect=True, toolbar_location="below",
tools="wheel_zoom,reset,pan,box_zoom,save", background_fill_color='#440154')
p.grid.visible = False
r, bins = p.hexbin(x, y, size=0.5, hover_color="pink", hover_alpha=0.8)
p.circle(x, y, color="white", size=1)
p.add_tools(HoverTool(
tooltips=[("count", "@c"), ("(q,r)", "(@q, @r)")],
mode="mouse", point_policy="follow_mouse", renderers=[r]
))
script, div = components(p, CDN)
return render(request, "Bokeh/bokeh_chart.html", {"the_script": script, "the_div": div})
def bar_dodged_chart（请求）：
fruits = ['Apples', 'Pears', 'Nectarines', 'Plums', 'Grapes', 'Strawberries']
years = ['2015', '2016', '2017']
data = {'fruits': fruits,
'2015': [2, 1, 4, 3, 2, 4],
'2016': [5, 3, 3, 2, 4, 6],
'2017': [3, 2, 4, 4, 5, 3]}
source = ColumnDataSource(data=data)
p = figure(x_range=fruits, y_range=(0, 10), plot_height=350, title="Fruit Counts by Year",
toolbar_location="below", tools="pan,wheel_zoom,box_zoom,reset,save")
p.vbar(x=dodge('fruits', -0.25, range=p.x_range), top='2015', width=0.2, source=source,
color="#c9d9d3", legend=value("2015"))
p.vbar(x=dodge('fruits', 0.0, range=p.x_range), top='2016', width=0.2, source=source,
color="#718dbf", legend=value("2016"))
p.vbar(x=dodge('fruits', 0.25, range=p.x_range), top='2017', width=0.2, source=source,
color="#e84d60", legend=value("2017"))
p.x_range.range_padding = 0.1
p.xgrid.grid_line_color = None
p.legend.location = "top_left"
p.legend.orientation = "horizontal"
script, div = components(p, CDN)
return render(request, "Bokeh/bokeh_chart.html", {"the_script": script, "the_div": div})
def bar_nested_chart（请求）：
fruits = ['Apples', 'Pears', 'Nectarines', 'Plums', 'Grapes', 'Strawberries']
years = ['2015', '2016', '2017']
data = {'fruits' : fruits,
'2015' : [2, 1, 4, 3, 2, 4],
'2016' : [5, 3, 3, 2, 4, 6],
'2017' : [3, 2, 4, 4, 5, 3]}
# this creates [ ("Apples", "2015"), ("Apples", "2016"), ("Apples", "2017"), ("Pears", "2015), ... ]
x = [ (fruit, year) for fruit in fruits for year in years ]
counts = sum(zip(data['2015'], data['2016'], data['2017']), ()) # like an hstack
source = ColumnDataSource(data=dict(x=x, counts=counts))
p = figure(x_range=FactorRange(*x), plot_height=350, title="Fruit Counts by Year",
toolbar_location='below', tools="pan,wheel_zoom,box_zoom,reset,save")
p.vbar(x='x', top='counts', width=0.9, source=source)
p.y_range.start = 0
p.x_range.range_padding = 0.1
p.xaxis.major_label_orientation = 1
p.xgrid.grid_line_color = None
script, div = components(p, CDN)
return render(request, "Bokeh/bokeh_chart.html", {"the_script": script, "the_div": div})
def pie_chart（请求）：
x = Counter({
'United States': 157,
'United Kingdom': 93,
'Japan': 89,
'China': 63,
'Germany': 44,
'India': 42,
'Italy': 40,
'Australia': 35,
'Brazil': 32,
'France': 31,
'Taiwan': 31,
'Spain': 29
})
# select the tools we want
data = pd.DataFrame.from_dict(dict(x), orient='index').reset_index().rename(index=str, columns={0:'value', 'index':'country'})
data['angle'] = data['value']/sum(x.values()) * 2*pi
data['color'] = Category20c[len(x)]
p = figure(plot_height=350, title="Pie Chart", toolbar_location="below",
tools="hover,pan,wheel_zoom,box_zoom,reset,save", tooltips="@country: @value")
p.wedge(x=0, y=1, radius=0.4,
start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),
line_color="white", fill_color='color', legend='country', source=data)
p.axis.axis_label=None
p.axis.visible=False
p.grid.grid_line_color = None
script, div = components(p, CDN)
return render(request, "Bokeh/bokeh_chart.html", {"the_script": script, "the_div": div})
def scatter_plot_chart（请求）：
# create some data
x1 = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
y1 = [0, 8, 2, 4, 6, 9, 5, 6, 25, 28, 4, 7]
x2 = [2, 5, 7, 15, 18, 19, 25, 28, 9, 10, 4]
y2 = [2, 4, 6, 9, 15, 18, 0, 8, 2, 25, 28]
x3 = [0, 1, 0, 8, 2, 4, 6, 9, 7, 8, 9]
y3 = [0, 8, 4, 6, 9, 15, 18, 19, 19, 25, 28]
# select the tools we want
TOOLS="pan,wheel_zoom,box_zoom,reset,save"
# the red and blue graphs will share this data range
xr1 = Range1d(start=0, end=30)
yr1 = Range1d(start=0, end=30)
# only the green will use this data range
xr2 = Range1d(start=0, end=30)
yr2 = Range1d(start=0, end=30)
# build our figures
p1 = figure(x_range=xr1, y_range=yr1, tools=TOOLS, plot_width=300, plot_height=300)
p1.scatter(x1, y1, size=12, color="red", alpha=0.5)
p2 = figure(x_range=xr1, y_range=yr1, tools=TOOLS, plot_width=300, plot_height=300)
p2.scatter(x2, y2, size=12, color="blue", alpha=0.5)
p3 = figure(x_range=xr2, y_range=yr2, tools=TOOLS, plot_width=300, plot_height=300)
p3.scatter(x3, y3, size=12, color="green", alpha=0.5)
# plots can be a single Bokeh Model, a list/tuple, or even a dictionary
plots = {'Red': p1, 'Blue': p2, 'Green': p3}
script, div = components(plots)
return render(request, "Bokeh/bokeh_chart.html", {"the_script": script, "the_div": div})
}