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| frames = []
steps = []
＃设置颜色条刻度值，范围从1到最大数。确诊病例任何国家迄今
max_country_confirmed_cases = cases_by_date[dates_list[-1]]["confirmed_cases"].max()
＃考虑到案例数量的显着差异，我们希望标度为对数
high_tick = np.log1p(max_country_confirmed_cases)
low_tick = np.log1p(1)
log_tick_values = np.geomspace(low_tick, high_tick, num=6)
＃但是，我们希望尺度上的/ labels /是实际的案例数（即不是log（n_cases））
visual_tick_values = np.expm1(log_tick_values).astype(int)
＃由于舍入误差- ＃明确设置最大CBAR值，否则它可能是最大
visual_tick_values[-1] = max_country_confirmed_cases
visual_tick_values = [f"{val:,}" for val in visual_tick_values]
＃生成折线图数据
元组的列表＃：[（confirmed_cases，死亡），...]
cases_deaths_totals = [(df.filter(like="confirmed_cases").astype("uint32").agg("sum")[0],
df.filter(like="deaths").astype("uint32").agg("sum")[0])
for df in cases_by_date.values()]
confirmed_cases_totals = [daily_total[0] for daily_total in cases_deaths_totals]
deaths_totals =[daily_total[1] for daily_total in cases_deaths_totals]
＃该循环为每个帧生成数据
for i, (date, data) in enumerate(cases_by_date.items(), start=1):
df = data
＃z比例尺（用于计算每个国家的颜色）需要为对数
df["confirmed_cases_log"] = np.log1p(df["confirmed_cases"])
df["text"] = (
date
+ "<br>"
+ df["country"]
+ "<br>Confirmed cases: "
+ df["confirmed_cases"].apply(lambda x: "{:,}".format(x))
+ "<br>Deaths: "
+ df["deaths"].apply(lambda x: "{:,}".format(x))
)
＃创建Choropleth图表
choro_trace = go.Choropleth(
**{
"locations": df["alpha-3_code"],
"z": df["confirmed_cases_log"],
"zmax": high_tick,
"zmin": low_tick,
"colorscale": "reds",
"colorbar": {
"ticks": "outside",
"ticktext": visual_tick_values,
"tickmode": "array",
"tickvals": log_tick_values,
"title": {"text": "<b>Confirmed Cases</b>"},
"len": 0.8,
"y": 1,
"yanchor": "top"
},
"hovertemplate": df["text"],
"name": "",
"showlegend": False
}
)
＃创建已确认的案例trace
confirmed_cases_trace = go.Scatter(
x=dates_list,
y=confirmed_cases_totals[:i],
mode="markers" if i == 1 else "lines",
name="Total Confirmed Cases",
line={"color": "Red"},
hovertemplate="%{x}<br>Total confirmed cases: %{y:,}<extra></extra>"
)
＃创建死亡跟踪
deaths_trace = go.Scatter(
x=dates_list,
y=deaths_totals[:i],
mode="markers" if i == 1 else "lines",
name="Total Deaths",
line={"color": "Black"},
hovertemplate="%{x}<br>Total deaths: %{y:,}<extra></extra>"
)
if i == 1:
＃第一帧是个什么人物最初显示..
fig.add_trace(choro_trace, row=1, col=1)
fig.add_traces([confirmed_cases_trace, deaths_trace], rows=[2, 2], cols=[1, 1])
＃...和所有其他帧被附加到`frames`列表和滑块
frames.append({"data": [choro_trace, confirmed_cases_trace, deaths_trace], "name": date})
steps.append(
{"args": [[date], frame_args(50)], "label": date, "method": "animate",}
)
＃整理轴和最终确定图表准备好用于显示
fig.update_xaxes(range=[0, len(dates_list)-1], visible=False)
fig.update_yaxes(range=[0, max(confirmed_cases_totals)])
fig.frames = frames
fig.layout.sliders[0].steps = steps
fig.layout.geo.domain = {"x": [0,1], "y": [0.2, 1]}
fig.update_layout(
height=650,
legend={"x": 0.05, "y": 0.175, "yanchor": "top", "bgcolor": "rgba(0, 0, 0, 0)"})
fig
|
