即使数据集中缺少某些日期，也可以将日期作为日期值进行解释，甚至在时间轴上显示丢失的日期。一种解决方案是获取第一个和最后一个日期，构建完整的时间轴，找出原始数据集中缺少的日期，并将这些日期包括在以下内容中：
fig.update_xaxes(rangebreaks=[dict(values=dt_breaks)])
这将使这个数字：
变成这个：
import plotly.graph_objects as go
from datetime import datetime
import pandas as pd
import numpy as np
# sample data
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
# remove some dates to build a similar case as in the question
df = df.drop(df.index[75:110])
df = df.drop(df.index[210:250])
df = df.drop(df.index[460:480])
# build complete timepline from start date to end date
dt_all = pd.date_range(start=df['Date'].iloc[0],end=df['Date'].iloc[-1])
# retrieve the dates that ARE in the original datset
dt_obs = [d.strftime("%Y-%m-%d") for d in pd.to_datetime(df['Date'])]
# define dates with missing values
dt_breaks = [d for d in dt_all.strftime("%Y-%m-%d").tolist() if not d in dt_obs]
# make fiuge
fig = go.figure(data=[go.Candlestick(x=df['Date'],
open=df['AAPL.Open'], high=df['AAPL.High'],
low=df['AAPL.Low'], close=df['AAPL.Close'])
])
# hide dates with no values
fig.update_xaxes(rangebreaks=[dict(values=dt_breaks)])
fig.update_layout(yaxis_title='AAPL Stock')
fig.show()
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