以阴影突出显示时间序列数据中的类别列

Question

这里我有一个时间序列数据，我正在尝试使用 plotly 进行绘制。我有一个分类列fill_cat，分别是二进制 1 或 0。在曾经存在 1 的地方，应绘制一条垂直线或阴影以识别存在某个事件 1。

 import numpy as np
import pandas as pd
import plotly.graph_objects as go
import plotly.express as px
import datetime

pd.set_option('display.max_rows', None)

# data sample
nperiods = 200
np.random.seed(123)
df = pd.DataFrame(np.random.randint(-10, 12, size=(nperiods, 4)),
                  columns=list('ABCD'))
datelist = pd.date_range(datetime.datetime(2020, 1, 1).strftime('%Y-%m-%d'),periods=nperiods).tolist()
df['dates'] = datelist 
df = df.set_index(['dates'])
df.index = pd.to_datetime(df.index)
df.iloc[0] = 0
df = df.cumsum().reset_index()
df['fill_cat'] = [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1,
       1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
       0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0] 
df.head()

fig = px.line(df, x='dates', y=df.columns[1:])
fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='rgba(0,0,255,0.1)')
fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='rgba(0,0,255,0.1)')
fig.show()

Answer 1

答案是使用官方参考准备的。在图形上添加矩形可以由add_vrect() 处理。如果它变成一个手动开始和结束的间隔，你可以给它上色，但我采取的方法是对'fii_cat'提取的数据帧使用循环过程。 （每天都这样）我想这就是效果。填充颜​​色未启用。

import numpy as np
import pandas as pd
import plotly.graph_objects as go
import plotly.express as px
import datetime

pd.set_option('display.max_rows', None)

# data sample
nperiods = 200
np.random.seed(123)
df = pd.DataFrame(np.random.randint(-10, 12, size=(nperiods, 4)),
                  columns=list('ABCD'))
datelist = pd.date_range(datetime.datetime(2020, 1, 1).strftime('%Y-%m-%d'),periods=nperiods).tolist()
df['dates'] = datelist 
df = df.set_index(['dates'])
df.index = pd.to_datetime(df.index)
df.iloc[0] = 0
df = df.cumsum().reset_index()
df['fill_cat'] = [0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1,
       1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
       0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0] 
df.head()


fig = px.line(df, x='dates', y=df.columns[1:])
fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='rgba(0,0,255,0.1)')
fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='rgba(0,0,255,0.1)')

fill_data = df[df['fill_cat'] == 1]
for idx,row in fill_data.iterrows():
    d = str(row.dates.strftime('%Y-%m-%d'))
    fig.add_vrect(x0=str(row.dates.strftime('%Y-%m-%d')),
                  x1=str(row.dates.strftime('%Y-%m-%d')),
                  fillcolor='yellow',
                  opacity=0.5,
                  line_width=2)

fig.show()