如何使用 plotly 在条形图中添加注释？ 剧情：代码：

如何解决如何使用 plotly 在条形图中添加注释？ 剧情：代码：

目前我的情节是这样的：

绘图、数据和代码：

df_pub = pd.read_excel('D:\Masterarbeit\Data\Excel/publication_years.xlsx')
fig = px.bar(df_pub,x = 'Publication date',y = 'Freq.')
fig.show()



years = ['80','81','82','83','84','85','86,'87','88','89','90','91','92','93','94','95','96','97','98','99','00','01','02','03','04' '05','06','07','08','09','10','11','12','13','14','15','16','17','18','19']
freq = [173,1368,2238,4135,5455,6280,7470,6580,7537,8781,10894,14788,20562,27637,32446,32665,30374,28234,24235,22312,16817,20222,24080,30398,30230,27462,33582,28908,31648,26579,29121,31216,34574,34271,32570,32531,43390,46761,55920,34675]

我想在图表下方添加一些注释。

正如回答所建议的：

import pandas as pd
import plotly.express as px

df_pub = pd.read_excel('D:/Masterarbeit/Data/Excel/publication_years.xlsx')
fig = px.bar(df_pub,y = 'Freq.',title = 'Frequency of publicated patents 1980-2019'
            )
annot_y = -0.2
annot_t = 'Figure 1(i) - Patent frequency 1980-2019Q1'

fig.add_annotation(
                                        y=annot_y,showarrow=False,text=annot_t,textangle=0,xanchor='left',xref="x",yref="paper")
fig.show()

但它仍然被挤压：/

解决方法

您想注释哪个数字并不是 100% 清楚。但现在我假设：

---

您尚未共享数据样本，因此很难确定。但在我看来，您的 x 值是时间戳，您在 x=4 中使用了 fig.add_annotation()。因此您需要确保分配给 x 轴的值对应于您在 fig.add_annotation() 中分配的值。下面是一个工作示例，可以让您完全按照自己的意愿行事。

剧情：

代码：

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

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

# data sample
nperiods = 50
np.random.seed(123)
df = pd.DataFrame(np.random.randint(-6,12,size=(nperiods,2)),columns=['price','divergence'])
datelist = pd.date_range(datetime.datetime(2017,1,1).strftime('%Y-%m-%d'),periods=nperiods).tolist()
df['date'] = datelist 
df = df.set_index(['date'])
df.index = pd.to_datetime(df.index)
# df.iloc[0] =1000
# df = df.cumsum().reset_index()
df.reset_index(inplace=True)
df['price'] = df['price'].cumsum()
df['divergence'] = df['divergence'].cumsum()

# filtered = df[(df['date'] > '2017-1-24') & (df['date'] <= '2018-1-24')]

fig = make_subplots(specs=[[{"secondary_y": True}]])

fig.add_trace(
    go.Bar(
        x=df['date'],y=df['divergence'],#opacity=0.5
    )
)

fig.update_traces(marker_color = 'rgba(0,250,0.5)',marker_line_width = 0,selector=dict(type="bar"))

fig.update_layout(bargap=0,bargroupgap = 0,)

annot_x = df['date'].to_list()[::20]
annot_y = -0.2
annot_t = list('ABC')


for i,x in enumerate(annot_x):
#     print(x)
    fig.add_annotation(dict(font=dict(color='red',size=12),x=x,y=annot_y,showarrow=False,text=annot_t[i],textangle=0,xanchor='left',xref="x",yref="paper"))

fig.show()