添加注释文本会产生整数错误消息
Adding annotation text yields integer error message
当我在我的图表中添加一条 vline 时,它完美地工作:
fig.add_vline(
x=pd.to_datetime('1970-01-01 00:00:00'),
line_dash='dot',
row=0)
[![在此处输入图片描述][1]][1]
当我尝试在 vline 旁边添加注释文本时,我收到一条错误消息
fig.add_vline(
x=pd.to_datetime('1970-01-01 00:00:00'),
line_dash='dot',
annotation_text='15',
row=0)
TypeError: Addition/subtraction of integers and integer-arrays with
Timestamp is no longer supported. Instead of adding/subtracting n
,
use n * obj.freq
- 作为解决方法,对
add_vline()
进行一次调用,对 add_annotation()
进行一次调用
- 已将参数设置为
add_annotation()
,以便注释位于行首
import pandas as pd
import plotly.express as px
ROWS = 20
df = pd.DataFrame({"ColA":pd.date_range("1-jan-1970", freq="4H", periods=ROWS), "ColB":np.random.uniform(1,30, ROWS)})
fig = px.line(df, x="ColA", y="ColB")
fig.update_xaxes(title_font=dict(size=12), tickformat='%X')
for time in df["ColA"].values:
time = pd.Timestamp(time).to_pydatetime()
fig.add_vline(x=time)
fig.add_annotation(x=time, y=1, yref="paper", text="15")
fig
子图
import pandas as pd
import plotly.express as px
ROWS = 20
df = pd.DataFrame(
{
"ColA": pd.date_range("1-jan-1970", freq="4H", periods=ROWS),
"ColB": np.random.uniform(1, 30, ROWS),
"Facet": np.repeat(["plot 1", "plot 2"], ROWS // 2),
}
)
fig = px.line(df, x="ColA", y="ColB", facet_row="Facet")
fig.update_xaxes(title_font=dict(size=12), tickformat="%X")
for time, y, facet in df[["ColA", "ColB", "Facet"]].values:
time = pd.Timestamp(time).to_pydatetime()
fig.add_vline(x=time, row=0 if facet == "plot 1" else 1)
fig.add_annotation(x=time, y=y, text="15", row=0 if facet == "plot 1" else 1, col=0)
fig
当我在我的图表中添加一条 vline 时,它完美地工作:
fig.add_vline(
x=pd.to_datetime('1970-01-01 00:00:00'),
line_dash='dot',
row=0)
[![在此处输入图片描述][1]][1]
当我尝试在 vline 旁边添加注释文本时,我收到一条错误消息
fig.add_vline(
x=pd.to_datetime('1970-01-01 00:00:00'),
line_dash='dot',
annotation_text='15',
row=0)
TypeError: Addition/subtraction of integers and integer-arrays with Timestamp is no longer supported. Instead of adding/subtracting
n
, usen * obj.freq
- 作为解决方法,对
add_vline()
进行一次调用,对add_annotation()
进行一次调用
- 已将参数设置为
add_annotation()
,以便注释位于行首
import pandas as pd
import plotly.express as px
ROWS = 20
df = pd.DataFrame({"ColA":pd.date_range("1-jan-1970", freq="4H", periods=ROWS), "ColB":np.random.uniform(1,30, ROWS)})
fig = px.line(df, x="ColA", y="ColB")
fig.update_xaxes(title_font=dict(size=12), tickformat='%X')
for time in df["ColA"].values:
time = pd.Timestamp(time).to_pydatetime()
fig.add_vline(x=time)
fig.add_annotation(x=time, y=1, yref="paper", text="15")
fig
子图
import pandas as pd
import plotly.express as px
ROWS = 20
df = pd.DataFrame(
{
"ColA": pd.date_range("1-jan-1970", freq="4H", periods=ROWS),
"ColB": np.random.uniform(1, 30, ROWS),
"Facet": np.repeat(["plot 1", "plot 2"], ROWS // 2),
}
)
fig = px.line(df, x="ColA", y="ColB", facet_row="Facet")
fig.update_xaxes(title_font=dict(size=12), tickformat="%X")
for time, y, facet in df[["ColA", "ColB", "Facet"]].values:
time = pd.Timestamp(time).to_pydatetime()
fig.add_vline(x=time, row=0 if facet == "plot 1" else 1)
fig.add_annotation(x=time, y=y, text="15", row=0 if facet == "plot 1" else 1, col=0)
fig