fail to update_xaxes rangebreaks by datetime
data df: ` id date_time time_hms time_second price time_date
0 2021-05-31 09:25:00 09:25:00 33900 7 2021-05-31
1 2021-05-31 09:30:00 09:30:00 34200 8 2021-05-31
2 2021-05-31 09:30:01 09:30:01 34201 7 2021-05-31
3 2021-05-31 09:30:02 09:30:02 34202 6 2021-05-31
4 2021-05-31 09:30:03 09:30:03 34203 5 2021-05-31
... ... ... ... ...
24264 2021-06-04 14:56:56 14:56:56 53816 7 2021-06-04
24265 2021-06-04 14:56:57 14:56:57 53817 6 2021-06-04
24266 2021-06-04 14:56:58 14:56:58 53818 4 2021-06-04
24267 2021-06-04 14:56:59 14:56:59 53819 7 2021-06-04
24268 2021-06-04 15:00:00 15:00:00 54000 8 2021-06-04 `
code: ` import pandas as pd import plotly.express as px import plotly.io as pio
fig = px.line(df,
x = "date_time",
y = "price"
)
fig.update_xaxes(
rangebreaks=[
dict(bounds=["2021-06-01 09:25:00", "2021-06-04 09:25:01"]) # hide by datetime
]
)
pio.write_html(fig, file="stock_graph_px.html", auto_open=True)
`
the result html page is blank.
as document, rangebreaks only work for "date" .
but, how to deal with datetime breaks?
is there a simple way to set axis datetime breaks?
plotly==4.14.3 Python 3.8.5
It works with hours:
dict(bounds=[15, 9], pattern="hour")