Plotly time series bars

I have a time series data with a few timestamps, and each timestamps has been detected with one label (action, discard, cut). Depending on these key words, the segments between these timestamps would be processed differently (keep, discard, check).

time_stamps = [[1.12, 'action'], [29.09, 'cut'], [52.36, 'action'], [87.34, 'cut'], [103.8, 'action'], [171.32, 'cut'], [191.46, 'action'], [238.56, 'action'], [257.1, 'cut']...]

import numpy as np

import pandas as pd

import plotly.express as px

import plotly.graph_objects as go

# import datetime

from datetime import date, datetime, timedelta

import time

tz = 'Europe/London'

start = pd.Timestamp(date.today(), tz=tz) # today's date

df = pd.DataFrame(columns=['Task','Start','End', "Key1", "Key2"])

not_finsh = True

i = 0

while not_finsh:

   stamp_curr, stamp_next = time_stamps[i], time_stamps[i+1]

   if stamp_curr[1] == "action" and stamp_next[1] == "cut":

       i += 2

       task = "keep"

   elif stamp_curr[1] == "action" and stamp_next[1] == "discard":

       i += 2

       task = "discard"

   else:

       i += 1

       task = "check"

   not_finsh = i<len(time_stamps)-1

   time_start = start+timedelta(seconds=stamp_curr[0])

   time_end = start+timedelta(seconds=stamp_next[0])

   df2 = pd.DataFrame({"Task": [task],

                       "Start": [time_start],

                       "End": [time_end],

                       "Key1": [stamp_curr[1]],  # the starting key word

                       "Key2": [stamp_next[1]]})  # the ending key word

   df = pd.concat([df, df2], ignore_index=True)

fig = px.timeline(df, x_start='Start', x_end='End', y='Task', color='Task')

fig.update_layout(xaxis=dict(title='Timestamp', tickformat='%M:%S.%f',))

fig.show()

a = 0