import pandas as pd

import io

​

## load data

​

raw ="""START,FINISH

0.000000    ,10.000000

2.000000    ,3.000000

10.000000   ,4500.182997

5000.00    ,7000.000000

6000   ,8500.687227

9850.123,9990.000000

"""

​

buf_bytes = io.StringIO(raw)

df=pd.read_csv(buf_bytes)

​

## solution

​

df.sort_values("START", inplace=True)

​

## This line compares if START of present row is greater than largest FINISH in previous 

## rows ("shift" shifts up FINISH by one row). The value of expression before

## cumsum will be True if interval breaks (i.e. cannot be merged), so

## cumsum will increment group value when interval breaks (cum sum treats True=1, False=0)

​

​

df["group"]=(df["START"]>df["FINISH"].shift().cummax()).cumsum()

​

print(df)

​

## this returns min value of "START" column from a group and max value fro m "FINISH"

result=df.groupby("group").agg({"START":"min", "FINISH": "max"})

print(result)