[Python] Creating new rows in a dataframe based on previous values

I have a dataframe that looks like this:

test = pd.DataFrame(
{'onset': [1,3,18,33,35,50],
'duration': [2,15,15,2,15,15],
'type': ['Instr', 'Remember', 'SocTestString', 'Rating', 'SelfTestString', 'XXX']
}
)


I want to create a new dataframe such that when type contains "TestString",

• two new rows are created below that row, such that the row is is now split into three rows with (for example) SocTestString_1, SocTestString_2, SocTestString_3
• for those three rows, change duration columns to the value 5
• for those three rows, also change the onset column such that it is the onset value of the previous column + 5

The final dataframe should look like this:

test_final = pd.DataFrame(
{'onset': [1,3,18,23,28,33,35,40,45,50],
'duration': [2,15,5,5,5,2,5,5,5,15],
'type': ['Instr', 'Remember', 'SocTestString_1', 'SocTestString_2', 'SocTestString_3', 'Rating', 'SelfTestString_1', 'SelfTestString_2', 'SelfTestString_3', 'XXX']
})


How may I accomplish this?

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