[Python] Removing rows from pandas if they match multiple column of other row of same dataframe

I am trying to remove all the rows in which value of Total, first and second is equal to the row which is marked by label M within a netting

DataFrame (pandas)

netting Total first second lable
01 9358.66 358.69 9717.35 M
01 9358.66 358.69 717.35 X
01 9358.66 358.69 9717.35 X
01 9358.66 358.69 9717.35 X
01 9358.66 358.69 9717.35 X
02 100 100 100 M
02 100 100 100 Y


Expected output is

netting Total first second lable
01 9358.66 358.69 9717.35 M
01 9358.66 358.69 717.35 X
01 9358.66 358.69 9717.35 X --> dropped
01 9358.66 358.69 9717.35 X --> dropped
01 9358.66 358.69 9717.35 X --> dropped
02 100 100 100 M
02 100 100 100 Y --> dropped


Final Data frame will look like this.

netting Total first second lable
01 9358.66 358.69 9717.35 M
01 9358.66 358.69 717.35 X
02 100 100 100 M


I am just starting out in Pandas, any help will be appreciated, thanks !!!

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