Python Forum

As the title entails, I am trying to remove rows from a pandas dataframe at random based on whether the given row (instance) has a certain value in some given column.

For example, suppose I had the following dataframe:

see attachment if image doesn't show*



and I wanted to remove at random 33% of the rows which have a value of 0 in the 'balon_dor_winner' column, how would I go about doing it?

I have tried the following but it hasn't worked:

df.drop(df.loc[df['balon_dor_winner']==0].sample(frac=0.33).index)

which didn't work and also:

df.drop(df.query('balon_dor_winner == 0').sample(frac=.33).index)

but no luck so far.

What about adding another column with random numbers and dropping if winner is 0 and new column < 0.33?

Yeah that sounds okay, but I would have really liked to do it as described, I'm sure it could be done in R it's just I want start using pandas more.

Well, instead of adding a column you could make a boolean list with both conditions and subset with that.

Got it, my mistake was not assigning it to a variable as so:

df=df.drop(df.query('salary == 0').sample(frac=.41).index)