how to split a dataframe in two from a specific value on a column

Question

I have this dataframe:

In row 84 it changes from a negative value in the 'position' column to positive.

I need to split the data frame into two at this point (before and after position=0)

I tried using

idx = run_1[run_1['Position_(m)']>0].index dfs = np.split(df, idx)

but it split on every instance where >0 and if I use idx[0] it says:

ValueError: array split does not result in an equal division

Note: I only need one split, "before and after," I have looked through other similar questions to mine but most deal with multiple splits and I'm unable to re-use the code sugested for a single split.

Answer 1

You can use a Boolean mask to do this:

before = run_9[run_9['Position_(m)']<0]
after = run_9[run_9['Position_(m)']>0]