Filtering rows from dataframe based on the values of the previous rows

You can't get away from looping through each row

Tips

• Avoid creating new (expensive to create) objects for each row
• Use a memory efficient iteration

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I'd use a generator

I'll pass a series to a function and yield the index values for which rows satisfy the conditions.

def f(s):
    it = s.iteritems()
    i, v = next(it)
    yield i                          # Yield the first one
    for j, x in it:
        if .5 * v <= x <= 1.5 * v:
            yield j                  # Yield the ones that satisfy
            v = x                    # Update the comparative value

df.loc[list(f(df.A))]                # Use `loc` with index values
                                     # yielded by my generator

       A
1   1000
2   1000
3   1001
4   1001
6   1000
7   1010
11   999
14  1000