using 'OR' to select data in pandas
pandas, python
Solution
You need to use `|` instead of `or`. The `and` and `or` operators are special in Python and don't interact well with things like numpy and pandas that try to apply to them elementwise across a collection. So for these contexts, they've redefined the "bitwise" operators `&` and `|` to mean "and" and "or".
Problem
I have a dataframe of values and I would like to explore the rows that are outliers. I wrote a function below that can be called with the `groupby().apply()` function and it works great for high or low values but when I want to combine them together i generate an error. I am somehow messing up the boolean `OR` selection but I could only find documentation for selection criteria using `&`. Any suggestions would be appreciated. zach cp ``` df = DataFrame( {'a': [1,1,1,2,2,2,2,2,2,2], 'b': [5,5,6,9,9,9,9,9,9,20] } ) #this works fine def get_outliers(group): x = mean(group.b) y = std(group.b) top_cutoff = x + 2*y bottom_cutoff = x - 2*y cutoffs = group[group.b > top_cutoff] return cutoffs #this will trigger an error def get_all_ outliers(group): x = mean(group.b) y = std(group.b) top_cutoff = x + 2*y bottom_cutoff = x -2*y cutoffs = group[(group.b > top_cutoff) or (group.b < top_cutoff)] return cutoffs #works fine grouped1 = df.groupby(['a']).apply(get_outliers) #triggers error grouped2 = df.groupby(['a']).apply(get_all_outliers) ```