How can I find the index that satisfies a condition in a column(numpy object) of dataframe?

Question

I have a dataframe that contains the numpy object column.The data is as follows：

                          data
0           [1, 2, 2, 3, 4, 2]
1        [2, 4, 2, 5, 2, 3, 2]
2  [2, 2, 2, 8, 2, 3, 2, 9, 1]
...

I would like to get the index of every numpy in the column to satisfy the condition: (>(mean+std))or(<(mean-std)),the output I expect is as follows：

                          data    index
0           [1, 2, 2, 3, 4, 2]    [0,4]
1        [2, 4, 2, 5, 2, 3, 2]    [1,3]
2  [2, 2, 2, 8, 2, 3, 2, 9, 1]    [3,7]
...

My code is like this:

df['index'] = df['data'].map(lambda x: np.where(((x > x.mean() + x.std()) or (x < x.mean() - x.std())))[0])

But it has a mistake：

The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

When I'm using only half of the condition(such as (>(mean+std))), there's no problem, so I guess my expression is wrong, but I don't know how to change it.

Can someone help me? Thanks in advance

jezrael · Accepted Answer · 2017-06-24T04:48:53.447

I think you need np.logical_or and reduce:

df['index'] = df['data'].map(lambda x: np.where(np.logical_or
                                                  .reduce(((x > x.mean() + x.std()), 
                                                           (x < x.mean() - x.std()))))[0])
print (df)
                          data   index
0           [1, 2, 2, 3, 4, 2]  [0, 4]
1        [2, 4, 2, 5, 2, 3, 2]  [1, 3]
2  [2, 2, 2, 8, 2, 3, 2, 9, 1]  [3, 7]

For verify solution:

df['index'] = df['data'].map(lambda x: ((x > x.mean() + x.std())))
df['index1'] = df['data'].map(lambda x: ((x < x.mean() - x.std())))
#https://stackoverflow.com/a/33375383/2901002
with pd.option_context('display.max_colwidth', 200):
    print (df)

                          data  \
0           [1, 2, 2, 3, 4, 2]   
1        [2, 4, 2, 5, 2, 3, 2]   
2  [2, 2, 2, 8, 2, 3, 2, 9, 1]   

                                                           index  \
0                      [False, False, False, False, True, False]   
1                [False, True, False, True, False, False, False]   
2  [False, False, False, True, False, False, False, True, False]   

                                                            index1  
0                        [True, False, False, False, False, False]  
1                [False, False, False, False, False, False, False]  
2  [False, False, False, False, False, False, False, False, False]

How can I find the index that satisfies a condition in a column(numpy object) of dataframe?

1 Answers1