Using booleans in Python

Question

I am trying to replace string values in an array with the array median, but I am getting an error code when I try to make a boolean. I have a defined array with 3 string values and the code I am trying to enter is:

arr2 = np.array ([1,2,3,1,5,2,3,4,2,
                  4,1,3,4,1,2,5,3,2,
                  1,"?",1,"n",3,2,5,
                  1,2,"Nan",3,2,2,4,3])

flag_good = [element.isdigit() for element in arr2]
flag_bad = ~flag_good

but I get an error code when running the line:

flag_bad = ~flag_good

How would I go about replacing the sting values with the array's median?

I apologize for the formatting it did retain its original format — Greg Sullivan
– Greg Sullivan, Commented Mar 20, 2020 at 16:06
Edit the question to show the full error message as properly formatted text. — Michael Butscher
– Michael Butscher, Commented Mar 20, 2020 at 16:08

Querenker · Accepted Answer · 2020-03-20 16:34:39Z

3

The tilde operation is part of numpy and is a shortcut for numpy.invert.

By using a list comprehension, flag_good is a Python list, which doesn't support this operation.

For example, you can convert the list flag_good to a Numpy array and then use the invert function.

>>> flag_bad = ~np.array(flag_good)
>>> flag_bad
array([False, False, False, False, False, False, False, False, False,
       False, False, False, False, False, False, False, False, False,
       False,  True, False,  True, False, False, False, False, False,
        True, False, False, False, False, False])

Or you can use vectorize and directly return a Numpy array where the function is called elementwise instead of using the list comprehension.

>>> flag_good = np.vectorize(lambda x: x.isdigit())(arr2)
>>> flag_bad = ~flag_good
>>> flag_bad
array([False, False, False, False, False, False, False, False, False,
       False, False, False, False, False, False, False, False, False,
       False,  True, False,  True, False, False, False, False, False,
        True, False, False, False, False, False])

edited Mar 20, 2020 at 16:34

answered Mar 20, 2020 at 16:14

Querenker

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5 Comments

Greg Sullivan Over a year ago

Thank you. The Boolean is now working like you have showed. But It is reporting an error when I try and run the code: arr2[FlagBad] = np.median(arr2[FlagGood]) is the function different on an array contains string and digit values then an array containing only digit values? I am trying to replicate a function I wrote to replace outliers with a mean, but this is replacing string values with a median and it is proving to be much different

Querenker Over a year ago

@GregSullivan Which code exactly doesn't work? And what's the error message?

Greg Sullivan Over a year ago

File "/Users/gregorysullivan/opt/anaconda3/lib/python3.7/site-packages/numpy/lib/function_base.py", line 3561, in median return mean(part[indexer], axis=axis, out=out) File "<__array_function_ internals>", line 6, in mean File "/Users/gregorysullivan/opt/anaconda3/lib/python3.7/site-packages/numpy/core/fromnumeric.py", line 3257, in mean out=out, **kwargs) File "/Users/gregorysullivan/opt/anaconda3/lib/python3.7/site-packages/numpy/core/_methods.py", line 151, in _mean ret = umr_sum(arr, axis, dtype, out, keepdims) TypeError: cannot perform reduce with flexible type

Querenker Over a year ago

@GregSullivan And which code do you execute? In the code listed above their is no mean function or something like that.

Greg Sullivan Over a year ago

The code I executed was: arr2[FlagBad2] = np.median(arr2[FlagGood2]) but after seeing the error code and working on it I entered: arr2[FlagBad2] = np.median(arr2[FlagGood2].astype(int)) and it worked! Thank you for you help!

gust · Accepted Answer · 2020-03-20 16:43:43Z

1

I feel like you could solve the problem from the beginning, editing your list comprehension.

flag_bad = [not(element.isdigit()) for element in arr2]

To answer your question, though, I'd do this:

import numpy as np
input_list = [1,2,3,1,5,2,3,4,2,
                  4,1,3,4,1,2,5,3,2,
                  1,"?",1,"n",3,2,5,
                  1,2,"Nan",3,2,2,4,3]

# calculate the median
median = int(np.median([elt for elt in input_list if type(elt) is int])) 

# replace elements of the list only if you have a non-int 
output_array = np.array([elt if type(elt) is int else median for elt in input_list])
print(output_array)

Output:

[1 2 3 1 5 2 3 4 2 4 1 3 4 1 2 5 3 2 1 2 1 2 3 2 5 1 2 2 3 2 2 4 3]

edited Mar 20, 2020 at 16:43

answered Mar 20, 2020 at 16:26

gust

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2 Comments

Greg Sullivan Over a year ago

Thank you, I don't think python will calculate the median when there is string and int values in the array, and that is what I was struggling to figure out.

gust Over a year ago

@GregSullivan Yes. That's why I only use the integers from the list to calculate the median. The code above should work on any platform without any errors.

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