CODEWITHSUNDEEP
pythonnumpy
Metadata
Metadata

Reputation: 2085

How access multiple column values in a numpy structured array in python?

I am new to numpy and still learning it. I created a structured array as below:

name = ['Alice', 'Beth', 'Cathy', 'Dorothy']
studentid = [1,2,3,4]
score = [85.4, 90.4, 87.66, 78.9]
student_data = np.zeros(4, dtype={'names':('name', 'studentId', 'score'), 
                         'formats':('U10', 'i4', 'f8')})
student_data['name'] = name
student_data['studentId'] = studentid
student_data['score']=score

Inorder to get the names of people who have scores greater than 85, I wrote this:

student_data[student_data['score'] > 85]['name']

But if I try to retrieve another column along with 'name', I am getting an error: 

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

For example, I tried the below ways:

student_data[student_data['score'] < 90]['name','studentid']
student_data[student_data['score'] < 90]['name']['studentid']

Both of them result in the error:

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-189-7ad7c151f0e3> in <module>
----> 1 student_data[student_data['score'] < 90]['name']['studentid']

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

Could anyone let me know what is the mistake I am doing here & how can I retrieve multiple columns on conditional basis ?

Upvotes: 0

Views: 164

Answers (2)

sushanth
sushanth

Reputation: 8302

You can use np.where

print(student_data[np.where(student_data['score'] < 90)][['name', 'studentId']])

[('Alice', 1) ('Cathy', 3) ('Dorothy', 4)]

Upvotes: 1

Quang Hoang
Quang Hoang

Reputation: 150735

You can access with array of columns:

student_data[student_data['score'] < 90][['name','studentid']]

Output:

array([('Alice', 1), ('Cathy', 3), ('Dorothy', 4)],
      dtype={'names':['name','studentId'], 'formats':['<U10','<i4'], 'offsets':[0,40], 'itemsize':52})

Upvotes: 1

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