Alternative solution for parallel numpy array application

Question

doctors and patients arrays are parallel. Data says, for example, the doctor named Benitz has 172 patients in 2017, the doctor Modin has 272 patients in 2019 and so on. I'd like to extract the doctor name data for year 2019 into an array, which is ['Modin' 'Vandergard']. I did this by the code below, but as you see, I firstly use list, append method and then turn the list into an array. I wonder if there is more practical solution without using lists. I mean, is there any way to solve it by just using arrays?

import numpy as np

doctors=np.array(['Benitz','Modin','Leabow','Vandergard'])

patients=np.array([[2017,172],
                   [2019,272],
                   [2016,203],
                   [2019,250]])

doc2019_list=[]
for row in range(0,len(patients)):
    for col in range(0,len(patients[row])):
        if patients[row][col]==2019:
            doc2019_list.append(doctors[row])
doc2019=np.array(doc2019_list)

print(doc2019)

Tomerikoo · Accepted Answer · 2020-12-16 18:26:10Z

1

You can use the years:

>>> patients[:,0]
[2017 2019 2016 2019]

...to create a boolean array of the years equivalent to 2019:

>>> patients[:,0] == 2019
[False  True False  True]

...and use that to access the doctors array:

>>> doctors[patients[:,0] == 2019]
['Modin' 'Vandergard']

edited Dec 16, 2020 at 18:26

answered Dec 16, 2020 at 18:18

Tomerikoo

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Comments

Ismail Durmaz · Accepted Answer · 2020-12-16 18:13:49Z

0

You can use zip functions by combining two lists.

import numpy as np

doctors=np.array(['Benitz','Modin','Leabow','Vandergard'])

patients=np.array([[2017,172],
                   [2019,272],
                   [2016,203],
                   [2019,250]])

doc2019_list = [doctor for doctor, patient in zip(doctors, patients) if patient[0] == 2019]
print(doc2019_list)

If the List comprehension method seems little confusing, look below code, this is the same with above. Further reading Python - List Comprehension

import numpy as np

doctors=np.array(['Benitz','Modin','Leabow','Vandergard'])

patients=np.array([[2017,172],
                   [2019,272],
                   [2016,203],
                   [2019,250]])
doc2019_list = []

for doctor, patient in zip(doctors, patients):
  if patient[0] == 2019:
    doc2019_list.append(doctor)
print(doc2019_list)

Another alternative way with numpy.array

doc2019_list = np.array([doctor for doctor, patient in zip(doctors, patients) if patient[0] == 2019])

edited Dec 16, 2020 at 18:13

answered Dec 16, 2020 at 18:08

Ismail Durmaz

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2 Comments

blit Over a year ago

so, because numpy has no attribute append, we need to use lists certainly, right?

Ismail Durmaz Over a year ago

Numpy has append function Numpy Append. It is your choice, you can process with numpy.append. But numpy.append generates a new array every call, be careful.

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