How to get specific values from my data based on an array values using numpy?

Question

I have a data array to which I have inserted a column with values starting from 0. So now my data contains all float values.

After some processing I have a array ARR which contains values from my 1st column. Using these ARR values (or positions) I want to extract the remaining columns to a new array using Numpy.

import numpy as np
import io
data =io.StringIO("""
ID,1,2,3
5362,0.97,-0.40,-0.76
485,-0.65,0.53,0.62
582,0.04,0.99,0.76
99,0.77,0.53,0.39
75,-0.44,0.52,0.85
474,0.35,0.8,0.13
594,-0.29,0.03,0.74
597,0.96,-0.35,0.59
124,0.73,0.61,0.76
635,0.88,0.96,-0.98
7894,-0.04,0.04,0.52
1268,0.56,0.73,-0.37
38,0.46,0.62,0.73
88,0.02,0.16,0.098
887,0.46,0.65,-0.89
""")

data = np.genfromtxt(data, delimiter=',', skip_header=2, dtype=np.float64)
index = np.arange(data.shape[0]).reshape(-1, 1)
data = np.hstack([index, data])


ARR = [[1.],[2.],[4.],[6.],[7.],[9.]]

Expected Output Like:

I want all the row values at the positions indicated in the ARR. I can also show it as Integer values. I want all the rows at these positions in my data array.

485,-0.65,0.53,0.62
582,0.04,0.99,0.76
75,-0.44,0.52,0.85
594,-0.29,0.03,0.74
597,0.96,-0.35,0.59
635,0.88,0.96,-0.98

CypherX · Accepted Answer · 2019-11-21 10:13:49Z

1

You only need to do the following (no need to add an index column to the data). Also, I do not understand why you specify the row numbers as floats (1., 2., 4.,...). Your row numbers must be integers. The solution here corrects this aspect.

# np.set_printoptions(precision=3, suppress=True)
data = np.genfromtxt(data, delimiter=',', skip_header=2, dtype=np.float64)
ARR = [[1.],[2.],[4.],[6.],[7.],[9.]]
ARR = np.array(ARR).astype(int).flatten()
data[ARR, :]

Output:

array([[485.  ,  -0.65,   0.53,   0.62],
       [582.  ,   0.04,   0.99,   0.76],
       [ 75.  ,  -0.44,   0.52,   0.85],
       [594.  ,  -0.29,   0.03,   0.74],
       [597.  ,   0.96,  -0.35,   0.59],
       [635.  ,   0.88,   0.96,  -0.98]])

Optionally:
In case you must add the index, then use the following code block in addition to the code you posted in the question.

ARR = np.array(ARR).astype(int).flatten()
data[ARR, 1:]

edited Nov 21, 2019 at 10:13

answered Nov 21, 2019 at 9:57

CypherX

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1 Comment

axay Over a year ago

Yes. I needed the locations initially but the array was taking float values, but this solution solved it as I needed the index of the array.

Márcio Coelho · Accepted Answer · 2019-11-21 09:53:44Z

1

Using the way data is shaped, you can easily do:

for value in ARR:
    print(data[int(value[0])][1::])

Hope it helps!

Edit: Added [1::] to slice the result and remove the index position.

answered Nov 21, 2019 at 9:53

Márcio Coelho

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2 Comments

axay Over a year ago

If I assign it to a variable new_arr = data[int(value[0])][1::], and try to save it to csv, I am getting different values. If I do not assign, it is working fine. Also the other solution provided works.

Márcio Coelho Over a year ago

I don't know how you're saving to a csv, but you might have to add a newline character between lines as you save them. Regardless, glad you found a working solution!

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