Python/Numpy joining subarrays of an array together

Question

Currently I have a list of arrays as follows:

array =
[array([100000.        , 100848.06652142,  99648.67144694, 102047.67944271,
       103655.99048427, 104602.87678005, 104597.83419837, 103505.42736768,
       104976.01311214, 104457.34603404, 105855.46549162, 105613.30235519,
       105212.71840922, 107647.5054673 ])
 array([107647.5054673 , 106891.82007643, 106979.91405552, 106030.74186486,
       107856.04281712, 108502.71948581, 106557.2401056 , 105659.59829843,
       105663.01875745, 107300.69453018, 106336.34733019, 107584.99034227,
       108089.2320392 , 106786.91702337])
 array([106786.91702337, 104416.74000465, 101289.12525402, 101932.58219813,
       102625.04352578, 101767.46209616, 103345.4263012 , 102816.73322055,
       102417.59316407, 104439.37518975, 103755.22627215, 103817.9744686 ,
       107872.40234863, 108110.9662065 ])
 array([108110.9662065 , 109544.86827069, 111072.22392645, 112618.46235766,
       113847.1768898 , 116708.86391903, 115790.02599715, 115614.72242411,
       119225.88436354, 121991.38468934, 123304.85972848, 125571.38040251,
       122456.3667249 ])
 array([122456.3667249 , 127497.74699282, 128659.85495604, 125813.77115906,
       129008.46450085, 128111.00914756, 123039.92607546, 124723.87932757,
       124181.57385836, 125134.9276196 , 126027.8631434 , 129304.85119148,
       128912.58600657])]

What would be the best possible way to join all these subarrays back together into one large array? I tried np.concatenate() but that did not work.

SOLUTION

For whatever reason, my output would not put commas between the subarrays, once I was able to find the fix for that np.concatenate() did indeed work.

Possible duplicate of numpy concatenate two arrays vertically — AGN Gazer
– AGN Gazer, Commented May 22, 2018 at 16:50
Could you use smaller arrays in your examples, preferably with more humane values that are easy to track when checking the solution? — AGN Gazer
– AGN Gazer, Commented May 22, 2018 at 16:52
Also, how do you want to join the arrays? Vertically? Horizontally? That is why it helps to show desired output. Finally, even though np.concatenate() did not work for you, can you show the actual code that you have attempted. — AGN Gazer
– AGN Gazer, Commented May 22, 2018 at 16:54
Why do you also say that np.concatenate() to no surprise did not work? I am surprised! — AGN Gazer
– AGN Gazer, Commented May 22, 2018 at 16:57
When a print display of an object omits commas, that means it's a numpy array, not a list. Your array looks like an object dtype array of ndarrays. I can make a valid list from @AGNGazer's modification. But when I try concatenate I get the shape shape error message. np.array(thatlist, dtype=object) produces an array whose 'print(arr)` looks like your array. The repr adds an outer array and object dtype. — hpaulj
– hpaulj, Commented May 22, 2018 at 23:40

ak_slick · Accepted Answer · 2018-05-22 16:54:47Z

2

concatenate works.. I think you forgot some commas in your example data between each array in the list.

import numpy as np
a = [np.array([1,2,3]), np.array(['4','5','6'])]

np.concatenate(a)

outputs

array(['1', '2', '3', '4', '5', '6']

answered May 22, 2018 at 16:54

ak_slick

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AGN Gazer · Accepted Answer · 2018-05-22 17:05:16Z

np.concatenate(array)

The only problem, in your example, array in the list array (now, do you see how bad it is to use confusing names) should become np.array and you should add commas after each numpy.ndarray in the list array:

array = [np.array([100000., 100848.06652142,  99648.67144694, 102047.67944271,
       103655.99048427, 104602.87678005, 104597.83419837, 103505.42736768,
       104976.01311214, 104457.34603404, 105855.46549162, 105613.30235519,
       105212.71840922, 107647.5054673 ]),
 np.array([107647.5054673 , 106891.82007643, 106979.91405552, 106030.74186486,
       107856.04281712, 108502.71948581, 106557.2401056 , 105659.59829843,
       105663.01875745, 107300.69453018, 106336.34733019, 107584.99034227,
       108089.2320392 , 106786.91702337]),
 np.array([106786.91702337, 104416.74000465, 101289.12525402, 101932.58219813,
       102625.04352578, 101767.46209616, 103345.4263012 , 102816.73322055,
       102417.59316407, 104439.37518975, 103755.22627215, 103817.9744686 ,
       107872.40234863, 108110.9662065 ]),
 np.array([108110.9662065 , 109544.86827069, 111072.22392645, 112618.46235766,
       113847.1768898 , 116708.86391903, 115790.02599715, 115614.72242411,
       119225.88436354, 121991.38468934, 123304.85972848, 125571.38040251,
       122456.3667249 ]),
 np.array([122456.3667249 , 127497.74699282, 128659.85495604, 125813.77115906,
       129008.46450085, 128111.00914756, 123039.92607546, 124723.87932757,
       124181.57385836, 125134.9276196 , 126027.8631434 , 129304.85119148,
       128912.58600657])]

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