Merging numpy array elements using join() in python

Merging numpy array elements using join() in python

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Merging numpy array elements using join() in python
Tag : python , By : Frank Rotolo
Date : November 29 2020, 09:01 AM

wish help you to fix your issue Want to convert the following numpy array a
In [144]: " , ".join(" * ".join(".".join(str(xx) + '!' + str(yy) for xx, yy in zip(x[:, 0], x[:, _x])) for _x in range(1, len(x[0]))) for x in a)
Out[144]: 'x!y.d!2.a!15 * x!k.d!z.a!r , p!49.l!n , 5!y.33!u.v!z , f!i.c!m.u!98'

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Python/Pandas - Merging dataframe with numpy array in a peculiar way

Tag : python , By : Timbo
Date : March 29 2020, 07:55 AM
wish helps you Try np.tile() to get repeat your array coef as many times as you need:
pd.DataFrame(np.tile(coef, (len(df.index), 1)), columns=['Coef']*5)

Python numpy array merging manipulation

Tag : python , By : Matt Watson
Date : March 29 2020, 07:55 AM
I think the issue was by ths following , With a as the array and L as the list, you could simply get a flattened view of the array with np.ravel() and assign values from L by slicing into it, like so -
a.ravel()[:len(L)] = L
np.put(a, range(len(L)), L)
In [51]: a
array([[[91, 18, 74],
        [49, 92, 93],
        [42, 38, 41],
        [27, 24, 69]],

       [[14, 72, 49],
        [85, 74, 45],
        [32, 88, 89],
        [12, 85, 60]]])

In [52]: L = [120, 99, 0, 88, 78, 32, 123]

In [53]: a.ravel()[:len(L)] = L

In [54]: a
array([[[120,  99,   0],
        [ 88,  78,  32],
        [123,  38,  41],
        [ 27,  24,  69]],

       [[ 14,  72,  49],
        [ 85,  74,  45],
        [ 32,  88,  89],
        [ 12,  85,  60]]])

remove specific elements from numpy array [PREVIOUSLY] selecting elements by data type from a numpy array

Tag : python , By : micate
Date : March 29 2020, 07:55 AM
hop of those help? Note that numpy.select takes an arbitrary condition list. You could use the condition isinstance(x, str) to check if x is of type str

Merging array elements based on other arrays elements in Python

Tag : python , By : Mr. Tacos
Date : March 29 2020, 07:55 AM
I hope this helps . Use zip_longest to create key-value pairs of elements and then use itertools.groupby to group them together based on the key.
>>> from itertools import groupby
>>> l = ['409597', ['You'], '409597', ['matter'], '409597', ['manager'], '809558', ['metro'], '809558', ['station'], '829258', ['bucket'], '829258', ['water']]
>>> [[e[1][0] for e in list(v)] for k,v in groupby(zip_longest(*([iter(l)]*2)), lambda x: x[0])]
[['You', 'matter', 'manager'], ['metro', 'station'], ['bucket', 'water']]
ld = [[{'Instant_ID': 409597}, {'Token': 'You'}], [{'Instant_ID': 409597}, {'Token': 'matter'}], [{'Instant_ID': 409597}, {'Token': 'manager'}], [{'Instant_ID': 809558}, {'Token': 'metro'}], [{'Instant_ID': 809558}, {'Token': 'station'}], [{'Instant_ID': 829258}, {'Token': 'bucket'}], [{'Instant_ID': 829258}, {'Token': 'water'}]]
>>> [[e[1]['Token'] for e in v] for k,v in groupby(ld, lambda x: x[0]['Instant_ID'])]
[['You', 'matter', 'manager'], ['metro', 'station'], ['bucket', 'water']]

Fast python algorithm (in numpy or pandas?) to find indices of array elements that match elements in another array

Tag : python , By : user186876
Date : March 29 2020, 07:55 AM
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