CODEWITHSUNDEEP
pythonarraysnumpytypes
Tbevans88
Tbevans88

Reputation: 103

Combining two 1D arrays of different data types into 1 2D array in PYTHON

I have 2 lists of numbers: a and b. A is a list of node numbers with type integer and b is a list of X coordinates with type float64. I want to combine these 2 equal length arrays (N) into an Nx2 array that preserves the data types. I am using this array later on in some boolean tests, so I need the first column to be integers. I've been using:

nodeID = np.concatenate([[a],[b]]).T

but obviously this converts everything into floating point numbers.

Thanks!

Upvotes: 1

Views: 3161

Answers (4)

Sdwdaw
Sdwdaw

Reputation: 1037

zip function is the simpliest way. The short example:

>>> a = [1, 2, 3, 4, 5]
>>> b = [1.1, 2.2, 3.3, 4.4, 5.5]
>>> zip(a,b)
[(1, 1.1), (2, 2.2), (3, 3.3), (4, 4.4), (5, 5.5)]
>>>

If you want to get a from the zip(a,b), just write:

>>> [x[0] for x in zip(a, b)]
[1, 2, 3, 4, 5]

A good idea is to make dictionary from two lists:

>>> keys = [1,2,3,4,5]
>>> values = [1.1,2.2,3.3,4.4,5.5]
>>> dictionary = dict(zip(keys, values))
>>> dictionary
{1: 1.1, 2: 2.2, 3: 3.3, 4: 4.4, 5: 5.5}

But be carefull, the order in the dictionary is not saved. Access to the data from the dictionary is very simple:

>>> dictionary.keys()
[1, 2, 3, 4, 5]
>>> dictionary.values()
[1.1, 2.2, 3.3, 4.4, 5.5]
>>> dictionary[1]
1.1
>>>

Upvotes: 0

Wover
Wover

Reputation: 1

I'm assuming because you mentioned a 2D list in the title that what you want a list like the one below, where each node and coord have their type preserved:

[[node1, coord1], [node2, coord2], ... ]

You can do this in three quick lines without any modules, preserving the type of each variable:

nodeID = []
for i, node in enumerate(a):
    nodeID.append([node, b[i]])

Thus, you will have a 2D list. Each element in the 2D list will itself be another list containing a pair of a node and a coordinate. Since Python is so type-insensitive, the type of both your node and your coordinate will be preserved. You will access each pair with:

pair1 = nodeID[0]
pair2 = nodeID[1]
pairx = nodeID[x]

And their contents with:

node1 = nodeID[0[0]]
node2 = nodeID[1[0]]
coord1 = nodeID[0[1]]
coord2 = nodeID[1[1]]

Hopefully that helps. :-)

Upvotes: 0

serge-sans-paille
serge-sans-paille

Reputation: 2139

One way to achieve your goal is to use numpy's dtype as documented in http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html

>>> import numpy as np
>>> dt = np.dtype([('a', np.int64, 1), ('b', np.float64, 1)])
>>> a = np.array([1,2,3,4], dtype=np.int64)
>>> b = np.array([1.,2.,3.,4.], dtype=np.float64)
>>> ab = np.array(zip(a,b), dtype=dt)
>>> ab[:]['a']
array([1, 2, 3, 4])
>>> ab[:]['b']
array([ 1.,  2.,  3.,  4.])

Upvotes: 3

Ahasanul Haque
Ahasanul Haque

Reputation: 11144

You can use zip() here. If you just compare the element of list a, then what is the problem here? 

a =[1,2,3,4]
b =["Hello", "world", "fellow"]

x=zip(a,b)
print x

for a,b in x:
  if a == someThing:
     doSomething()

Upvotes: 0

Related Questions