Pythonic way of Adding Columns to Array

Question

I'm trying to combine an mxn array called data with a list of m elements called cluster_data such that each element in the list cluster_data is appended as the last element of each of the rows in data.

As an example, I would want something like to combine

data = [[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16],[17,18,19,20]]

cluster_data = [1,2,3,4,5]

Such that

final_data = [[1,2,3,4,1],[5,6,7,8,2],[9,10,11,12,3],[13,14,15,16,4],[17,18,19,20,5]]

I have written some code that does this, but I was hoping for a more Pythonic way.

data_with_clusters = []    
for i, row in enumerate(data):
    row.append(cluster_data[i])
    data_with_clusters.append(row)

My best guess so far, which doesn't work, is:

data_with_clusters = [row.append(cluster_data[i]) for i, row in enumerate(data)]

Yash Mehrotra · Accepted Answer · 2015-10-28 22:04:35Z

5

I think this is the most pythonic way

final_data = [i+[j] for i,j in zip(data, cluster_data)]

answered Oct 28, 2015 at 22:04

Yash Mehrotra

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Karoly Horvath · Accepted Answer · 2015-10-28 22:02:12Z

2

The problem with your approach is that append doesn't return anything.

Instead of append, merge lists:

[row + [cluster_data[i]] for i, row in enumerate(data)]

or

[e[0] + [e[1]] for e in zip(data, cluster_data)]

answered Oct 28, 2015 at 22:02

Karoly Horvath

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3 Comments

Alexander Moore Over a year ago

Works perfectly. I used the first one. Can you explain why you need brackets around cluster_data[i]?

Karoly Horvath Over a year ago

The + operator in this case merges two lists.

Karoly Horvath Over a year ago

Please accept Yash's solution, it's really the most pythonic one.

oz123 · Accepted Answer · 2015-10-28 23:09:22Z

2

A Pythonic way would be to use Array first thing first. Lists are commonly abused as array, because they share some similarity.

But a more Pythonic way, if you often work with numbers is to use NumPy. Which makes such operations a piece of cake.

The answers with list comprehension given previously are fine too, but they will be extremely slow for large arrays.

Here is your intro to NumPy:

In [2]: import numpy as np
In [3]: array = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16],[17,18,19,20]])

In [3]: array
Out[3]: 
array([[ 1,  2,  3,  4],
       [ 5,  6,  7,  8],
       [ 9, 10, 11, 12],
       [13, 14, 15, 16],
       [17, 18, 19, 20]])

In [4]: col = np.array([[1],[2],[3],[4],[5]])
In [4]: col
Out[4]: 
array([[1],
       [2],
       [3],
       [4],
       [5]])

In [5]: np.append(array, col, axis=1)
Out[5]: 
array([[ 1,  2,  3,  4,  1],
       [ 5,  6,  7,  8,  2],
       [ 9, 10, 11, 12,  3],
       [13, 14, 15, 16,  4],
       [17, 18, 19, 20,  5]])

edited Oct 28, 2015 at 23:09

answered Oct 28, 2015 at 22:14

oz123

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3 Comments

oz123 Over a year ago

Also if you are crunching many numbers with python you should get familiar with IPython, which the code snippets in my answer are from

Alexander Moore Over a year ago

Thanks for your suggestion. About IPython and NumPy in particular. I was not aware that NumPy was so much more convenient!

oz123 Over a year ago

Numpy is defacto the standard for working with array and matrix. If you do a lot of number crunching, take a look into scipy and pandas too.

RobertB · Accepted Answer · 2015-10-28 22:02:39Z

1

row.append(cluster_data[i]) returns None, so that doesn't work,

Try instead: row + [cluster_data[i]]

answered Oct 28, 2015 at 22:02

RobertB

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