I have a NumPy ndarray to which I would like to add row/column headers.
The data is actually 7x12x12, but I can represent it like this:
A=[[[0, 1, 2, 3, 4, 5],
[1, 0, 3, 4, 5, 6],
[2, 3, 0, 5, 6, 7],
[3, 4, 5, 0, 7, 8],
[4, 5, 6, 7, 0, 9],
[5, 6, 7, 8, 9, 0]]
[[0, 1, 2, 3, 4, 5],
[1, 0, 3, 4, 5, 6],
[2, 3, 0, 5, 6, 7],
[3, 4, 5, 0, 7, 8],
[4, 5, 6, 7, 0, 9],
[5, 6, 7, 8, 9, 0]]]
where A is my 2x6x6 array.
How do I insert headers across the first row and the first column, so that each array looks like this in my CSV output file?
A, a, b, c, d, e, f
a, 0, 1, 2, 3, 4, 5,
b, 1, 0, 3, 4, 5, 6,
c, 2, 3, 0, 5, 6, 7,
d, 3, 4, 5, 0, 7, 8,
e, 4, 5, 6, 7, 0, 9,
f, 5, 6, 7, 8, 9, 0
What I have done is made the array 7x13x13 and inserted the data such that I have a row and column of zeros, but I’d much prefer strings.
I guess I could just write an Excel macro to replace the zeros with strings. However, the problem is that NumPy cannot convert string to float, if I try to reassign those zeros as the strings I want.
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Answer
Numpy will handle n-dimensional arrays fine, but many of the facilities are limited to 2-dimensional arrays. Not even sure how you want the output file to look.
Many people who would wish for named columns overlook the recarray() capabilities of numpy. Good stuff to know, but that only “names” one dimension.
For two dimensions, Pandas is very cool.
In [275]: DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])],
.....: orient='index', columns=['one', 'two', 'three'])
Out[275]:
one two three
A 1 2 3
B 4 5 6
If output is the only problem you are trying to solve here, I’d probably just stick with a few lines of hand coded magic as it will be less weighty than installing another package for one feature.