Issue
I'll try to be as clear as possible, and I'll start by explaining why I want to transform two arrays into a matrix.
To plot the performance of a portfolio vs an market index I need a data structure like in this format:
[[portfolio_value1, index_value1]
[portfolio_value2, index_value2]]
But I have the the data as two separate 1-D arrays:
portfolio = [portfolio_value1, portfolio_value2, ...]
index = [index_value1, index_value2, ...]
So how do I transform the second scenario into the first. I've tried np.insert
to add the second array to a test matrix I had in a python shell, my problem was to transpose the first array into a single column matrix.
Any help on how to achieve this without an imperative loop would be great.
Solution
The standard numpy function for what you want is np.column_stack
:
>>> np.column_stack(([1, 2, 3], [4, 5, 6]))
array([[1, 4],
[2, 5],
[3, 6]])
So with your portfolio
and index
arrays, doing
np.column_stack((portfolio, index))
would yield something like:
[[portfolio_value1, index_value1],
[portfolio_value2, index_value2],
[portfolio_value3, index_value3],
...]
Answered By - Jaime
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