Expand DataFrame using Pandas

Question

I'm working with a feature set structured like the following, which has 150 features:

-1 45:1 55:1 67:1
1  55:1 65:1 89:1

How can I use pandas to expand this data set such that it's a full matrix or array with all 150 features? In other words in the first row feature 44 is 0, so I would like to use pandas to make something like:

[-1,0,0,0,...(44th entry)0,1,...
1,0,0,0,...(54th entry)0,1,...]

Basically I assume there is a way in pandas to do this so I don't write a for loop and generate a zeros matrix and have it fill in the values. Am I seeking to do something like this : Fill a Pandas dataframe using information from another Pandas dataframe Or is there a better implementation since my problem seems less complex. Thanks as I am new to pandas.

I don't understand how your input data is structured, what type of object is that? Are the -1 and 1 at the beginning supposed to be indices? — Emma
– Emma, Commented Jan 21, 2016 at 19:57
no they are binary classifiers or imagine a matrix like [y|x1 x2 x3,...] — eWizardII
– eWizardII, Commented Jan 22, 2016 at 1:52

eWizardII · Accepted Answer · 2016-02-19 03:31:08Z

0

Turns out the data was in svm_light format so I used the approbate python module - problem solved!

answered Feb 19, 2016 at 3:31

eWizardII

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