Matlab Clustering technique with textual data

Hi, I am trying to figure out the best way to cluster numeric information (stock returns) using a series of textual information. For instance, let's say I have 10 sectors with of stock returns that I'd like to cluster to 3 distinct groups. My first thought was to use the K-means clustering algorithm from the "Stats and ML" toolbox however, it doesn't take textual information as a descriptor.

Please advise.

Example data set

Industry, Return
Financials,2%
Consumer Disc,3%
Consumer Staples,4.5%
Energy,1%
Health Care,1.5%
Industrials,2.2%
Info Tech,3.7%
Materials,4.8%
Telecom,-2%
Utilities,-1%

[Brian]

Any ideas on this from statistical experts?

Answer 1

[mizuki]

Make the textual data categorical to reduce information.