# Analysis of table to make compressing model

I have a table with hundred of entries in this style:

//HEADER//CODE1//decimals_here//CODE4//decimals_here//CODE3//decimals_here//CODE5//decimals_here//ENDING//

I want to make a simple text compressor that works for only 1 entry at each time. Can someone give me a kickstart hint to start playing in Orange?

1. Where do I split the text for better analysis? Can I find that also in Orange?
2. How can I get the most repeated/common segments and their occurrence?

Thanks

• See Preprocess Text widget > Tokenization, then Bag of Words to get term frequency. I found the widgets here: orangedatamining.com/widget-catalog Jan 29, 2021 at 0:24
• Nice thanks! I wonder if there is something similar to find 2 words in sequence that are common in a similar way Feb 1, 2021 at 9:15