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I have a CSV file with a set of words occurrences in several documents.
The first column is the document it. The second column states the text topic (there are 5 different topics). The other columns indicate whether a word occurs in this document (1) or not (0), so it is a binary representation.

Here is an extract:

id,topic,w_hello,w_apple,w_tomato
1,politics,1,1,0
2,sport,0,1,0
3,politics,1,0,1

My actual CSV consists of over 10.000 words.

I now want to visualize.

My first approach was just plot each word individually with a bar plot:

plot

  • x-axis: the different words
  • y-axis: number of occurrences per document

But as you can see, with over 10.000 words the plot looks very confusing.

Are there any other approaches to visualize it?
Is there something else interesting I can do with my CSV? I'm just playing around.

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  • $\begingroup$ There are a lot of different things you could do. What are you interested in ? Once you have an objective, you can search how to properly visualize this data set. You could compare word occurrences per topics, or look at document similarity, or topics similarity, or defining key word for each topics or build a model to predict topics based on word occurrences or detect which word is useless to compare topics ... $\endgroup$ – Romain Dec 19 '15 at 18:59
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Here are a few cool websites that generate a visualization of a text document that captures the word counts:

Here are two examples of what you can get:

enter image description here

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In addition to Sobi's answer: There are open tools (like UAM, python, R, or javascript packages) available to create word clouds. Some tutorials on how-to achieve this can be found on the CLARIN-D TeLeMaCo service here https://fedora.clarin-d.uni-saarland.de/hub/kwsearch/word%20cloud/0/

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