# Chart for seeing trends, correlations, triggers and patterns

I've scraped a set of data, and I was wandering what the best way to start analyzing it was. My initial thoughts were to use a multi y axis graph, like this:

The reason I was thinking about a multi axis graph was because if they were using the same axis some of the data would be way overstretched for the axis. That is, some of the data sets are 10-100 others are 10,000-100,000, but I wasn't sure if this is best suited.

I'm comparing tweet sentiment of a particular stock, to the performance of that stock, I've got up to 7 data sets to compare -

• tweet volume
• sentiment-pos
• sentiment-nue
• sentiment-neg
• stock sell price

Any idea of the best way to visualize this, is to allow me to view patterns and correlations?

Also is this usually done on a chart or can it be done by running VBA or other scripting language to find correlations in the data?

• @Bitwise We welcome questions here that ask for creative methods to visualize and analyze data. This one doesn't sound like it's just looking for some canned code. – whuber Jun 19 '13 at 22:09
• @whuber Ok sorry. I thought the question is mostly about how to implement this kind of overlayed plot. Reading through it again I believe you are right. – Bitwise Jun 20 '13 at 0:59
• @bitwise - Just to clarify, im just trying to work out the best way to visulise the data so i can see if there are any correlations between the sentiment and stock price / volume, my initial thoughts were to use the above line chart and try and see a pattern visulay. But if theres a more scientific or automated way to try a see correlations im open to that aswell. – sam Jun 20 '13 at 9:46
• I would plot in dimensionless coordinates. For each series, subtract the min, then divide by the range of that series. When you plot it, they will all range from 0 (minimum) to 1 (maximum). When comparing a number of items, a radar or polar plot can be more informative. You might consider one of those. – EngrStudent - Reinstate Monica Aug 20 '13 at 19:22