How to compile data

Exporting bar-data from SC to CSV for "import" into Excel is a simple matter.
http://www.sierrachart.com/index.php?l=doc/doc_ImportExport.html

Alternatively, you can add a "Spreadsheet Study" to your chart and the bar data will populate a SC Spreadsheet. You can then cut and paste into excel.

Additionally, for a VISUAL ONLY of your example, I've attached a chart of NQ using 2 hours bars. Nothing fancy. A SC default candlestick chart with 2 studies.
The 2 studies are both "Color Bar Based On Alert Condition"... so 2 instances of that one study. All study parameters are default values. The Alert tab in each study contains an alert formula. The formulas (1 in each of the alert tabs of each study)...
AND(H-L > 10, C > O) this is the purple bar
AND(H-L > 10, C < O) this is the yellow bar
Of course I had to choose the color for each study in the "Subgraphs" tab of each study.
Alert formula documentation is here...
http://www.sierrachart.com/index.php?l=doc/doc_AlertCondAndScan.html#AlertConditionFormulaFormat

Hope that helps
I really think you're making this too difficult... No formal programming is needed.


It does. Thanks. I played around with it and yes while raw data can be exported to excel, it still requires a lot of manipulation. Example: If I want values for the 'Time' that High/Low was made, I have to first output all the data from the High/Low study and then do all sorts of sorting to get the time during which High/Low was made. Not terribly time intensive though. Would be nice to know how to get it in one step.
 
I have been reading the following book:

http://www.amazon.com/Data-Smart-Sc...TF8&qid=1401569815&sr=8-1&keywords=data+smart

While the majority of the book is about developing prototypes in excel, the author concludes by saying that once the basics are covered, it's time to learn R. He say's that while R is excellent for application it is poor for learning since everything is already loaded up in the libraries and ready to go. Excel meanwhile, allows one to develop a hands on feel for the data. So excel is great for learning and R is great for execution.

Yeah R is pretty good for statistical work. If you're going in that direction checkout Roger Peng's class in coursera. It's part of the data analisys specialization n u can take it for free.
 
It does. Thanks. I played around with it and yes while raw data can be exported to excel, it still requires a lot of manipulation. Example: If I want values for the 'Time' that High/Low was made, I have to first output all the data from the High/Low study and then do all sorts of sorting to get the time during which High/Low was made. Not terribly time intensive though. Would be nice to know how to get it in one step.

Use the INDEX MATCH formula to get the time/date that the H/L were made. You can do it in Sierra Charts, but if you are pulling the data from one sheet to another, be aware of the problem with comparing serial date-time values between sheets - you get incorrect values returned (see link below). A work around is to put the INDEX MATCH in the same sheet as the data and pull it over with a simple cell reference.

http://www.sierrachart.com/index.php?l=doc/doc_WorksheetFunctions.html
 
Yeah R is pretty good for statistical work. If you're going in that direction checkout Roger Peng's class in coursera. It's part of the data analisys specialization n u can take it for free.

Yes nice to get validation for it. I had browsed coursera earlier and saved the following for possible followup

https://www.coursera.org/course/datascitoolbox

Not sure if I need to go all in on data analysis . Although the 'Data Smart' book was a great eyeopener to what is possible.
 
Use the INDEX MATCH formula to get the time/date that the H/L were made. You can do it in Sierra Charts, but if you are pulling the data from one sheet to another, be aware of the problem with comparing serial date-time values between sheets - you get incorrect values returned (see link below). A work around is to put the INDEX MATCH in the same sheet as the data and pull it over with a simple cell reference.

http://www.sierrachart.com/index.php?l=doc/doc_WorksheetFunctions.html

I will look at it JT and be sure to ask you any followup questions. Amazing how despite having used excel for years, I wasn't even aware of VLookup, Pivots, Index, Match. Market making me catch up now.
 
Yes nice to get validation for it. I had browsed coursera earlier and saved the following for possible followup

https://www.coursera.org/course/datascitoolbox

Not sure if I need to go all in on data analysis . Although the 'Data Smart' book was a great eyeopener to what is possible.

I got started into computer science from courseras data science courses (they had different names back in 2012 but were basically the same idea)

There's a course from GATech called computational investments that leans a lot more towards analyzing financial data on python.
 
A note on Quandl, which is referenced above:

I wasted some time running continuous futures contracts through Hoadley Tools, not realizing the data sets were full of holes. Now, I zoom the graphs within Quandl before downloading and can find the holes and error spikes and make a decision as to whether the data can be repaired quickly or whether it's garbage.

Unfortunately, a lot of the futures data is garbage. I like Quandl, but they're still new and apparently they don't curate the thousands and thousands of data sets they have available. I hope they improve in the future, but in the meantime, check their data visually or with some simple stats before you use it, and if you need a very clean price series, you're probably going to have to buy it.
 
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