R will not have to learn on the check book "R data science" tool is not the point, the purpose is to create value. Specific to the scientific data, forms often offer solutions or make some kind of decision. As for what language, using what tools, not nature. With R or Python or Julia, it can be.
Tools will affect the efficiency of output per unit of time. Under typical data analysis scenarios, productivity may not mark a start to write a service framework to ensure high concurrency, because the direction of the business may have not given it. So this time the productivity mark is often found as soon as possible, as soon as possible to verify various models, to make a reasonable decision as soon as possible.
Learning Reference:
"R Data Science" HD Chinese PDF, 374 pages, catalogs and bookmarks, color with pictures, text can be copied; HD English PDF, 520 pages, catalogs and bookmarks, color with pictures, text can be copied; the English version two can contrast learning, supporting source code.
Network disk download: http://106.13.73.98
