November 2016
Intermediate to advanced
697 pages
14h 44m
English
Content preview from Julia: High Performance ProgrammingBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Data arrays and data frames
Users of R will be aware of the success of data frames when employed in analyzing datasets, a success which has been mirrored by Python with the pandas package. Julia too adds data frame support through use of a package DataFrames, which is available on GitHub, in the usual way.
The package extends Julia's base by introducing three basic types:
NA: An indicator that a data value is missingDataArray: An extension to theArraytype that can contain missing valuesDataFrame: A data structure for representing tabular datasets
It is such a large topic that we will be looking at data frames in some depth when we consider statistical computing in Chapter 4, Interoperability.
However, to get a flavor of processing data with these ...
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