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JULIA QUICK SYNTAX REFERENCE : a pocket guide for data science programming.

Author: ANTONELLO LOBIANCO
Publisher: [S.l.] : APRESS, 2020.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Additional Physical Format: (OCoLC)1107601988
Material Type: Document
Document Type: Book, Computer File
All Authors / Contributors: ANTONELLO LOBIANCO
ISBN: 9781484251904 1484251903
OCLC Number: 1127935850
Description: 1 online resource
Contents: Language core (book part)Getting started (chapter)Allow reader to set up with the software needed to run Julia and let her run her first Hello World. Packages are introduced as early as this section. Why Julia Installing Julia Running Julia Main syntax elements Packages Help systemData types (chapter)Make reader familiar with the Julia concept of types, showing her the different containers that Julia make available for rapid application development. Scalar types Strings Concatenation Arrays (lists) Multidimensional and nested arrays Tuples NamedTuples Dictionaries Sets Memory and copy issues Various notes on Data types Random numbers Missing, nothing and NaNControl flow (chapter)Vectorised or classical loop-based code ? This section explains how to obtain them in Julia Logical operators Do blocksFunctions (chapter)Julia is rich in the way you can handle functions, and this chapter try to present all the related notions to the reader Arguments Return value Multiple-dispatch (aka polymorphism) Templates (type parametrisation) Functions as objects Call by reference / call by value Anonymous functions BroadcastCustom structures (chapter)If you can from an object-oriented language you would expect this section. We show how you can organise your data in Julia and make it connect in your program. Defining a structure Initialising an object and accessing its fields Implementation of the OO paradigm in Julia More on typesInput - Output (chapter)Feed your program with data and retrieve its outputs File reading/writing Networking IO Other IOManaging run-time errors (exceptions) (chapter)How to set a plan-B if things go wrong in your codeInterfacing Julia with other languages (chapter)Do not reinvent the wheel: use what's already be done, even if developed in other languages C/C++ Python RMetaprogramming (chapter)Provide a richer API modifying the code before it is executed Expressions Colon prefix operator Quote block Parse a string Use the Exp constructor with a tree Symbols MacrosPerformances (parallelisation, debugging, profiling..) (chapter)One of the main reason why Julia exists is performances. It's easy to obtain them. We write here how not to make errors that would hit performances. Type safety Benchmarking Code parallelisation Debugging ProfilingDeveloping Julia packages (chapter)Learn how to organise code that provide similar functionalities in a package, either for yourself or for the general public Packages ecosystem (book part)Working with data (chapter)The rich ecosystem Julia provides for working with data DataFrames Install and import the library Create a df or load data: Get insights about your data: Edit data Edit structure Manage Missing values Split-Apply-Combine strategy Pivot Export your data IndexedTables Create an IndexedTable Edit values LAJuliaUtilsMathematics (chapter)Not a mathematician? Still don't skip this chapter, you may discover you can still benefit in your work from mathematic libraries without knowing their theoretical fundations. JuMP SymPy Other Mathematical packagesUtilities (chapter)From plotting to writing scientific papers with embedded code, a list of packages you will probably want to use Plotting Pipe Weave

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