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Data Structures And Other Objects Using C - 4th Edition.zip



Data Structures and Other Objects Using C++ takes a gentle approach to the data structures course in C++. Providing an early, self-contained review of object-oriented programming and C++, this text gives students a firm grasp of key concepts and allows those experienced in another language to adjust easily. Flexible by design, professors have the option of emphasizing object-oriented programming, covering recursion and sorting early, or accelerating the pace of the course. Finally, a solid foundation in building and using abstract data types is also provided, along with an assortment of advanced topics such as B-trees for project building and graphs.




Data Structures and Other Objects Using C - 4th edition.zip



1A provides students with the opportunity to build skills and knowledge in the following areas: problem solving and algorithm development, C and C++ programming, software development tools, programming language paradigms (structured, functional and object-oriented programming), basic UNIX utilities and tools, basic data structures including arrays and linked lists representations of lists, stacks, queues, and binary trees, binary and linear search, sorting techniques, iteration vs. recursion, basic running time analysis, data representation.


With Panel, describing the matching behavior is a bit more difficult, sothe arithmetic methods instead (and perhaps confusingly?) give you the optionto specify the broadcast axis. For example, suppose we wished to demean thedata over a particular axis. This can be accomplished by taking the mean overan axis and broadcasting over the same axis:


In Series and DataFrame (though not yet in Panel), the arithmetic functionshave the option of inputting a fill_value, namely a value to substitute whenat most one of the values at a location are missing. For example, when addingtwo DataFrame objects, you may wish to treat NaN as 0 unless both DataFramesare missing that value, in which case the result will be NaN (you can laterreplace NaN with some other value using fillna if you wish).


For example, we can fit a regression using statsmodels. Their API expects a formula first and a DataFrame as the second argument, data. We pass in the function, keyword pair (sm.poisson, 'data') to pipe:


reindex() is the fundamental data alignment method in pandas.It is used to implement nearly all other features relying on label-alignmentfunctionality. To reindex means to conform the data to match a given set oflabels along a particular axis. This accomplishes several things:


The copy() method on pandas objects copies the underlying data (though notthe axis indexes, since they are immutable) and returns a new object. Note thatit is seldom necessary to copy objects. For example, there are only ahandful of ways to alter a DataFrame in-place:


To be clear, no pandas methods have the side effect of modifying your data;almost all methods return new objects, leaving the original objectuntouched. If data is modified, it is because you did so explicitly.


pandas offers various functions to try to force conversion of types from the object dtype to other types.In cases where the data is already of the correct type, but stored in an object array, theDataFrame.infer_objects() and Series.infer_objects() methods can be used to soft convertto the correct type.


In addition to object conversion, to_numeric() provides another argument downcast, which gives theoption of downcasting the newly (or already) numeric data to a smaller dtype, which can conserve memory:


In Series and DataFrame, the arithmetic functions have the option of inputtinga fill_value, namely a value to substitute when at most one of the values ata location are missing. For example, when adding two DataFrame objects, you maywish to treat NaN as 0 unless both DataFrames are missing that value, in whichcase the result will be NaN (you can later replace NaN with some other valueusing fillna if you wish).


The T_FIXNUM data is a 31bit or 63bit length fixed integer. This size depends on the size of long: if long is 32bit then T_FIXNUM is 31bit, if long is 64bit then T_FIXNUM is 63bit. T_FIXNUM can be converted to a C integer by using the FIX2INT() macro or FIX2LONG(). Though you have to check that the data is really FIXNUM before using them, they are faster. FIX2LONG() never raises exceptions, but FIX2INT() raises RangeError if the result is bigger or smaller than the size of int. There are also NUM2INT() and NUM2LONG() which converts any Ruby numbers into C integers. These macros include a type check, so an exception will be raised if the conversion failed. NUM2DBL() can be used to retrieve the double float value in the same way.


Wrap a C pointer into a Ruby object. If object has references to other Ruby objects, they should be marked by using the mark function during the GC process. Otherwise, mark should be 0. When this object is no longer referred by anywhere, the pointer will be discarded by free function.


Inserting write barriers into T_DATA objects only works with the following type objects: (a) long-lived objects, (b) when a huge number of objects are generated and (c) container-type objects that have references to other objects. If your extension provides such a type of T_DATA objects, consider inserting write barriers.


For example, if your T_DATA has references to other objects, then you can move these references to Array. A T_DATA object only has a reference to an array object. Or you can also use a Struct object to gather a T_DATA object (without any references) and an that Array contains references.


The T_FIXNUM data is a 31bit or 63bit length fixed integer. This sizedepends on the size of long: if long is 32bit then T_FIXNUM is 31bit, iflong is 64bit then T_FIXNUM is 63bit. T_FIXNUM can be converted to a Cinteger by using the FIX2INT() macro or FIX2LONG(). Though you have tocheck that the data is really FIXNUM before using them, they are faster. FIX2LONG() never raises exceptions, but FIX2INT() raises RangeError if the result is bigger or smallerthan the size of int. There are also NUM2INT() and NUM2LONG() whichconverts any Ruby numbers into C integers. These macros include a typecheck, so an exception will be raised if the conversion failed. NUM2DBL()can be used to retrieve the double float value in the same way.


Wrap a C pointer into a Ruby object. If object has references to otherRuby objects, they should be marked by using the mark function during theGC process. Otherwise, mark should be 0. Whenthis object is no longer referred by anywhere, the pointer will bediscarded by free function.


Ruby supports I/O multiplexing based on the select(2) system call. TheLinux select_tut(2) manpage provides a good overview on how to use select(2), and the Ruby API hasanalogous functions and data structures to the well-known select API.Understanding of select(2) is required to understand this section.


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