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In computer programming, profile-guided optimization (PGO, sometimes pronounced as pogo [1]), also known as profile-directed feedback (PDF) [2] or feedback-directed optimization (FDO), [3] is the compiler optimization technique of using prior analyses of software artifacts or behaviors ("profiling") to improve the expected runtime performance of the program.
However, if data is a DataFrame, then data['a'] returns all values in the column(s) named a. To avoid this ambiguity, Pandas supports the syntax data.loc['a'] as an alternative way to filter using the index. Pandas also supports the syntax data.iloc[n], which always takes an integer n and returns the nth value, counting from 0. This allows a ...
Python: Python profiling includes the profile module, hotshot (which is call-graph based), and using the 'sys.setprofile' function to trap events like c_{call,return,exception}, python_{call,return,exception}. Ruby: Ruby also uses a similar interface to Python for profiling. Flat-profiler in profile.rb, module, and ruby-prof a C-extension are ...
Police said their K9, named Bumi, died on Monday, Dec. 23, after being sent out on a mission with his handler, Ware, to track suspects that “fled from a stolen vehicle.” During the mission ...
Vitamin D with or without calcium doesn't reduce the risk of falls or fractures in generally healthy older adults, according to a new draft recommendation from the US Preventive Services Task Force.
Michael Brewer, one-half of the folk-rock duo Brewer & Shipley, has died. He was 80. On Tuesday, Dec. 17, Brewer's musical partner, Tom Shipley, confirmed the news of his death in a Facebook post ...
This category is a catch-all for errors reported by Module:String. Such errors generally occur due to incorrect parameters, such as indices that are out of range for the strings being examined. Users of Module:String may also specify an alternative cat to use via the error_category= parameter.
Data profiling utilizes methods of descriptive statistics such as minimum, maximum, mean, mode, percentile, standard deviation, frequency, variation, aggregates such as count and sum, and additional metadata information obtained during data profiling such as data type, length, discrete values, uniqueness, occurrence of null values, typical string patterns, and abstract type recognition.