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However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values. For example, if s is a Series, s['a'] will return the data point at index a. Unlike dictionary keys, index values are ...
For example, appending addresses with any phone numbers related to that address. Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [ 2 ] and transforming it into one cohesive data set; a simple example is the ...
A dictionary coder, also sometimes known as a substitution coder, is a class of lossless data compression algorithms which operate by searching for matches between the text to be compressed and a set of strings contained in a data structure (called the 'dictionary') maintained by the encoder. When the encoder finds such a match, it substitutes ...
An example of Python code and indentation Example of C# code with curly braces and semicolons Python is meant to be an easily readable language. Its formatting is visually uncluttered and often uses English keywords where other languages use punctuation.
The practice of always using references in place of copies of equal objects is known as interning. If interning is used, two objects are considered equal if and only if their references, typically represented as pointers or integers, are equal. Some languages do this automatically: for example, Python automatically interns short strings. If the ...
A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet Σ. Σ may be a human language alphabet, for example, the letters A through Z and other applications may use a binary alphabet (Σ = {0,1}) or a DNA alphabet (Σ = {A,C,G,T}) in bioinformatics.
Identifying the in-place algorithms with L has some interesting implications; for example, it means that there is a (rather complex) in-place algorithm to determine whether a path exists between two nodes in an undirected graph, [3] a problem that requires O(n) extra space using typical algorithms such as depth-first search (a visited bit for ...
A single edit operation may be changing a single symbol of the string into another (cost W C), deleting a symbol (cost W D), or inserting a new symbol (cost W I). [2] If all edit operations have the same unit costs (W C = W D = W I = 1) the problem is the same as computing the Levenshtein distance of two strings.