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For including parser functions, variables and behavior switches, see Help:Magic words; For a guide to displaying mathematical equations and formulas, see Help:Displaying a formula; For a guide to editing, see Wikipedia:Contributing to Wikipedia; For an overview of commonly used style guidelines, see Wikipedia:Simplified Manual of Style
[4]: 114 A DataFrame is a 2-dimensional data structure of rows and columns, similar to a spreadsheet, and analogous to a Python dictionary mapping column names (keys) to Series (values), with each Series sharing an index. [4]: 115 DataFrames can be concatenated together or "merged" on columns or indices in a manner similar to joins in SQL.
Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow ...
Code generation is the process of generating executable code (e.g. SQL, Python, R, or other executable instructions) that will transform the data based on the desired and defined data mapping rules. [4] Typically, the data transformation technologies generate this code [5] based on the definitions or metadata defined by the developers.
Data-driven languages frequently have a default action: if no condition matches, line-oriented languages may print the line (as in sed), or deliver a message (as in sieve). In some applications, such as filtering, matching is may be done exclusively (so only first matching statement), while in other cases all matching statements are applied.
In order to calculate the average and standard deviation from aggregate data, it is necessary to have available for each group: the total of values (Σx i = SUM(x)), the number of values (N=COUNT(x)) and the total of squares of the values (Σx i 2 =SUM(x 2)) of each groups.
In the lower plot, both the area and population data have been transformed using the logarithm function. In statistics, data transformation is the application of a deterministic mathematical function to each point in a data set—that is, each data point z i is replaced with the transformed value y i = f(z i), where f is a function.
When dealing with garbage collection schemes, it is often helpful to think of the reference graph, which is a directed graph where the vertices are objects and there is an edge from an object A to an object B if A holds a reference to B.