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dplyr is an R package whose set of functions are designed to enable dataframe (a spreadsheet-like data structure) manipulation in an intuitive, user-friendly way. It is one of the core packages of the popular tidyverse set of packages in the R programming language . [ 1 ]
[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.
Yet another example of grouping the data is the use of some commonly used numerical values, which are in fact "names" we assign to the categories. For example, let us look at the age distribution of the students in a class. The students may be 10 years old, 11 years old or 12 years old. These are the age groups, 10, 11, and 12.
R is a programming language for statistical computing and data visualization.It has been adopted in the fields of data mining, bioinformatics and data analysis. [9]The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.
In fact, 2-groups are classified in this way: given a group π 1, an abelian group π 2, a group action of π 1 on π 2, and an element of H 3 (π 1, π 2), there is a unique (up to equivalence) 2-group G with π 1 G isomorphic to π 1, π 2 G isomorphic to π 2, and the other data corresponding.
For instance, a typical dose-ranging study may include four groups: a placebo group, low-dose group, medium-dose group and a high-dose group. The maximum tolerable dose (MTD) information is necessary to be able to design such groups and therefore dose-ranging studies are usually designed after the availability of MTD information.