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In statistics, ranking is the data transformation in which numerical or ordinal values are replaced by their rank when the data are sorted. For example, the ranks of the numerical data 3.4, 5.1, 2.6, 7.3 are 2, 3, 1, 4. As another example, the ordinal data hot, cold, warm would be replaced by 3, 1, 2.
Data conversions may be as simple as the conversion of a text file from one character encoding system to another; or more complex, such as the conversion of office file formats, or the conversion of image formats and audio file formats. There are many ways in which data is converted within the computer environment.
The data in the following example were intentionally designed to contradict most of the normal forms. In practice it is often possible to skip some of the normalization steps because the data is already normalized to some extent. Fixing a violation of one normal form also often fixes a violation of a higher normal form.
Both free and paid versions are available. It can handle Microsoft Excel .xls and .xlsx files, and also produce other file formats such as .et, .txt, .csv, .pdf, and .dbf. It supports multiple tabs, VBA macro and PDF converting. [10] Lotus SmartSuite Lotus 123 – for MS Windows. In its MS-DOS (character cell) version, widely considered to be ...
To further illustrate, imagine a relational model with two tables: a people table (which has a person_id and person_name column) and a friend table (with friend_id and person_id, which is a foreign key from the people table). In this case, searching for all of Jack's friends would result in the following SQL query.
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.
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For example, when looking up a personal name, it may be desirable to ignore the distinction between upper and lower case letters. For such data, one must use a hash function that is compatible with the data equivalence criterion being used: that is, any two inputs that are considered equivalent must yield the same hash value. This can be ...