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The flattening transformation is an algorithm that transforms nested data parallelism into flat data parallelism. It was pioneered by Guy Blelloch as part of the NESL programming language. [ 1 ] The flattening transformation is also sometimes called vectorization , but is completely unrelated to automatic vectorization .
Matplotlib-animation [11] capabilities are intended for visualizing how certain data changes. However, one can use the functionality in any way required. These animations are defined as a function of frame number (or time). In other words, one defines a function that takes a frame number as input and defines/updates the matplotlib-figure based ...
This makes accessing data in these formats much faster than data in formats requiring more extensive processing, such as JSON, CSV, and in many cases Protocol Buffers. Compared to other serialization formats however, the handling of FlatBuffers requires usually more code, and some operations are not possible (like some mutation operations).
Flattening is a measure of the compression of a circle or sphere along a diameter to form an ellipse or an ellipsoid of revolution respectively. Other terms used are ellipticity , or oblateness . The usual notation for flattening is f {\displaystyle f} and its definition in terms of the semi-axes a {\displaystyle a} and b {\displaystyle b} of ...
Google Sheets is a spreadsheet application and part of the free, web-based Google Docs Editors suite offered by Google. Google Sheets is available as a web application; a mobile app for: Android, iOS, and as a desktop application on Google's ChromeOS. The app is compatible with Microsoft Excel file formats. [5]
Google Dataset Search is a search engine from Google that helps researchers locate online data that is freely available for use. [1] The company launched the service on September 5, 2018, and stated that the product was targeted at scientists and data journalists. The service was out of beta as of January 23, 2020. [2]
Plain text files usually contain one record per line. [2]Examples of flat files include /etc/passwd and /etc/group on Unix-like operating systems. Another example of a flat file is a name-and-address list with the fields Name, Address and Phone Number.
The average of these values is 18.05 and the excess kurtosis is thus 18.05 − 3 = 15.05. This example makes it clear that data near the "middle" or "peak" of the distribution do not contribute to the kurtosis statistic, hence kurtosis does not measure "peakedness". It is simply a measure of the outlier, 999 in this example.