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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 table to wide table is generally referred to as "pivoting" in the context of data transformations.
For example, a table of 128 rows with a Boolean column requires 128 bytes a row-oriented format (one byte per Boolean) but 128 bits (16 bytes) in a column-oriented format (via a bitmap). Another example is the use of run-length encoding to encode a column.
The size of assembly B is 305 kbp, the N50 contig length drops to 50 kbp because 80 + 70 + 50 is greater than 50% of 305, and the L50 contig count is 3 contigs. This example illustrates that one can sometimes increase the N50 length simply by removing some of the shortest contigs or scaffolds from an assembly.
(HTTP represents length of payload with a Content-Length header and separates headers from the payload with an empty line and headers from each other with a new line.) ASN.1 specifies several TLV-based encoding rules (BER, DER), as well as non-TLV based ones (PER, XER). CSN.1 describes encoding rules using non-TLV semantics. More recently, [when?
The cross-section of the column is uniform throughout its length. The direct stress is very small as compared to the bending stress (the material is compressed only within the elastic range of strains). The length of the column is very large as compared to the cross-sectional dimensions of the column. The column fails only by buckling.
Asymmetric numeral systems (ANS) [1] [2] is a family of entropy encoding methods introduced by Jarosław (Jarek) Duda [3] from Jagiellonian University, used in data compression since 2014 [4] due to improved performance compared to previous methods. [5]
The slenderness ratio is an indicator of the specimen's resistance to bending and buckling, due to its length and cross section. If the slenderness ratio is less than the critical slenderness ratio, the column is considered to be a short column. In these cases, the Johnson parabola is more applicable than the Euler formula. [5]
The FAST4 format was invented as a derivative of the FASTQ format where each of the 4 bases (A,C,G,T) had separate probabilities stored. It was part of the Swift basecaller, an open source package for primary data analysis on next-gen sequence data "from images to basecalls". The FAST5 format was invented as an extension of the FAST4 format.