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Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the ...
PER Aligned: a fixed number of bits if the integer type has a finite range and the size of the range is less than 65536; a variable number of octets otherwise; OER: 1, 2, or 4 octets (either signed or unsigned) if the integer type has a finite range that fits in that number of octets; a variable number of octets otherwise
Tab-separated values (TSV) is a simple, text-based file format for storing tabular data. [3] Records are separated by newlines, and values within a record are separated by tab characters. The TSV format is thus a delimiter-separated values format, similar to comma-separated values.
A summary provides an overview of the data of a table for text and audio browsers, and does not normally display in graphical browsers. The summary (also a high Manual of Style priority for tables) is a synopsis of content, and does not repeat the caption text; think of it as analogous to an image's alt description.
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.
Hierarchical Data Format (HDF) is a set of file formats (HDF4, HDF5) designed to store and organize large amounts of data.Originally developed at the U.S. National Center for Supercomputing Applications, it is supported by The HDF Group, a non-profit corporation whose mission is to ensure continued development of HDF5 technologies and the continued accessibility of data stored in HDF.
Depending on the amount and format of the incoming data, data wrangling has traditionally been performed manually (e.g. via spreadsheets such as Excel), tools like KNIME or via scripts in languages such as Python or SQL. R, a language often used in data mining and statistical data analysis, is now also sometimes used for data wrangling. [6]
Besides differences in the schema, there are several other differences between the earlier Office XML schema formats and Office Open XML. Whereas the data in Office Open XML documents is stored in multiple parts and compressed in a ZIP file conforming to the Open Packaging Conventions, Microsoft Office XML formats are stored as plain single monolithic XML files (making them quite large ...