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Formats that use delimiter-separated values (also DSV) [2]: 113 store two-dimensional arrays of data by separating the values in each row with specific delimiter characters. Most database and spreadsheet programs are able to read or save data in a delimited format.
mw-collapsible also does not require a header row in the table, as collapsible did. Tables will show the "[hide]" / "[show]" controls in the first row of the table (whether or not it is a header row), unless a table caption is present.(see § Tables with captions) Example with a header row
One method of hiding rows in tables (or other structures within tables) uses HTML directly. [1] HTML is more complicated than MediaWiki table syntax, but not much more so. In general, there are only a handful of HTML tags you need to be aware of
the basic code for a table row; code for color, alignment, and sorting mode; fixed texts such as units; special formats for sorting; In such a case, it can be useful to create a template that produces the syntax for a table row, with the data as parameters. This can have many advantages: easily changing the order of columns, or removing a column
A stylistic depiction of values inside of a so-named comma-separated values (CSV) text file. The commas (shown in red) are used as field delimiters. A delimiter is a sequence of one or more characters for specifying the boundary between separate, independent regions in plain text, mathematical expressions or other data streams.
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 ...
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[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.