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Template:Diagonal split header allows splitting the background color (see below) Template:Diagonal split header 2 produces a line with consistent thickness in very large table cells (see below) As the effect is achieved by drawing a diagonal line across the cell, the two headers are still part of the same cell and can easily overrun the line.
Template:Diagonal split header allows splitting the background color (see below) Template:Diagonal split header 2 produces a line with consistent thickness in very large table cells (see below) As the effect is achieved by drawing a diagonal line across the cell, the two headers are still part of the same cell and can easily overrun the line.
It has peeved me for a while that the diagonal line produced by this template is somewhat thicker than the table cell border, which is especially visible when the cell is large. I've come up with an alternative technique, using a SVG background-image to draw the line: Template:Diagonal split header/sandbox
1.1 Background colour and non-header cells. ... and collapsible and sortable tables. ... Toggle the table of contents. Template: Diagonal split header 2/doc. Add ...
Toggle the table of contents. Template: Diagonal split color box/doc. Add languages ...
1 Diagonal split color box. 1 comment. 2 Lint errors. 2 comments. 3 Unexpected features. 1 comment. Toggle the table of contents. Template talk: Diagonal split color ...
Cut cells into parts: Instead of trying to make a super-cell that spans rows/columns, split it into smaller cells while leaving some cells intentionally empty. Use a non-breaking space with or {} in empty cells to maintain the table structure. Custom CSS styling: Override the wikitable class defaults by explicitly specifying:
Diagonalization is the process of re-ordering the rows and columns of tables and charts so that the data forms an approximately diagonal line. [1] This makes it easier for people to see patterns in the data. Columns and rows are moved around until a diagonal pattern appears, thereby making it easy to see patterns in the data.