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  2. Power Query - Wikipedia

    en.wikipedia.org/wiki/Power_Query

    Power Query was first announced in 2011 under the codename "Data Explorer" as part of Azure SQL Labs. In 2013, in order to expand on the self-service business intelligence capabilities of Microsoft Excel, the project was redesigned to be packaged as an add-in Excel and was renamed "Data Explorer Preview for Excel" [4], and was made available for Excel 2010 and Excel 2013. [5]

  3. Help:Advanced table formatting - Wikipedia

    en.wikipedia.org/wiki/Help:Advanced_table_formatting

    Solution: divide one of the tall cells so that the row gets one rowspan=1 cell (and don't mind the eventual loss of text-centering). Then kill the border between them. Don't forget to fill the cell with nothing ({}). This being the only solution that correctly preserves the cell height, matching that of the reference seven row table.

  4. Row and column vectors - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_vectors

    The transpose (indicated by T) of any row vector is a column vector, and the transpose of any column vector is a row vector: […] = [] and [] = […]. The set of all row vectors with n entries in a given field (such as the real numbers ) forms an n -dimensional vector space ; similarly, the set of all column vectors with m entries forms an m ...

  5. In-place matrix transposition - Wikipedia

    en.wikipedia.org/wiki/In-place_matrix_transposition

    For example, with N = M the number of fixed points is simply N (the diagonal of the matrix). If N − 1 and M − 1 are coprime, on the other hand, the only two fixed points are the upper-left and lower-right corners of the matrix. The number of cycles of any length k>1 is given by (Cate & Twigg, 1977):

  6. Transpose - Wikipedia

    en.wikipedia.org/wiki/Transpose

    The transpose of a matrix A, denoted by A T, [3] ⊤ A, A ⊤, , [4] [5] A′, [6] A tr, t A or A t, may be constructed by any one of the following methods: Reflect A over its main diagonal (which runs from top-left to bottom-right) to obtain A T; Write the rows of A as the columns of A T; Write the columns of A as the rows of A T

  7. Row equivalence - Wikipedia

    en.wikipedia.org/wiki/Row_equivalence

    An elementary row operation is any one of the following moves: Swap: Swap two rows of a matrix. Scale: Multiply a row of a matrix by a nonzero constant. Pivot: Add a multiple of one row of a matrix to another row. Two matrices A and B are row equivalent if it is possible to transform A into B by a sequence of elementary row operations.

  8. Data orientation - Wikipedia

    en.wikipedia.org/wiki/Data_orientation

    The two most common representations are column-oriented (columnar format) and row-oriented (row format). [ 1 ] [ 2 ] The choice of data orientation is a trade-off and an architectural decision in databases , query engines, and numerical simulations. [ 1 ]

  9. Orthogonal matrix - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_matrix

    One way to express this is = =, where Q T is the transpose of Q and I is the identity matrix. This leads to the equivalent characterization: a matrix Q is orthogonal if its transpose is equal to its inverse : Q T = Q − 1 , {\displaystyle Q^{\mathrm {T} }=Q^{-1},} where Q −1 is the inverse of Q .