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  2. Array slicing - Wikipedia

    en.wikipedia.org/wiki/Array_slicing

    A[-1, *] % The last row of A A[[1:5], [2:7]] % 2d array using rows 1-5 and columns 2-7 A[[5:1:-1], [2:7]] % Same as above except the rows are reversed Array indices can also be arrays of integers. For example, suppose that I = [0:9] is an array of 10 integers.

  3. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy addresses the slowness problem partly by providing multidimensional arrays and functions and operators that operate efficiently on arrays; using these requires rewriting some code, mostly inner loops, using NumPy. Using NumPy in Python gives functionality comparable to MATLAB since they are both interpreted, [18] and they both allow the ...

  4. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.

  5. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    To use column-major order in a row-major environment, or vice versa, for whatever reason, one workaround is to assign non-conventional roles to the indexes (using the first index for the column and the second index for the row), and another is to bypass language syntax by explicitly computing positions in a one-dimensional array.

  6. Knuth's Algorithm X - Wikipedia

    en.wikipedia.org/wiki/Knuth's_Algorithm_X

    Choose a row r such that A r, c = 1 (nondeterministically). Include row r in the partial solution. For each column j such that A r, j = 1, for each row i such that A i, j = 1, delete row i from matrix A. delete column j from matrix A. Repeat this algorithm recursively on the reduced matrix A.

  7. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    In Python NumPy arrays implement the flatten method, [note 1] while in R the desired effect can be achieved via the c() or as.vector() functions or, more efficiently, by removing the dimensions attribute of a matrix A with dim(A) <- NULL.

  8. Centering matrix - Wikipedia

    en.wikipedia.org/wiki/Centering_matrix

    It can be used not only to remove the mean of a single vector, but also of multiple vectors stored in the rows or columns of an m-by-n matrix . The left multiplication by C m {\displaystyle C_{m}} subtracts a corresponding mean value from each of the n columns, so that each column of the product C m X {\displaystyle C_{m}\,X} has a zero mean.

  9. Sparse matrix - Wikipedia

    en.wikipedia.org/wiki/Sparse_matrix

    For example, CSC is (val, row_ind, col_ptr), where val is an array of the (top-to-bottom, then left-to-right) non-zero values of the matrix; row_ind is the row indices corresponding to the values; and, col_ptr is the list of val indexes where each column starts. The name is based on the fact that column index information is compressed relative ...