NumPy

Indexing routines

See also

Indexing

Generating index arrays

c_

Translates slice objects to concatenation along the second axis.

r_

Translates slice objects to concatenation along the first axis.

s_

A nicer way to build up index tuples for arrays.

nonzero(a)

Return the indices of the elements that are non-zero.

where(condition, [x, y])

Return elements chosen from x or y depending on condition.

indices(dimensions[, dtype, sparse])

Return an array representing the indices of a grid.

ix_(\*args)

Construct an open mesh from multiple sequences.

ogrid

nd_grid instance which returns an open multi-dimensional “meshgrid”.

ravel_multi_index(multi_index, dims[, mode, …])

Converts a tuple of index arrays into an array of flat indices, applying boundary modes to the multi-index.

unravel_index(indices, shape[, order])

Converts a flat index or array of flat indices into a tuple of coordinate arrays.

diag_indices(n[, ndim])

Return the indices to access the main diagonal of an array.

diag_indices_from(arr)

Return the indices to access the main diagonal of an n-dimensional array.

mask_indices(n, mask_func[, k])

Return the indices to access (n, n) arrays, given a masking function.

tril_indices(n[, k, m])

Return the indices for the lower-triangle of an (n, m) array.

tril_indices_from(arr[, k])

Return the indices for the lower-triangle of arr.

triu_indices(n[, k, m])

Return the indices for the upper-triangle of an (n, m) array.

triu_indices_from(arr[, k])

Return the indices for the upper-triangle of arr.

Indexing-like operations

take(a, indices[, axis, out, mode])

Take elements from an array along an axis.

take_along_axis(arr, indices, axis)

Take values from the input array by matching 1d index and data slices.

choose(a, choices[, out, mode])

Construct an array from an index array and a set of arrays to choose from.

compress(condition, a[, axis, out])

Return selected slices of an array along given axis.

diag(v[, k])

Extract a diagonal or construct a diagonal array.

diagonal(a[, offset, axis1, axis2])

Return specified diagonals.

select(condlist, choicelist[, default])

Return an array drawn from elements in choicelist, depending on conditions.

lib.stride_tricks.as_strided(x[, shape, …])

Create a view into the array with the given shape and strides.

Inserting data into arrays

place(arr, mask, vals)

Change elements of an array based on conditional and input values.

put(a, ind, v[, mode])

Replaces specified elements of an array with given values.

put_along_axis(arr, indices, values, axis)

Put values into the destination array by matching 1d index and data slices.

putmask(a, mask, values)

Changes elements of an array based on conditional and input values.

fill_diagonal(a, val[, wrap])

Fill the main diagonal of the given array of any dimensionality.

Iterating over arrays

nditer(op[, flags, op_flags, op_dtypes, …])

Efficient multi-dimensional iterator object to iterate over arrays.

ndenumerate(arr)

Multidimensional index iterator.

ndindex(*shape)

An N-dimensional iterator object to index arrays.

nested_iters()

Create nditers for use in nested loops

flatiter()

Flat iterator object to iterate over arrays.

lib.Arrayterator(var[, buf_size])

Buffered iterator for big arrays.