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Copy file name to clipboardExpand all lines: docs/migration-guides/numpy/README.md
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@@ -48,7 +48,7 @@ limitations under the License.
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| Filter an array according to a predicate function |`x[np.vectorize(predicate)(x)]`|[`filter(x, predicate)`][@stdlib/ndarray/filter]|
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| Find the index of the first element which equals a specified value |`np.argmax(x == v, axis=dim)`|[`indexOf(x, v, {dim: dim})`][@stdlib/blas/ext/index-of]|
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| Find the index of the last element which equals a specified value |`x.shape[dim]-1-np.argmax(np.flip(x, axis=dim) == v, axis=dim)`|[`lastIndexOf(x, v, {dim: dim})`][@stdlib/blas/ext/last-index-of]|
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| Flatten an array to a desired depth |`np.reshape(x, newshape)`]|[`flatten(x, {depth: depth})`][@stdlib/ndarray/flatten]|
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| Flatten an array to a desired depth |`np.reshape(x, newshape)`|[`flatten(x, {depth: depth})`][@stdlib/ndarray/flatten]|
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| Flatten an array starting from a specific dimension |`np.reshape(x, x.shape[:dim] + (-1,))`|[`flattenFrom(x, dim)`][@stdlib/ndarray/flatten-from]|
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| Prepend a specified number of singleton dimensions |`np.reshape(x, (1,)*n + x.shape)`|[`prependSingletonDimensions(x, n)`][@stdlib/ndarray/prepend-singleton-dimensions]|
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| Prepend a zero-filled array of the same shape along a specified dimension |`np.concat((np.zeros_like(x), x), axis=dim)`|[`concat([zerosLike(x), x], {dim: dim})`][@stdlib/ndarray/concat]|
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