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new 3c5825b30d GH-49278: [Python][Doc] Add from_numpy examples for sparse
tensor constructors (#49279)
3c5825b30d is described below
commit 3c5825b30dbb5a897a903034c12ce6ece664c560
Author: ChiLin Chiu <[email protected]>
AuthorDate: Thu Mar 12 21:01:39 2026 +0800
GH-49278: [Python][Doc] Add from_numpy examples for sparse tensor
constructors (#49279)
### Rationale for this change
Follow-up from #49147 (comment:
https://github.com/apache/arrow/pull/49147#issuecomment-3879302706).
### What changes are included in this PR?
Add `from_numpy` docstring examples.
### Are these changes tested?
Yes.
### Are there any user-facing changes?
No.
* GitHub Issue: #49278
Authored-by: ChiLin Chiu <[email protected]>
Signed-off-by: AlenkaF <[email protected]>
---
python/pyarrow/tensor.pxi | 61 +++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 61 insertions(+)
diff --git a/python/pyarrow/tensor.pxi b/python/pyarrow/tensor.pxi
index 4edbb41339..edb136b410 100644
--- a/python/pyarrow/tensor.pxi
+++ b/python/pyarrow/tensor.pxi
@@ -411,6 +411,18 @@ shape: {self.shape}"""
Shape of the tensor.
dim_names : list, optional
Names of the dimensions.
+
+ Examples
+ --------
+ >>> import pyarrow as pa
+ >>> import numpy as np
+ >>> data = np.array([1.0, 2.0, 3.0], dtype=np.float32)
+ >>> coords = np.array([[0, 1], [1, 0], [1, 2]], dtype=np.int64)
+ >>> sparse_coo = pa.SparseCOOTensor.from_numpy(data, coords, shape=(2,
3))
+ >>> sparse_coo
+ <pyarrow.SparseCOOTensor>
+ type: float
+ shape: (2, 3)
"""
cdef shared_ptr[CSparseCOOTensor] csparse_tensor
cdef vector[int64_t] c_shape
@@ -735,6 +747,20 @@ shape: {self.shape}"""
Shape of the matrix.
dim_names : list, optional
Names of the dimensions.
+
+ Examples
+ --------
+ >>> import pyarrow as pa
+ >>> import numpy as np
+ >>> data = np.array([1.0, 2.0, 3.0], dtype=np.float64)
+ >>> indptr = np.array([0, 2, 3], dtype=np.int64)
+ >>> indices = np.array([0, 2, 1], dtype=np.int64)
+ >>> sparse_csr = pa.SparseCSRMatrix.from_numpy(
+ ... data, indptr, indices, shape=(2, 3))
+ >>> sparse_csr
+ <pyarrow.SparseCSRMatrix>
+ type: double
+ shape: (2, 3)
"""
cdef shared_ptr[CSparseCSRMatrix] csparse_tensor
cdef vector[int64_t] c_shape
@@ -992,6 +1018,20 @@ shape: {self.shape}"""
Shape of the matrix.
dim_names : list, optional
Names of the dimensions.
+
+ Examples
+ --------
+ >>> import pyarrow as pa
+ >>> import numpy as np
+ >>> data = np.array([1.0, 3.0, 2.0], dtype=np.float64)
+ >>> indptr = np.array([0, 1, 2, 3], dtype=np.int64)
+ >>> indices = np.array([0, 1, 0], dtype=np.int64)
+ >>> sparse_csc = pa.SparseCSCMatrix.from_numpy(
+ ... data, indptr, indices, shape=(2, 3))
+ >>> sparse_csc
+ <pyarrow.SparseCSCMatrix>
+ type: double
+ shape: (2, 3)
"""
cdef shared_ptr[CSparseCSCMatrix] csparse_tensor
cdef vector[int64_t] c_shape
@@ -1265,6 +1305,27 @@ shape: {self.shape}"""
produce the prefix tree.
dim_names : list, optional
Names of the dimensions.
+
+ Examples
+ --------
+ >>> import pyarrow as pa
+ >>> import numpy as np
+ >>> data = np.array([1.0, 2.0], dtype=np.float32)
+ >>> indptr = [
+ ... np.array([0, 1, 2], dtype=np.int64),
+ ... np.array([0, 1, 2], dtype=np.int64),
+ ... ]
+ >>> indices = [
+ ... np.array([0, 1], dtype=np.int64),
+ ... np.array([1, 2], dtype=np.int64),
+ ... np.array([0, 1], dtype=np.int64),
+ ... ]
+ >>> sparse_csf = pa.SparseCSFTensor.from_numpy(
+ ... data, indptr, indices, shape=(2, 3, 2))
+ >>> sparse_csf
+ <pyarrow.SparseCSFTensor>
+ type: float
+ shape: (2, 3, 2)
"""
cdef shared_ptr[CSparseCSFTensor] csparse_tensor
cdef vector[int64_t] c_axis_order
