diff --git a/.github/workflows/check_stub_files_diff.yaml b/.github/workflows/check_stub_files_diff.yaml
index 8fe3a5e38..36ad91b2b 100644
--- a/.github/workflows/check_stub_files_diff.yaml
+++ b/.github/workflows/check_stub_files_diff.yaml
@@ -17,7 +17,7 @@ jobs:
       - uses: actions/checkout@v6
       - uses: prefix-dev/setup-pixi@v0.9.6
         with:
-          pixi-version: v0.59.0
+          pixi-version: v0.68.0
           frozen: true
 
       - name: Check stub file for `_data_ops.py` is up-to-date
diff --git a/.github/workflows/run-code-format-checks.yaml b/.github/workflows/run-code-format-checks.yaml
index a02eb44ea..01f5f1dbc 100644
--- a/.github/workflows/run-code-format-checks.yaml
+++ b/.github/workflows/run-code-format-checks.yaml
@@ -17,7 +17,7 @@ jobs:
       - uses: actions/checkout@v6
       - uses: prefix-dev/setup-pixi@v0.9.6
         with:
-          pixi-version: v0.59.0
+          pixi-version: v0.68.0
           frozen: true
 
       - name: Run tests
diff --git a/.github/workflows/test-javascript.yml b/.github/workflows/test-javascript.yml
index 1040b3c01..ea83bf264 100644
--- a/.github/workflows/test-javascript.yml
+++ b/.github/workflows/test-javascript.yml
@@ -15,7 +15,7 @@ jobs:
       - uses: actions/checkout@v6
       - uses: prefix-dev/setup-pixi@v0.9.6
         with:
-          pixi-version: v0.59.0
+          pixi-version: v0.68.0
           environments: ci-py314-latest-optional-deps
           # we can freeze the environment and manually bump the dependencies to the
           # latest version time to time.
diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
index ef92e6fcd..acff2e332 100644
--- a/.github/workflows/testing.yml
+++ b/.github/workflows/testing.yml
@@ -27,7 +27,7 @@ jobs:
       - uses: actions/checkout@v6
       - uses: prefix-dev/setup-pixi@v0.9.6
         with:
-          pixi-version: v0.59.0
+          pixi-version: v0.68.0
           environments: ${{ matrix.environment }}
           # we can freeze the environment and manually bump the dependencies to the
           # latest version time to time.
@@ -63,7 +63,7 @@ jobs:
       - uses: actions/checkout@v6
       - uses: prefix-dev/setup-pixi@v0.9.6
         with:
-          pixi-version: v0.59.0
+          pixi-version: v0.68.0
           environments: ci-nightly-deps
           # we can freeze the environment and manually bump the dependencies to the
           # latest version time to time.
diff --git a/.github/workflows/update_pixi_lock_files.yml b/.github/workflows/update_pixi_lock_files.yml
index 6d936b2de..4d8af05d8 100644
--- a/.github/workflows/update_pixi_lock_files.yml
+++ b/.github/workflows/update_pixi_lock_files.yml
@@ -24,7 +24,7 @@ jobs:
       - uses: actions/checkout@v6
       - uses: prefix-dev/setup-pixi@v0.9.6
         with:
-          pixi-version: v0.59.0
+          pixi-version: v0.68.0
           run-install: false
 
       - name: Remove the current lock file
diff --git a/doc/conf.py b/doc/conf.py
index 5194c86cc..aa18871ad 100644
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -70,6 +70,7 @@
     "sphinx.ext.linkcode",
     "sphinx.ext.autodoc.typehints",
     # contrib
+    "sphinx_design",
     "numpydoc",
     "sphinx_issues",
     "sphinx_copybutton",
diff --git a/doc/data_ops.rst b/doc/data_ops.rst
index b8c56794d..31c832f54 100644
--- a/doc/data_ops.rst
+++ b/doc/data_ops.rst
@@ -1,36 +1,60 @@
 .. _user_guide_data_ops_index:
 
-Complex multi-table pipelines with Data Ops
-===========================================
-
-Skrub provides an easy way to build complex, flexible machine learning pipelines.
-There are several needs that are not easily addressed with standard scikit-learn
-tools such as :class:`~sklearn.pipeline.Pipeline` and
-:class:`~sklearn.compose.ColumnTransformer`, and for which the skrub DataOps offer
-a solution:
-
-- Multiple tables: We often have several tables of different shapes (for
-  example, "Customers", "Orders", and "Products" tables) that need to be
-  processed and assembled into a design matrix ``X``. The target ``y`` may also
-  be the result of some data processing. Standard scikit-learn estimators do not
-  support this, as they expect right away a single design matrix ``X`` and a
-  target array ``y``, with one row per observation.
-- DataFrame wrangling: Performing typical DataFrame operations such as
-  projections, joins, and aggregations should be possible and allow leveraging
-  the powerful and familiar APIs of `Pandas <https://pandas.pydata.org>`_ or
-  `Polars <https://docs.pola.rs/>`_.
-- Hyperparameter tuning: Choices of estimators, hyperparameters, and even
-  the pipeline architecture can be guided by validation scores. Specifying
-  ranges of possible values outside of the pipeline itself (as in
-  :class:`~sklearn.model_selection.GridSearchCV`) is difficult in complex
-  pipelines.
-- Iterative development: Building a pipeline step by step while inspecting
-  intermediate results allows for a short feedback loop and early discovery of
-  errors.
-
-In this section we cover all about the skrub Data Ops, from starting out with a
-simple example, to more advanced concepts like parameter tuning and and pipeline
-validation.
+.. currentmodule:: skrub
+
+Building complete pipelines with DataOps
+========================================
+
+A skrub DataOp is a complete machine learning pipeline —from data loading and
+wrangling to the final prediction— in a single object that can be fitted, tuned,
+cross-validated, and saved in a file like any scikit-learn estimator.
+
+By integrating the whole data processing, DataOps help to validate pipelines
+while **avoiding data leakage**, to **tune complex modelling choices**, and to keep
+track of important **fitted (learned) state**.
+
+To solve a machine-learning task we often need to combine multiple operations
+such as loading and filtering data, joining tables and computing aggregations,
+extracting numerical features, and fitting a classifier or regressor.
+
+**Storing state**  Each of those operations may need to be fitted: to learn some
+information from training data and reuse it to apply consistent transformations
+to new data. This is the case for transformers like the
+:class:`~sklearn.preprocessing.StandardScaler` and :class:`TableVectorizer` and
+estimators like :class:`~sklearn.ensemble.RandomForestClassifier`.
+
+**Tuning**  Moreover, each processing step may involve decisions that need to be
+tuned (*tuning* means finding the value that gives the best predictive
+performance), for example: what weather forecast features should I include to
+predict the load on an electric grid? How should I encode a product description
+to help predict the product's category? What learning rate to set on a
+:class:`~sklearn.ensemble.HistGradientBoostingRegressor`?
+
+**Validation**  Finally, the quality of predictions must be evaluated on
+held-out data (with a train/test split or cross-validation), taking care to
+**avoid leakage** of test data into the training set.
+
+Separating the data wrangling from the fitted estimator prevents correctly
+handling the tasks above. Skrub DataOps help by binding an arbitrary set of
+transformations of any number of inputs in a single estimator. These
+transformations can be easily parametrized with tunable choices. The resulting
+objects have built-in methods for cross-validation and tuning with either Optuna
+or scikit-learn, and for inspecting runs and intermediate results. Once fitted,
+they can be saved in a file, loaded, applied to new data as easily as a single
+:class:`~sklearn.linear_model.LogisticRegression`.
+
+.. dropdown:: Going beyond the scikit-learn Pipeline
+  :color: primary
+
+  To some extent, the DataOps exist for the same reasons as the simpler
+  scikit-learn :class:`sklearn.pipeline.Pipeline` used in other parts of this
+  documentation. However the Pipeline is too limited for many real-world problems:
+  it can only represent a linear sequence of scikit-learn transformers, the design
+  matrix and target variables must be constructed and divided into training and
+  testing sets outside of the pipeline and the number of rows cannot change, only
+  a single table can be handled, hyperparameter choices are difficult to define,
+  etc. . Skrub DataOps remove those limitations and add several useful features
+  such as interactive previews and integration with Optuna.
 
 Data Ops basic concepts
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
diff --git a/pixi.lock b/pixi.lock
index ec4e86ab1..efd60a25b 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -1,4 +1,9 @@
-version: 6
+version: 7
+platforms:
+- name: linux-64
+- name: osx-64
+- name: osx-arm64
+- name: win-64
 environments:
   check-pyi-diff:
     channels:
@@ -9,34 +14,21 @@ environments:
     packages:
       linux-64:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/adwaita-icon-theme-49.0-unix_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.16-hb03c661_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.16.1-hb03c661_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/at-spi2-atk-2.38.0-h0630a04_3.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/linux-64/at-spi2-core-2.40.3-h0630a04_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/linux-64/atk-1.0-2.38.0-h04ea711_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/backports.zstd-1.6.0-py314h680f03e_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-1.2.0-hed03a55_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.2.0-hb03c661_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.2.0-py314h3de4e8d_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.5.20-hbd8a1cb_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cairo-1.18.4-he90730b_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2026.5.20-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.4.7-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.3.3-py314h97ea11e_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhcf101f3_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cyrus-sasl-2.1.28-hac629b4_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/dbus-1.16.2-h24cb091_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/double-conversion-3.4.0-hecca717_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/epoxy-1.5.10-hb03c661_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-h77eed37_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/fontconfig-2.18.1-h27c8c51_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-hc364b38_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/fonttools-4.63.0-pyh7db6752_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/freetype-2.14.3-ha770c72_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.16-hb03c661_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/gdk-pixbuf-2.44.6-h2b0a6b4_0.conda
@@ -45,15 +37,9 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/graphviz-14.1.2-h8b86629_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/gtk3-3.24.52-ha5ea40c_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/gts-0.7.6-h977cf35_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/h2-4.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/harfbuzz-14.2.1-h6083320_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/hicolor-icon-theme-0.17-ha770c72_3.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/hpack-4.1.0-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.1.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/idna-3.17-pyhcf101f3_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhcf101f3_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/joblib-1.5.3-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.5.0-py314h97ea11e_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/krb5-1.22.2-ha1258a1_0.conda
@@ -118,41 +104,27 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/markupsafe-3.0.3-py314h67df5f8_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/matplotlib-3.10.9-py314hdafbbf9_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.10.9-py314h1194b4b_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/munkres-1.1.4-pyhd8ed1ab_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/narwhals-2.22.1-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.6-hdb14827_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/numpy-2.4.6-py314h2b28147_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/openjpeg-2.5.4-h55fea9a_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/openldap-2.6.13-hbde042b_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.3-h35e630c_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-3.0.3-py314hb4ffadd_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pango-1.56.4-hda50119_1.conda
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       - conda: https://conda.anaconda.org/conda-forge/linux-64/pixman-0.46.4-h54a6638_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-hb9d3cd8_1002.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/pydot-4.0.1-pyhcf101f3_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/pyparsing-3.3.2-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pyside6-6.11.1-py314h3987850_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha55dd90_7.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.6-habeac84_100_cp314.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.9.0.post0-pyhe01879c_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/qhull-2020.2-h434a139_5.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/qt6-main-6.11.1-pl5321h16c4a6b_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/requests-2.34.2-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.9.0-np2py314hf09ca88_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/scipy-1.17.1-py314hf07bd8e_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-82.0.1-pyh332efcf_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/six-1.17.0-pyhe01879c_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.6.0-pyhecae5ae_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/tornado-6.5.7-py314h5bd0f2a_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/unicodedata2-17.0.1-py314h5bd0f2a_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/urllib3-2.7.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/wayland-1.25.0-hd6090a7_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xcb-util-0.4.1-h4f16b4b_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xcb-util-cursor-0.1.6-hb03c661_0.conda
@@ -180,31 +152,84 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-xorgproto-2025.1-hb03c661_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/zlib-ng-2.3.3-hceb46e0_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda
-      - pypi: ./
+      - conda: https://conda.anaconda.org/conda-forge/noarch/adwaita-icon-theme-49.0-unix_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/backports.zstd-1.6.0-py314h680f03e_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.5.20-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2026.5.20-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.4.7-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhcf101f3_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-h77eed37_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-hc364b38_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/fonttools-4.63.0-pyh7db6752_0.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-http-0.9.2-hefd7a92_4.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-64/aws-c-http-0.11.0-he315c99_2.conda
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-  license: Apache-2.0
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-- conda: https://conda.anaconda.org/conda-forge/osx-64/aws-c-http-0.9.2-h5492b4a_4.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/aws-c-http-0.10.12-h95cdebe_2.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/aws-c-http-0.11.0-h0a63974_2.conda
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-- conda: https://conda.anaconda.org/conda-forge/win-64/aws-c-http-0.11.0-h4721ae0_2.conda
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-- conda: https://conda.anaconda.org/conda-forge/win-64/aws-c-http-0.9.2-h3888f84_4.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.15.3-h173a860_6.conda
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-  license: Apache-2.0
-  license_family: APACHE
+  - mkl >=2026.0.0,<2027.0a0
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+  - liblapacke 3.11.0   8*_mkl
+  - liblapack  3.11.0   8*_mkl
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+  - blas_mkl_2
+  license: BSD-3-Clause
+  license_family: BSD
   purls: []
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-  - aws-c-http >=0.11.0,<0.11.1.0a0
-  license: Apache-2.0
-  license_family: APACHE
+  - libopenblas >=0.3.25,<0.3.26.0a0
+  - libopenblas >=0.3.25,<1.0a0
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+  - libcblas 3.9.0 20_linux64_openblas
+  - blas * openblas
+  - liblapack 3.9.0 20_linux64_openblas
+  - mkl <2025
+  license: BSD-3-Clause
+  license_family: BSD
   purls: []
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-  - aws-checksums >=0.2.2,<0.2.3.0a0
-  license: Apache-2.0
-  license_family: Apache
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+  - libgcc >=14
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   purls: []
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-  license: Apache-2.0
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-  license: Apache-2.0
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+  - __glibc >=2.17,<3.0.a0
+  - libbrotlicommon 1.1.0 hb03c661_4
+  - libgcc >=14
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+  license_family: MIT
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-  license: Apache-2.0
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+  - liblapack  3.11.0   8*_openblas
+  license: BSD-3-Clause
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+  constrains:
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+  - liblapacke 3.11.0   8*_mkl
+  - liblapack  3.11.0   8*_mkl
+  track_features:
+  - blas_mkl
+  license: BSD-3-Clause
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-  license: Apache-2.0
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+  - libgcc >=14
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+  - libstdcxx >=14
+  license: Apache-2.0 WITH LLVM-exception
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   license: Apache-2.0
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-  - numba>=0.60.0 ; extra == 'all'
-  - numexpr>=2.10.2 ; extra == 'all'
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-  - openpyxl>=3.1.5 ; extra == 'all'
-  - psycopg2>=2.9.10 ; extra == 'all'
-  - pyarrow>=13.0.0 ; extra == 'all'
-  - pyiceberg>=0.8.1 ; extra == 'all'
-  - pymysql>=1.1.1 ; extra == 'all'
-  - pyqt5>=5.15.9 ; extra == 'all'
-  - pyreadstat>=1.2.8 ; extra == 'all'
-  - pytest>=8.3.4 ; extra == 'all'
-  - pytest-xdist>=3.6.1 ; extra == 'all'
-  - python-calamine>=0.3.0 ; extra == 'all'
-  - pytz>=2020.1 ; extra == 'all'
-  - pyxlsb>=1.0.10 ; extra == 'all'
-  - qtpy>=2.4.2 ; extra == 'all'
-  - scipy>=1.14.1 ; extra == 'all'
-  - s3fs>=2024.10.0 ; extra == 'all'
-  - sqlalchemy>=2.0.36 ; extra == 'all'
-  - tables>=3.10.1 ; extra == 'all'
-  - tabulate>=0.9.0 ; extra == 'all'
-  - xarray>=2024.10.0 ; extra == 'all'
-  - xlrd>=2.0.1 ; extra == 'all'
-  - xlsxwriter>=3.2.0 ; extra == 'all'
-  - zstandard>=0.23.0 ; extra == 'all'
-  requires_python: '>=3.11'
-- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/pandas/3.1.0.dev0+1043.gaee9241b41/pandas-3.1.0.dev0+1043.gaee9241b41-cp314-cp314-macosx_11_0_arm64.whl
-  name: pandas
-  version: 3.1.0.dev0+1043.gaee9241b41
-  requires_dist:
-  - numpy>=1.26.0 ; python_full_version < '3.14'
-  - numpy>=2.3.3 ; python_full_version >= '3.14'
-  - python-dateutil>=2.8.2
-  - tzdata ; sys_platform == 'win32'
-  - tzdata ; sys_platform == 'emscripten'
-  - hypothesis>=6.116.0 ; extra == 'test'
-  - pytest>=8.3.4 ; extra == 'test'
-  - pytest-xdist>=3.6.1 ; extra == 'test'
-  - pyarrow>=13.0.0 ; extra == 'pyarrow'
-  - bottleneck>=1.4.2 ; extra == 'performance'
-  - numba>=0.60.0 ; extra == 'performance'
-  - numexpr>=2.10.2 ; extra == 'performance'
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-  - xarray>=2024.10.0 ; extra == 'computation'
-  - fsspec>=2024.10.0 ; extra == 'fss'
-  - s3fs>=2024.10.0 ; extra == 'aws'
-  - gcsfs>=2024.10.0 ; extra == 'gcp'
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-  - openpyxl>=3.1.5 ; extra == 'excel'
-  - python-calamine>=0.3.0 ; extra == 'excel'
-  - pyxlsb>=1.0.10 ; extra == 'excel'
-  - xlrd>=2.0.1 ; extra == 'excel'
-  - xlsxwriter>=3.2.0 ; extra == 'excel'
-  - pyarrow>=13.0.0 ; extra == 'parquet'
-  - pyarrow>=13.0.0 ; extra == 'feather'
-  - pyiceberg>=0.8.1 ; extra == 'iceberg'
-  - tables>=3.10.1 ; extra == 'hdf5'
-  - pyreadstat>=1.2.8 ; extra == 'spss'
-  - sqlalchemy>=2.0.36 ; extra == 'postgresql'
-  - psycopg2>=2.9.10 ; extra == 'postgresql'
-  - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql'
-  - sqlalchemy>=2.0.36 ; extra == 'mysql'
-  - pymysql>=1.1.1 ; extra == 'mysql'
-  - sqlalchemy>=2.0.36 ; extra == 'sql-other'
-  - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other'
-  - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other'
-  - beautifulsoup4>=4.12.3 ; extra == 'html'
-  - html5lib>=1.1 ; extra == 'html'
-  - lxml>=5.3.0 ; extra == 'html'
-  - lxml>=5.3.0 ; extra == 'xml'
-  - matplotlib>=3.9.3 ; extra == 'plot'
-  - jinja2>=3.1.5 ; extra == 'output-formatting'
-  - tabulate>=0.9.0 ; extra == 'output-formatting'
-  - pyqt5>=5.15.9 ; extra == 'clipboard'
-  - qtpy>=2.4.2 ; extra == 'clipboard'
-  - zstandard>=0.23.0 ; extra == 'compression'
-  - pytz>=2020.1 ; extra == 'timezone'
-  - adbc-driver-postgresql>=1.2.0 ; extra == 'all'
-  - adbc-driver-sqlite>=1.2.0 ; extra == 'all'
-  - beautifulsoup4>=4.12.3 ; extra == 'all'
-  - bottleneck>=1.4.2 ; extra == 'all'
-  - fastparquet>=2024.11.0 ; extra == 'all'
-  - fsspec>=2024.10.0 ; extra == 'all'
-  - gcsfs>=2024.10.0 ; extra == 'all'
-  - html5lib>=1.1 ; extra == 'all'
-  - hypothesis>=6.116.0 ; extra == 'all'
-  - jinja2>=3.1.5 ; extra == 'all'
-  - lxml>=5.3.0 ; extra == 'all'
-  - matplotlib>=3.9.3 ; extra == 'all'
-  - numba>=0.60.0 ; extra == 'all'
-  - numexpr>=2.10.2 ; extra == 'all'
-  - odfpy>=1.4.1 ; extra == 'all'
-  - openpyxl>=3.1.5 ; extra == 'all'
-  - psycopg2>=2.9.10 ; extra == 'all'
-  - pyarrow>=13.0.0 ; extra == 'all'
-  - pyiceberg>=0.8.1 ; extra == 'all'
-  - pymysql>=1.1.1 ; extra == 'all'
-  - pyqt5>=5.15.9 ; extra == 'all'
-  - pyreadstat>=1.2.8 ; extra == 'all'
-  - pytest>=8.3.4 ; extra == 'all'
-  - pytest-xdist>=3.6.1 ; extra == 'all'
-  - python-calamine>=0.3.0 ; extra == 'all'
-  - pytz>=2020.1 ; extra == 'all'
-  - pyxlsb>=1.0.10 ; extra == 'all'
-  - qtpy>=2.4.2 ; extra == 'all'
-  - scipy>=1.14.1 ; extra == 'all'
-  - s3fs>=2024.10.0 ; extra == 'all'
-  - sqlalchemy>=2.0.36 ; extra == 'all'
-  - tables>=3.10.1 ; extra == 'all'
-  - tabulate>=0.9.0 ; extra == 'all'
-  - xarray>=2024.10.0 ; extra == 'all'
-  - xlrd>=2.0.1 ; extra == 'all'
-  - xlsxwriter>=3.2.0 ; extra == 'all'
-  - zstandard>=0.23.0 ; extra == 'all'
-  requires_python: '>=3.11'
-- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/pandas/3.1.0.dev0+1043.gaee9241b41/pandas-3.1.0.dev0+1043.gaee9241b41-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
-  name: pandas
-  version: 3.1.0.dev0+1043.gaee9241b41
-  requires_dist:
-  - numpy>=1.26.0 ; python_full_version < '3.14'
-  - numpy>=2.3.3 ; python_full_version >= '3.14'
-  - python-dateutil>=2.8.2
-  - tzdata ; sys_platform == 'win32'
-  - tzdata ; sys_platform == 'emscripten'
-  - hypothesis>=6.116.0 ; extra == 'test'
-  - pytest>=8.3.4 ; extra == 'test'
-  - pytest-xdist>=3.6.1 ; extra == 'test'
-  - pyarrow>=13.0.0 ; extra == 'pyarrow'
-  - bottleneck>=1.4.2 ; extra == 'performance'
-  - numba>=0.60.0 ; extra == 'performance'
-  - numexpr>=2.10.2 ; extra == 'performance'
-  - scipy>=1.14.1 ; extra == 'computation'
-  - xarray>=2024.10.0 ; extra == 'computation'
-  - fsspec>=2024.10.0 ; extra == 'fss'
-  - s3fs>=2024.10.0 ; extra == 'aws'
-  - gcsfs>=2024.10.0 ; extra == 'gcp'
-  - odfpy>=1.4.1 ; extra == 'excel'
-  - openpyxl>=3.1.5 ; extra == 'excel'
-  - python-calamine>=0.3.0 ; extra == 'excel'
-  - pyxlsb>=1.0.10 ; extra == 'excel'
-  - xlrd>=2.0.1 ; extra == 'excel'
-  - xlsxwriter>=3.2.0 ; extra == 'excel'
-  - pyarrow>=13.0.0 ; extra == 'parquet'
-  - pyarrow>=13.0.0 ; extra == 'feather'
-  - pyiceberg>=0.8.1 ; extra == 'iceberg'
-  - tables>=3.10.1 ; extra == 'hdf5'
-  - pyreadstat>=1.2.8 ; extra == 'spss'
-  - sqlalchemy>=2.0.36 ; extra == 'postgresql'
-  - psycopg2>=2.9.10 ; extra == 'postgresql'
-  - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql'
-  - sqlalchemy>=2.0.36 ; extra == 'mysql'
-  - pymysql>=1.1.1 ; extra == 'mysql'
-  - sqlalchemy>=2.0.36 ; extra == 'sql-other'
-  - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other'
-  - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other'
-  - beautifulsoup4>=4.12.3 ; extra == 'html'
-  - html5lib>=1.1 ; extra == 'html'
-  - lxml>=5.3.0 ; extra == 'html'
-  - lxml>=5.3.0 ; extra == 'xml'
-  - matplotlib>=3.9.3 ; extra == 'plot'
-  - jinja2>=3.1.5 ; extra == 'output-formatting'
-  - tabulate>=0.9.0 ; extra == 'output-formatting'
-  - pyqt5>=5.15.9 ; extra == 'clipboard'
-  - qtpy>=2.4.2 ; extra == 'clipboard'
-  - zstandard>=0.23.0 ; extra == 'compression'
-  - pytz>=2020.1 ; extra == 'timezone'
-  - adbc-driver-postgresql>=1.2.0 ; extra == 'all'
-  - adbc-driver-sqlite>=1.2.0 ; extra == 'all'
-  - beautifulsoup4>=4.12.3 ; extra == 'all'
-  - bottleneck>=1.4.2 ; extra == 'all'
-  - fastparquet>=2024.11.0 ; extra == 'all'
-  - fsspec>=2024.10.0 ; extra == 'all'
-  - gcsfs>=2024.10.0 ; extra == 'all'
-  - html5lib>=1.1 ; extra == 'all'
-  - hypothesis>=6.116.0 ; extra == 'all'
-  - jinja2>=3.1.5 ; extra == 'all'
-  - lxml>=5.3.0 ; extra == 'all'
-  - matplotlib>=3.9.3 ; extra == 'all'
-  - numba>=0.60.0 ; extra == 'all'
-  - numexpr>=2.10.2 ; extra == 'all'
-  - odfpy>=1.4.1 ; extra == 'all'
-  - openpyxl>=3.1.5 ; extra == 'all'
-  - psycopg2>=2.9.10 ; extra == 'all'
-  - pyarrow>=13.0.0 ; extra == 'all'
-  - pyiceberg>=0.8.1 ; extra == 'all'
-  - pymysql>=1.1.1 ; extra == 'all'
-  - pyqt5>=5.15.9 ; extra == 'all'
-  - pyreadstat>=1.2.8 ; extra == 'all'
-  - pytest>=8.3.4 ; extra == 'all'
-  - pytest-xdist>=3.6.1 ; extra == 'all'
-  - python-calamine>=0.3.0 ; extra == 'all'
-  - pytz>=2020.1 ; extra == 'all'
-  - pyxlsb>=1.0.10 ; extra == 'all'
-  - qtpy>=2.4.2 ; extra == 'all'
-  - scipy>=1.14.1 ; extra == 'all'
-  - s3fs>=2024.10.0 ; extra == 'all'
-  - sqlalchemy>=2.0.36 ; extra == 'all'
-  - tables>=3.10.1 ; extra == 'all'
-  - tabulate>=0.9.0 ; extra == 'all'
-  - xarray>=2024.10.0 ; extra == 'all'
-  - xlrd>=2.0.1 ; extra == 'all'
-  - xlsxwriter>=3.2.0 ; extra == 'all'
-  - zstandard>=0.23.0 ; extra == 'all'
-  requires_python: '>=3.11'
-- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/pandas/3.1.0.dev0+1043.gaee9241b41/pandas-3.1.0.dev0+1043.gaee9241b41-cp314-cp314-win_amd64.whl
-  name: pandas
-  version: 3.1.0.dev0+1043.gaee9241b41
-  requires_dist:
-  - numpy>=1.26.0 ; python_full_version < '3.14'
-  - numpy>=2.3.3 ; python_full_version >= '3.14'
-  - python-dateutil>=2.8.2
-  - tzdata ; sys_platform == 'win32'
-  - tzdata ; sys_platform == 'emscripten'
-  - hypothesis>=6.116.0 ; extra == 'test'
-  - pytest>=8.3.4 ; extra == 'test'
-  - pytest-xdist>=3.6.1 ; extra == 'test'
-  - pyarrow>=13.0.0 ; extra == 'pyarrow'
-  - bottleneck>=1.4.2 ; extra == 'performance'
-  - numba>=0.60.0 ; extra == 'performance'
-  - numexpr>=2.10.2 ; extra == 'performance'
-  - scipy>=1.14.1 ; extra == 'computation'
-  - xarray>=2024.10.0 ; extra == 'computation'
-  - fsspec>=2024.10.0 ; extra == 'fss'
-  - s3fs>=2024.10.0 ; extra == 'aws'
-  - gcsfs>=2024.10.0 ; extra == 'gcp'
-  - odfpy>=1.4.1 ; extra == 'excel'
-  - openpyxl>=3.1.5 ; extra == 'excel'
-  - python-calamine>=0.3.0 ; extra == 'excel'
-  - pyxlsb>=1.0.10 ; extra == 'excel'
-  - xlrd>=2.0.1 ; extra == 'excel'
-  - xlsxwriter>=3.2.0 ; extra == 'excel'
-  - pyarrow>=13.0.0 ; extra == 'parquet'
-  - pyarrow>=13.0.0 ; extra == 'feather'
-  - pyiceberg>=0.8.1 ; extra == 'iceberg'
-  - tables>=3.10.1 ; extra == 'hdf5'
-  - pyreadstat>=1.2.8 ; extra == 'spss'
-  - sqlalchemy>=2.0.36 ; extra == 'postgresql'
-  - psycopg2>=2.9.10 ; extra == 'postgresql'
-  - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql'
-  - sqlalchemy>=2.0.36 ; extra == 'mysql'
-  - pymysql>=1.1.1 ; extra == 'mysql'
-  - sqlalchemy>=2.0.36 ; extra == 'sql-other'
-  - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other'
-  - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other'
-  - beautifulsoup4>=4.12.3 ; extra == 'html'
-  - html5lib>=1.1 ; extra == 'html'
-  - lxml>=5.3.0 ; extra == 'html'
-  - lxml>=5.3.0 ; extra == 'xml'
-  - matplotlib>=3.9.3 ; extra == 'plot'
-  - jinja2>=3.1.5 ; extra == 'output-formatting'
-  - tabulate>=0.9.0 ; extra == 'output-formatting'
-  - pyqt5>=5.15.9 ; extra == 'clipboard'
-  - qtpy>=2.4.2 ; extra == 'clipboard'
-  - zstandard>=0.23.0 ; extra == 'compression'
-  - pytz>=2020.1 ; extra == 'timezone'
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-  - gcsfs>=2024.10.0 ; extra == 'all'
-  - html5lib>=1.1 ; extra == 'all'
-  - hypothesis>=6.116.0 ; extra == 'all'
-  - jinja2>=3.1.5 ; extra == 'all'
-  - lxml>=5.3.0 ; extra == 'all'
-  - matplotlib>=3.9.3 ; extra == 'all'
-  - numba>=0.60.0 ; extra == 'all'
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-  - openpyxl>=3.1.5 ; extra == 'all'
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-  - pyqt5>=5.15.9 ; extra == 'all'
-  - pyreadstat>=1.2.8 ; extra == 'all'
-  - pytest>=8.3.4 ; extra == 'all'
-  - pytest-xdist>=3.6.1 ; extra == 'all'
-  - python-calamine>=0.3.0 ; extra == 'all'
-  - pytz>=2020.1 ; extra == 'all'
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-  - xlsxwriter>=3.2.0 ; extra == 'all'
-  - zstandard>=0.23.0 ; extra == 'all'
-  requires_python: '>=3.11'
-- conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-1.5.3-py310h9b08913_1.conda
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+  size: 324342
+  timestamp: 1727206096912
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libthrift-0.22.0-h1fb9c8a_2.conda
+  sha256: 568bb23db02b050c3903bec05edbcab84960c8c7e5a1710dac3109df997ac7f1
+  md5: d006875f9a58a44f92aec9a7ebeb7150
   depends:
-  - libgcc-ng >=12
-  - libstdcxx-ng >=12
-  - numpy >=1.21.6,<2.0a0
+  - __osx >=11.0
+  - libcxx >=19
+  - libevent >=2.1.12,<2.1.13.0a0
+  - libzlib >=1.3.2,<2.0a0
+  - openssl >=3.5.6,<4.0a0
+  license: Apache-2.0
+  license_family: APACHE
+  purls: []
+  size: 323017
+  timestamp: 1777019893083
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libtiff-4.7.1-h4030677_1.conda
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+  - libcxx >=19
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+  - libjpeg-turbo >=3.1.0,<4.0a0
+  - liblzma >=5.8.1,<6.0a0
+  - libwebp-base >=1.6.0,<2.0a0
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+  - zstd >=1.5.7,<1.6.0a0
+  license: HPND
+  purls: []
+  size: 373892
+  timestamp: 1762022345545
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libtorch-2.12.0-cpu_generic_h5d695db_0.conda
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+  - fmt >=12.1.0,<12.2.0a0
+  - libabseil * cxx17*
+  - libabseil >=20260107.1,<20260108.0a0
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - libcxx >=19
+  - liblapack >=3.9.0,<4.0a0
+  - libprotobuf >=6.33.5,<6.33.6.0a0
+  - libuv >=1.52.1,<2.0a0
+  - libzlib >=1.3.2,<2.0a0
+  - llvm-openmp >=19.1.7
+  - onednn >=3.12,<4.0a0
+  - pybind11-abi 11
+  - sleef >=3.9.0,<4.0a0
+  constrains:
+  - pytorch 2.12.0 cpu_generic_*_0
+  - pytorch-gpu <0.0a0
+  - openblas * openmp_*
+  - libopenblas * openmp_*
+  - pytorch-cpu 2.12.0
+  license: BSD-3-Clause
+  license_family: BSD
+  purls: []
+  size: 32098564
+  timestamp: 1781355515831
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libutf8proc-2.10.0-h74a6958_0.conda
+  sha256: db843568afeafcb7eeac95b44f00f3e5964b9bb6b94d6880886843416d3f7618
+  md5: 639880d40b6e2083e20b86a726154864
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+  license: MIT
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+  purls: []
+  size: 83815
+  timestamp: 1748341829716
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libutf8proc-2.11.3-h2431656_0.conda
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+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 87916
+  timestamp: 1768735311947
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libuv-1.52.1-h1a92334_0.conda
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+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 122732
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-  - trove-classifiers>=2024.10.12 ; extra == 'tests'
-  - defusedxml ; extra == 'xmp'
-  requires_python: '>=3.10'
-- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/pillow/12.3.0.dev0/pillow-12.3.0.dev0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
-  name: pillow
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-  requires_dist:
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-  - olefile ; extra == 'docs'
-  - sphinx>=8.2 ; extra == 'docs'
-  - sphinx-autobuild ; extra == 'docs'
-  - sphinx-copybutton ; extra == 'docs'
-  - sphinx-inline-tabs ; extra == 'docs'
-  - sphinxext-opengraph ; extra == 'docs'
-  - olefile ; extra == 'fpx'
-  - olefile ; extra == 'mic'
-  - arro3-compute ; extra == 'test-arrow'
-  - arro3-core ; extra == 'test-arrow'
-  - nanoarrow ; extra == 'test-arrow'
-  - pyarrow ; extra == 'test-arrow'
-  - check-manifest ; extra == 'tests'
-  - coverage>=7.4.2 ; extra == 'tests'
-  - defusedxml ; extra == 'tests'
-  - markdown2 ; extra == 'tests'
-  - olefile ; extra == 'tests'
-  - packaging ; extra == 'tests'
-  - pyroma>=5 ; extra == 'tests'
-  - pytest ; extra == 'tests'
-  - pytest-cov ; extra == 'tests'
-  - pytest-timeout ; extra == 'tests'
-  - pytest-xdist ; extra == 'tests'
-  - trove-classifiers>=2024.10.12 ; extra == 'tests'
-  - defusedxml ; extra == 'xmp'
-  requires_python: '>=3.10'
-- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/pillow/12.3.0.dev0/pillow-12.3.0.dev0-cp314-cp314-win_amd64.whl
-  name: pillow
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-  - olefile ; extra == 'docs'
-  - sphinx>=8.2 ; extra == 'docs'
-  - sphinx-autobuild ; extra == 'docs'
-  - sphinx-copybutton ; extra == 'docs'
-  - sphinx-inline-tabs ; extra == 'docs'
-  - sphinxext-opengraph ; extra == 'docs'
-  - olefile ; extra == 'fpx'
-  - olefile ; extra == 'mic'
-  - arro3-compute ; extra == 'test-arrow'
-  - arro3-core ; extra == 'test-arrow'
-  - nanoarrow ; extra == 'test-arrow'
-  - pyarrow ; extra == 'test-arrow'
-  - check-manifest ; extra == 'tests'
-  - coverage>=7.4.2 ; extra == 'tests'
-  - defusedxml ; extra == 'tests'
-  - markdown2 ; extra == 'tests'
-  - olefile ; extra == 'tests'
-  - packaging ; extra == 'tests'
-  - pyroma>=5 ; extra == 'tests'
-  - pytest ; extra == 'tests'
-  - pytest-cov ; extra == 'tests'
-  - pytest-timeout ; extra == 'tests'
-  - pytest-xdist ; extra == 'tests'
-  - trove-classifiers>=2024.10.12 ; extra == 'tests'
-  - defusedxml ; extra == 'xmp'
-  requires_python: '>=3.10'
-- conda: https://conda.anaconda.org/conda-forge/linux-64/pillow-12.2.0-py310h5a73078_0.conda
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-  license: HPND
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-  size: 890549
-  timestamp: 1775060059882
-- conda: https://conda.anaconda.org/conda-forge/linux-64/pillow-12.2.0-py311hf88fc01_0.conda
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-  - lcms2 >=2.18,<3.0a0
-  - tk >=8.6.13,<8.7.0a0
-  license: HPND
+  - xarray >=2024.10.0
+  - xlrd >=2.0.1
+  - xlsxwriter >=3.2.0
+  - zstandard >=0.23.0
+  license: BSD-3-Clause
+  license_family: BSD
   purls:
-  - pkg:pypi/pillow?source=hash-mapping
-  size: 1082797
-  timestamp: 1775060059882
-- conda: https://conda.anaconda.org/conda-forge/osx-64/pillow-12.2.0-py310h0c0a54c_0.conda
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+  size: 14368928
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-- conda: https://conda.anaconda.org/conda-forge/osx-64/pillow-12.2.0-py314hc904d5e_0.conda
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+  - fonts-conda-ecosystem
+  - fribidi >=1.0.10,<2.0a0
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-  license: HPND
-  purls:
-  - pkg:pypi/pillow?source=hash-mapping
-  size: 1015315
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+  - cairo >=1.18.4,<2.0a0
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+  - fonts-conda-ecosystem
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/pcre2-10.47-h30297fc_0.conda
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+  license: BSD-3-Clause
+  license_family: BSD
+  purls: []
+  size: 850231
+  timestamp: 1763655726735
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pillow-12.2.0-py310hc037f36_0.conda
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-- conda: https://conda.anaconda.org/conda-forge/win-64/pillow-10.4.0-py310h3e38d90_1.conda
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/polars-1.5.0-py310h0bf8226_0.conda
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+  - python >=3.10,<3.11.0a0 *_cpython
   - python_abi 3.10.* *_cp310
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-  - ucrt >=10.0.20348.0
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-  - vc14_runtime >=14.29.30139
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+  - typing_extensions >=4.0.0
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+  license_family: MIT
   purls:
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-- conda: https://conda.anaconda.org/conda-forge/win-64/pillow-12.2.0-py311h17b8079_0.conda
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/polars-runtime-32-1.41.2-py310hb2fc7d1_0.conda
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-- conda: https://conda.anaconda.org/conda-forge/win-64/pillow-12.2.0-py313h38f99e1_0.conda
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   - python_abi 3.13.* *_cp313
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+  license_family: APACHE
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-- conda: https://conda.anaconda.org/conda-forge/win-64/pillow-12.2.0-py314h61b30b5_0.conda
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+  - scikit-image>=0.22.0 ; extra == 'docs'
+  - pandas>=1.5.0 ; extra == 'docs'
+  - rich>=14.1.0 ; extra == 'docs'
+  - seaborn>=0.13.0 ; extra == 'docs'
+  - memory-profiler>=0.57.0 ; extra == 'docs'
+  - sphinx>=7.3.7 ; extra == 'docs'
+  - sphinx-copybutton>=0.5.2 ; extra == 'docs'
+  - sphinx-gallery>=0.17.1 ; extra == 'docs'
+  - numpydoc>=1.2.0 ; extra == 'docs'
+  - pillow>=12.1.1 ; extra == 'docs'
+  - pooch>=1.8.0 ; extra == 'docs'
+  - sphinx-prompt>=1.4.0 ; extra == 'docs'
+  - sphinxext-opengraph>=0.9.1 ; extra == 'docs'
+  - plotly>=5.22.0 ; extra == 'docs'
+  - polars>=0.20.30 ; extra == 'docs'
+  - sphinx-design>=0.6.0 ; extra == 'docs'
+  - sphinxcontrib-sass>=0.3.4 ; extra == 'docs'
+  - pydata-sphinx-theme>=0.15.3 ; extra == 'docs'
+  - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs'
+  - towncrier>=24.8.0 ; extra == 'docs'
+  - matplotlib>=3.6.1 ; extra == 'examples'
+  - scikit-image>=0.22.0 ; extra == 'examples'
+  - pandas>=1.5.0 ; extra == 'examples'
+  - rich>=14.1.0 ; extra == 'examples'
+  - seaborn>=0.13.0 ; extra == 'examples'
+  - pooch>=1.8.0 ; extra == 'examples'
+  - plotly>=5.22.0 ; extra == 'examples'
+  - matplotlib>=3.6.1 ; extra == 'tests'
+  - pandas>=1.5.0 ; extra == 'tests'
+  - rich>=14.1.0 ; extra == 'tests'
+  - pytest>=7.1.2 ; extra == 'tests'
+  - pytest-cov>=2.9.0 ; extra == 'tests'
+  - ruff>=0.12.2 ; extra == 'tests'
+  - mypy>=1.15 ; extra == 'tests'
+  - pyamg>=5.0.0 ; extra == 'tests'
+  - polars>=0.20.30 ; extra == 'tests'
+  - pyarrow>=13.0.0 ; extra == 'tests'
+  - numpydoc>=1.2.0 ; extra == 'tests'
+  - pooch>=1.8.0 ; extra == 'tests'
+  - conda-lock==3.0.1 ; extra == 'maintenance'
+  requires_python: '>=3.11'
+- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/scikit-learn/1.10.dev0/scikit_learn-1.10.dev0-cp314-cp314-win_amd64.whl
+  name: scikit-learn
+  version: 1.10.dev0
+  index: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
+  requires_dist:
+  - numpy>=1.24.1
+  - scipy>=1.10.0
+  - joblib>=1.4.0
+  - narwhals>=2.0.1
+  - threadpoolctl>=3.5.0
+  - numpy>=1.24.1 ; extra == 'build'
+  - scipy>=1.10.0 ; extra == 'build'
+  - cython>=3.1.2 ; extra == 'build'
+  - meson-python>=0.17.1 ; extra == 'build'
+  - numpy>=1.24.1 ; extra == 'install'
+  - scipy>=1.10.0 ; extra == 'install'
+  - joblib>=1.4.0 ; extra == 'install'
+  - narwhals>=2.0.1 ; extra == 'install'
+  - threadpoolctl>=3.5.0 ; extra == 'install'
+  - matplotlib>=3.6.1 ; extra == 'benchmark'
+  - pandas>=1.5.0 ; extra == 'benchmark'
+  - memory-profiler>=0.57.0 ; extra == 'benchmark'
+  - matplotlib>=3.6.1 ; extra == 'docs'
+  - scikit-image>=0.22.0 ; extra == 'docs'
+  - pandas>=1.5.0 ; extra == 'docs'
+  - rich>=14.1.0 ; extra == 'docs'
+  - seaborn>=0.13.0 ; extra == 'docs'
+  - memory-profiler>=0.57.0 ; extra == 'docs'
+  - sphinx>=7.3.7 ; extra == 'docs'
+  - sphinx-copybutton>=0.5.2 ; extra == 'docs'
+  - sphinx-gallery>=0.17.1 ; extra == 'docs'
+  - numpydoc>=1.2.0 ; extra == 'docs'
+  - pillow>=12.1.1 ; extra == 'docs'
+  - pooch>=1.8.0 ; extra == 'docs'
+  - sphinx-prompt>=1.4.0 ; extra == 'docs'
+  - sphinxext-opengraph>=0.9.1 ; extra == 'docs'
+  - plotly>=5.22.0 ; extra == 'docs'
+  - polars>=0.20.30 ; extra == 'docs'
+  - sphinx-design>=0.6.0 ; extra == 'docs'
+  - sphinxcontrib-sass>=0.3.4 ; extra == 'docs'
+  - pydata-sphinx-theme>=0.15.3 ; extra == 'docs'
+  - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs'
+  - towncrier>=24.8.0 ; extra == 'docs'
+  - matplotlib>=3.6.1 ; extra == 'examples'
+  - scikit-image>=0.22.0 ; extra == 'examples'
+  - pandas>=1.5.0 ; extra == 'examples'
+  - rich>=14.1.0 ; extra == 'examples'
+  - seaborn>=0.13.0 ; extra == 'examples'
+  - pooch>=1.8.0 ; extra == 'examples'
+  - plotly>=5.22.0 ; extra == 'examples'
+  - matplotlib>=3.6.1 ; extra == 'tests'
+  - pandas>=1.5.0 ; extra == 'tests'
+  - rich>=14.1.0 ; extra == 'tests'
+  - pytest>=7.1.2 ; extra == 'tests'
+  - pytest-cov>=2.9.0 ; extra == 'tests'
+  - ruff>=0.12.2 ; extra == 'tests'
+  - mypy>=1.15 ; extra == 'tests'
+  - pyamg>=5.0.0 ; extra == 'tests'
+  - polars>=0.20.30 ; extra == 'tests'
+  - pyarrow>=13.0.0 ; extra == 'tests'
+  - numpydoc>=1.2.0 ; extra == 'tests'
+  - pooch>=1.8.0 ; extra == 'tests'
+  - conda-lock==3.0.1 ; extra == 'maintenance'
+  requires_python: '>=3.11'
+- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/scipy/1.19.0.dev0/scipy-1.19.0.dev0-cp314-cp314-macosx_10_15_x86_64.whl
+  name: scipy
+  version: 1.19.0.dev0
+  index: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
+  requires_dist:
+  - numpy>=2.0.0
+  - pooch ; extra == 'all'
+  - threadpoolctl ; extra == 'all'
+  - matplotlib ; extra == 'all'
+  requires_python: '>=3.12'
+- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/scipy/1.19.0.dev0/scipy-1.19.0.dev0-cp314-cp314-macosx_12_0_arm64.whl
+  name: scipy
+  version: 1.19.0.dev0
+  index: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
+  requires_dist:
+  - numpy>=2.0.0
+  - pooch ; extra == 'all'
+  - threadpoolctl ; extra == 'all'
+  - matplotlib ; extra == 'all'
+  requires_python: '>=3.12'
+- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/scipy/1.19.0.dev0/scipy-1.19.0.dev0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
+  name: scipy
+  version: 1.19.0.dev0
+  index: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
+  requires_dist:
+  - numpy>=2.0.0
+  - pooch ; extra == 'all'
+  - threadpoolctl ; extra == 'all'
+  - matplotlib ; extra == 'all'
+  requires_python: '>=3.12'
+- pypi: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/scipy/1.19.0.dev0/scipy-1.19.0.dev0-cp314-cp314-win_amd64.whl
+  name: scipy
+  version: 1.19.0.dev0
+  index: https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
+  requires_dist:
+  - numpy>=2.0.0
+  - pooch ; extra == 'all'
+  - threadpoolctl ; extra == 'all'
+  - matplotlib ; extra == 'all'
+  requires_python: '>=3.12'
diff --git a/pyproject.toml b/pyproject.toml
index 5259d8ca9..38991146f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -55,6 +55,7 @@ dev = [
   "jupyterlite-pyodide-kernel",
   "numpydoc",
   "pydata-sphinx-theme",
+  "sphinx-design>=0.6.0",
   "seaborn",
   # TODO: unpin sphinx when incmpatibility with autosummary-accessors is fixed:
   # https://github.com/xarray-contrib/sphinx-autosummary-accessors/issues/165
@@ -111,6 +112,7 @@ matplotlib = "*"
 pydot = "*"
 numpydoc = "*"
 pydata-sphinx-theme = "*"
+sphinx-design = "*"
 plotly = "*"
 memory_profiler = "*"
 seaborn = "*"