diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
index 53cb88749..d8a12cde2 100644
--- a/.github/workflows/testing.yml
+++ b/.github/workflows/testing.yml
@@ -20,7 +20,8 @@ jobs:
             ci-py309-min-optional-deps,
             ci-py311-transformers,
             ci-py313-latest-deps,
-            ci-py313-latest-optional-deps
+            ci-py313-latest-optional-deps,
+            ci-py313-polars-without-pyarrow
         ]
     runs-on: ${{ matrix.os }}
     steps:
diff --git a/pixi.lock b/pixi.lock
index 35c396b54..2b21835e9 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -5804,6 +5804,680 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/win-64/zstandard-0.25.0-py313h5fd188c_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-hbeecb71_2.conda
       - pypi: ./
+  ci-py313-polars-without-pyarrow:
+    channels:
+    - url: https://conda.anaconda.org/conda-forge/
+    - url: https://conda.anaconda.org/pytorch/
+    indexes:
+    - https://pypi.org/simple
+    packages:
+      linux-64:
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/_python_abi3_support-1.0-hd8ed1ab_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/adwaita-icon-theme-49.0-unix_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/alabaster-1.0.0-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.14-hb9d3cd8_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/babel-2.17.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-1.1.0-hb03c661_4.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.1.0-hb03c661_4.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.1.0-py313h7033f15_4.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_8.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.8.3-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cairo-1.18.4-h3394656_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2025.8.3-pyhd8ed1ab_0.conda
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+      - conda: https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cyrus-sasl-2.1.28-hd9c7081_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/dbus-1.16.2-h3c4dab8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/docutils-0.21.2-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/double-conversion-3.3.1-h5888daf_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/exceptiongroup-1.3.0-pyhd8ed1ab_0.conda
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+      - 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
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+      - 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-1-0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/fonttools-4.60.1-py313h3dea7bd_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/freetype-2.14.1-ha770c72_0.conda
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+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gdk-pixbuf-2.44.3-h2b0a6b4_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/glib-tools-2.86.0-hf516916_0.conda
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+      - conda: https://conda.anaconda.org/conda-forge/linux-64/harfbuzz-12.1.0-h15599e2_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/hicolor-icon-theme-0.17-ha770c72_2.tar.bz2
+      - 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-75.1-he02047a_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/idna-3.10-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/imagesize-1.4.1-pyhd8ed1ab_0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/joblib-1.5.2-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-1.4.9-py313hc8edb43_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/krb5-1.21.3-h659f571_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/lcms2-2.17-h717163a_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.44-ha97dd6f_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/lerc-4.0.0-h0aef613_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-36_h4a7cf45_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.1.0-hb03c661_4.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.1.0-hb03c661_4.conda
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+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcups-2.3.3-hb8b1518_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.24-h86f0d12_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdrm-2.4.125-hb03c661_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20250104-pl5321h7949ede_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libegl-1.7.0-ha4b6fd6_2.conda
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+  - libfreetype6 >=2.14.1
+  - libwebp-base >=1.6.0,<2.0a0
+  - libjpeg-turbo >=3.1.0,<4.0a0
+  - libxcb >=1.17.0,<2.0a0
+  - python_abi 3.13.* *_cp313
+  - tk >=8.6.13,<8.7.0a0
+  - openjpeg >=2.5.3,<3.0a0
+  license: HPND
+  purls:
+  - pkg:pypi/pillow?source=compressed-mapping
+  size: 963129
+  timestamp: 1758208741247
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pillow-11.3.0-py39hfea3036_0.conda
   sha256: ff0de09b24b4cebb4162d3595a15549616f73187c13939e4eabb02b00b2cfa76
   md5: 01c0fba8d135065c5d42ec17feb702b8
@@ -25451,6 +27633,33 @@ packages:
   - pkg:pypi/pillow?source=hash-mapping
   size: 898496
   timestamp: 1758013111396
+- conda: https://conda.anaconda.org/conda-forge/win-64/pillow-11.3.0-py313hf455b62_3.conda
+  sha256: c52cd3bb28f8b9efca4305298792eeb3c323358cb4812fba21f8c9bea2b77e19
+  md5: 1f4089963969058084f252c4587512e2
+  depends:
+  - python
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  - ucrt >=10.0.20348.0
+  - libwebp-base >=1.6.0,<2.0a0
+  - libtiff >=4.7.0,<4.8.0a0
+  - libzlib >=1.3.1,<2.0a0
+  - python_abi 3.13.* *_cp313
+  - openjpeg >=2.5.3,<3.0a0
+  - libxcb >=1.17.0,<2.0a0
+  - tk >=8.6.13,<8.7.0a0
+  - lcms2 >=2.17,<3.0a0
+  - libfreetype >=2.14.1
+  - libfreetype6 >=2.14.1
+  - libjpeg-turbo >=3.1.0,<4.0a0
+  license: HPND
+  purls:
+  - pkg:pypi/pillow?source=hash-mapping
+  size: 944083
+  timestamp: 1758208682964
 - conda: https://conda.anaconda.org/conda-forge/linux-64/pixman-0.46.4-h54a6638_1.conda
   sha256: 43d37bc9ca3b257c5dd7bf76a8426addbdec381f6786ff441dc90b1a49143b6a
   md5: c01af13bdc553d1a8fbfff6e8db075f0
@@ -27044,6 +29253,18 @@ packages:
   - pkg:pypi/pyparsing?source=compressed-mapping
   size: 104029
   timestamp: 1757767060575
+- conda: https://conda.anaconda.org/conda-forge/noarch/pyparsing-3.2.5-pyhcf101f3_0.conda
+  sha256: 6814b61b94e95ffc45ec539a6424d8447895fef75b0fec7e1be31f5beee883fb
+  md5: 6c8979be6d7a17692793114fa26916e8
+  depends:
+  - python >=3.10
+  - python
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/pyparsing?source=compressed-mapping
+  size: 104044
+  timestamp: 1758436411254
 - conda: https://conda.anaconda.org/conda-forge/linux-64/pyqt-5.15.11-py39h08c78a2_1.conda
   sha256: 04e933d4ac849bf0361219d16b4ddc0e1b6cb4627b0c1ef0cb0e6e437962f8ca
   md5: 3fdfe79c112d99b523c17bae9aa9538c
@@ -27203,6 +29424,31 @@ packages:
   - pkg:pypi/shiboken6?source=hash-mapping
   size: 10165311
   timestamp: 1756673817908
+- conda: https://conda.anaconda.org/conda-forge/linux-64/pyside6-6.9.3-py313h85046ba_1.conda
+  sha256: 8d143b89d075b39fa25e69ad9be2396f4b591a205f95b2bf5a81a14cd397c56f
+  md5: bb7ac52bfa917611096023598a7df152
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - libclang13 >=21.1.2
+  - libegl >=1.7.0,<2.0a0
+  - libgcc >=14
+  - libgl >=1.7.0,<2.0a0
+  - libopengl >=1.7.0,<2.0a0
+  - libstdcxx >=14
+  - libvulkan-loader >=1.4.313.0,<2.0a0
+  - libxml2
+  - libxml2-16 >=2.14.6
+  - libxslt >=1.1.43,<2.0a0
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313
+  - qt6-main 6.9.3.*
+  - qt6-main >=6.9.3,<6.10.0a0
+  license: LGPL-3.0-only
+  purls:
+  - pkg:pypi/pyside6?source=hash-mapping
+  - pkg:pypi/shiboken6?source=hash-mapping
+  size: 10101334
+  timestamp: 1759403237088
 - conda: https://conda.anaconda.org/conda-forge/win-64/pyside6-6.9.2-py311h5d1a980_1.conda
   sha256: 8d6f5411eea073cf77daf335d904f64701abc3e8086b1f540c2b24ea8f342276
   md5: 372dcf53b700d63d76f46dab66bf41ed
@@ -27266,6 +29512,28 @@ packages:
   - pkg:pypi/shiboken6?source=hash-mapping
   size: 8904821
   timestamp: 1756674303067
+- conda: https://conda.anaconda.org/conda-forge/win-64/pyside6-6.9.3-py313h475ba69_1.conda
+  sha256: e12121e1e7abc9a328e46ecee4addf1d56f56c75b92eba2486b6987aeef1ee36
+  md5: 9b77f3ed4ce1e607c8646ec613a94f91
+  depends:
+  - libclang13 >=21.1.2
+  - libvulkan-loader >=1.4.313.0,<2.0a0
+  - libxml2
+  - libxml2-16 >=2.14.6
+  - libxslt >=1.1.43,<2.0a0
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313
+  - qt6-main 6.9.3.*
+  - qt6-main >=6.9.3,<6.10.0a0
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: LGPL-3.0-only
+  purls:
+  - pkg:pypi/pyside6?source=hash-mapping
+  - pkg:pypi/shiboken6?source=hash-mapping
+  size: 8898905
+  timestamp: 1759403334290
 - conda: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyh09c184e_7.conda
   sha256: d016e04b0e12063fbee4a2d5fbb9b39a8d191b5a0042f0b8459188aedeabb0ca
   md5: e2fd202833c4a981ce8a65974fe4abd1
@@ -28685,6 +30953,70 @@ packages:
   purls: []
   size: 52405921
   timestamp: 1758011263853
+- conda: https://conda.anaconda.org/conda-forge/linux-64/qt6-main-6.9.3-h5c1c036_0.conda
+  sha256: 999ce4a6af5f9570373047f7c61ccc86d17bef294b402b7297b8efc25ec3b5e9
+  md5: cc0bffcaf6410aba9c6581dfdc18012d
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - alsa-lib >=1.2.14,<1.3.0a0
+  - dbus >=1.16.2,<2.0a0
+  - double-conversion >=3.3.1,<3.4.0a0
+  - fontconfig >=2.15.0,<3.0a0
+  - fonts-conda-ecosystem
+  - harfbuzz >=12.0.0
+  - icu >=75.1,<76.0a0
+  - krb5 >=1.21.3,<1.22.0a0
+  - libclang-cpp21.1 >=21.1.2,<21.2.0a0
+  - libclang13 >=21.1.2
+  - libcups >=2.3.3,<2.4.0a0
+  - libdrm >=2.4.125,<2.5.0a0
+  - libegl >=1.7.0,<2.0a0
+  - libfreetype >=2.14.1
+  - libfreetype6 >=2.14.1
+  - libgcc >=14
+  - libgl >=1.7.0,<2.0a0
+  - libglib >=2.86.0,<3.0a0
+  - libjpeg-turbo >=3.1.0,<4.0a0
+  - libllvm21 >=21.1.2,<21.2.0a0
+  - libpng >=1.6.50,<1.7.0a0
+  - libpq >=18.0,<19.0a0
+  - libsqlite >=3.50.4,<4.0a0
+  - libstdcxx >=14
+  - libtiff >=4.7.1,<4.8.0a0
+  - libvulkan-loader >=1.4.313.0,<2.0a0
+  - libwebp-base >=1.6.0,<2.0a0
+  - libxcb >=1.17.0,<2.0a0
+  - libxkbcommon >=1.11.0,<2.0a0
+  - libxml2
+  - libxml2-16 >=2.14.6
+  - libzlib >=1.3.1,<2.0a0
+  - openssl >=3.5.3,<4.0a0
+  - pcre2 >=10.46,<10.47.0a0
+  - wayland >=1.24.0,<2.0a0
+  - xcb-util >=0.4.1,<0.5.0a0
+  - xcb-util-cursor >=0.1.5,<0.2.0a0
+  - xcb-util-image >=0.4.0,<0.5.0a0
+  - xcb-util-keysyms >=0.4.1,<0.5.0a0
+  - xcb-util-renderutil >=0.3.10,<0.4.0a0
+  - xcb-util-wm >=0.4.2,<0.5.0a0
+  - xorg-libice >=1.1.2,<2.0a0
+  - xorg-libsm >=1.2.6,<2.0a0
+  - xorg-libx11 >=1.8.12,<2.0a0
+  - xorg-libxcomposite >=0.4.6,<1.0a0
+  - xorg-libxcursor >=1.2.3,<2.0a0
+  - xorg-libxdamage >=1.1.6,<2.0a0
+  - xorg-libxext >=1.3.6,<2.0a0
+  - xorg-libxrandr >=1.5.4,<2.0a0
+  - xorg-libxtst >=1.2.5,<2.0a0
+  - xorg-libxxf86vm >=1.1.6,<2.0a0
+  - zstd >=1.5.7,<1.6.0a0
+  constrains:
+  - qt 6.9.3
+  license: LGPL-3.0-only
+  license_family: LGPL
+  purls: []
+  size: 54537863
+  timestamp: 1759251856141
 - conda: https://conda.anaconda.org/conda-forge/win-64/qt6-main-6.9.2-ha0de62e_2.conda
   sha256: 47b9847c9d543e0f5cdce7cfcc20f9cf017c55840b6c841c97520cd0c6c463ed
   md5: a318de6656e3ecc332dcd42051c8b622
@@ -28714,6 +31046,36 @@ packages:
   purls: []
   size: 82001367
   timestamp: 1758025652766
+- conda: https://conda.anaconda.org/conda-forge/win-64/qt6-main-6.9.3-ha0de62e_0.conda
+  sha256: 2fb9f30a6bf9211f3ef0e1f49990a2f70794ed85bce21d172864f129d2437714
+  md5: ba19851ccdcee8d0a074cb3738b08f60
+  depends:
+  - double-conversion >=3.3.1,<3.4.0a0
+  - harfbuzz >=12.0.0
+  - icu >=75.1,<76.0a0
+  - krb5 >=1.21.3,<1.22.0a0
+  - libclang13 >=21.1.2
+  - libglib >=2.86.0,<3.0a0
+  - libjpeg-turbo >=3.1.0,<4.0a0
+  - libpng >=1.6.50,<1.7.0a0
+  - libsqlite >=3.50.4,<4.0a0
+  - libtiff >=4.7.1,<4.8.0a0
+  - libvulkan-loader >=1.4.313.0,<2.0a0
+  - libwebp-base >=1.6.0,<2.0a0
+  - libzlib >=1.3.1,<2.0a0
+  - openssl >=3.5.3,<4.0a0
+  - pcre2 >=10.46,<10.47.0a0
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  - zstd >=1.5.7,<1.6.0a0
+  constrains:
+  - qt 6.9.3
+  license: LGPL-3.0-only
+  license_family: LGPL
+  purls: []
+  size: 96316397
+  timestamp: 1759254007679
 - conda: https://conda.anaconda.org/conda-forge/linux-64/rdma-core-59.0-hecca717_0.conda
   sha256: ce0e671ce8b6151b135eb6b5aea9caed4d4032a416f73a04a3fb29048fd772c3
   md5: d95e4c5679876a9d3f2211263f75dc9c
@@ -30137,7 +32499,7 @@ packages:
 - pypi: ./
   name: skrub
   version: 0.7.dev0
-  sha256: 62c126d160758bc116ff2a2ed43f31fae909415d858a89513aab1408080d8a5a
+  sha256: 2e0f05a0ee03b28d835948da413824866af5f49f138fb7ceaf89792f9d6407d7
   requires_dist:
   - numpy>=1.23.5
   - pandas>=1.5.3
@@ -32068,6 +34430,18 @@ packages:
   purls: []
   size: 19575
   timestamp: 1727794961233
+- conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxfixes-6.0.2-hb03c661_0.conda
+  sha256: 83c4c99d60b8784a611351220452a0a85b080668188dce5dfa394b723d7b64f4
+  md5: ba231da7fccf9ea1e768caf5c7099b84
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=14
+  - xorg-libx11 >=1.8.12,<2.0a0
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 20071
+  timestamp: 1759282564045
 - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxi-1.8.2-hb9d3cd8_0.conda
   sha256: 1a724b47d98d7880f26da40e45f01728e7638e6ec69f35a3e11f92acd05f9e7a
   md5: 17dcc85db3c7886650b8908b183d6876
@@ -32232,6 +34606,17 @@ packages:
   purls: []
   size: 31034
   timestamp: 1677037259999
+- conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-xorgproto-2024.1-hb9d3cd8_1.conda
+  sha256: 1316680be6edddee0156b86ec1102fc8286f51c1a5440366ed1db596a2dc3731
+  md5: 7c21106b851ec72c037b162c216d8f05
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=13
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 565425
+  timestamp: 1726846388217
 - conda: https://conda.anaconda.org/conda-forge/win-64/xorg-xproto-7.0.31-hcd874cb_1007.tar.bz2
   sha256: b84cacba8479fa14199c9255fb62e005cacc619e90198c53b1653973709ec331
   md5: 88f3c65d2ad13826a9e0b162063be023
diff --git a/pyproject.toml b/pyproject.toml
index 96d80a84b..5d52e254c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -168,6 +168,10 @@ pyarrow = "==15.0.2"
 polars = "==0.20.15"
 plotly = "*"
 
+[tool.pixi.feature.polars-without-pyarrow.dependencies]
+polars = "*"
+plotly = "*"
+
 [tool.pixi.feature.py309.dependencies]
 python = "~=3.9.0"
 
@@ -211,6 +215,7 @@ ci-py311-transformers = ["py311", "transformers", "test"]
 ci-py312-latest-deps = ["py312", "test"]
 ci-py312-latest-optional-deps = ["py312", "optional", "test"]
 ci-py313-latest-deps = ["py313", "test"]
+ci-py313-polars-without-pyarrow = ["py313", "test", "polars-without-pyarrow"]
 ci-py313-latest-optional-deps = ["py313", "optional", "test"]
 
 [tool.black]
diff --git a/skrub/_dataframe/tests/test_common.py b/skrub/_dataframe/tests/test_common.py
index b0db4de4f..52c32e195 100644
--- a/skrub/_dataframe/tests/test_common.py
+++ b/skrub/_dataframe/tests/test_common.py
@@ -18,6 +18,7 @@
 import skrub
 from skrub import selectors as s
 from skrub._dataframe import _common as ns
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 def test_not_implemented():
@@ -103,6 +104,7 @@ def test_to_numpy(df_module, example_data_dict):
     assert_array_equal(array[2:], np.asarray(example_data_dict["str-col"])[2:])
 
 
+@polars_installed_without_pyarrow
 def test_to_pandas(df_module, pd_module):
     with pytest.raises(TypeError):
         ns.to_pandas(np.arange(3))
@@ -725,6 +727,7 @@ def test_mean(df_module):
     )
 
 
+@polars_installed_without_pyarrow
 def test_corr(df_module):
     df = df_module.example_dataframe
 
diff --git a/skrub/_reporting/tests/test_patch_display.py b/skrub/_reporting/tests/test_patch_display.py
index 1c877233f..f6c73f5de 100644
--- a/skrub/_reporting/tests/test_patch_display.py
+++ b/skrub/_reporting/tests/test_patch_display.py
@@ -3,10 +3,12 @@
 import pytest
 
 from skrub import patch_display, unpatch_display
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 @pytest.mark.parametrize("repeat_patch", [1, 2])
 @pytest.mark.parametrize("repeat_unpatch", [1, 2])
+@polars_installed_without_pyarrow
 def test_patch_display(df_module, repeat_patch, repeat_unpatch, capsys):
     df = df_module.make_dataframe(
         dict(
diff --git a/skrub/_reporting/tests/test_summarize.py b/skrub/_reporting/tests/test_summarize.py
index bfb809b14..4424102af 100644
--- a/skrub/_reporting/tests/test_summarize.py
+++ b/skrub/_reporting/tests/test_summarize.py
@@ -9,11 +9,13 @@
 from skrub import _dataframe as sbd
 from skrub._reporting import _sample_table
 from skrub._reporting._summarize import summarize_dataframe
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 @pytest.mark.parametrize("order_by", [None, "date.utc", "value"])
 @pytest.mark.parametrize("with_plots", [False, True])
 @pytest.mark.parametrize("with_associations", [False, True])
+@polars_installed_without_pyarrow
 def test_summarize(
     monkeypatch, df_module, air_quality, order_by, with_plots, with_associations
 ):
@@ -114,6 +116,7 @@ def test_high_cardinality_column(pd_module):
     assert "10 most frequent" in summary["columns"][0]["value_counts_plot"]
 
 
+@polars_installed_without_pyarrow
 def test_all_null(df_module):
     df = df_module.make_dataframe(
         {
@@ -142,6 +145,7 @@ def make_summary(df_size, **summarize_kwargs):
     return make_summary
 
 
+@polars_installed_without_pyarrow
 def test_small_df(small_df_summary):
     summary = small_df_summary(11)
     thead, first_slice, ellipsis, last_slice = summary["sample_table"]["parts"]
@@ -256,6 +260,7 @@ def test_duplicate_columns(pd_module):
     assert cols[1]["mean"] == 3.5
 
 
+@polars_installed_without_pyarrow
 def test_high_cardinality_columns(df_module):
     df = df_module.make_dataframe(
         {
@@ -269,6 +274,7 @@ def test_high_cardinality_columns(df_module):
     assert cols[1]["is_high_cardinality"]
 
 
+@polars_installed_without_pyarrow
 def test_bool_column_mean(df_module):
     df = df_module.make_dataframe({"a": [True, False, True, True, False, True]})
     summary = summarize_dataframe(df)
diff --git a/skrub/_reporting/tests/test_table_report.py b/skrub/_reporting/tests/test_table_report.py
index ff040f607..f57b9335a 100644
--- a/skrub/_reporting/tests/test_table_report.py
+++ b/skrub/_reporting/tests/test_table_report.py
@@ -11,12 +11,14 @@
 from skrub import TableReport, ToDatetime, datasets
 from skrub import _dataframe as sbd
 from skrub._reporting._sample_table import make_table
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 def get_report_id(html):
     return re.search(r'<skrub-table-report.*?id="report_([a-z0-9]+)"', html).group(1)
 
 
+@polars_installed_without_pyarrow
 def test_report(air_quality):
     col_filt = {
         "first_2": {
@@ -64,11 +66,13 @@ def test_report(air_quality):
     assert len(all_report_ids) == len(set(all_report_ids))
 
 
+@polars_installed_without_pyarrow
 def test_few_columns(df_module, check_polars_numpy2):
     report = TableReport(df_module.example_dataframe)
     assert "First 10 columns" not in report.html()
 
 
+@polars_installed_without_pyarrow
 def test_few_rows(df_module, check_polars_numpy2):
     df = sbd.slice(df_module.example_dataframe, 2)
     TableReport(df).html()
@@ -84,6 +88,7 @@ def test_open(pd_module, browser_mock):
     assert b"the title" in browser_mock.content
 
 
+@polars_installed_without_pyarrow
 def test_non_hashable_values(df_module):
     # non-regression test for #1066
     df = df_module.make_dataframe(dict(a=[[1, 2, 3], None, [4]]))
@@ -91,6 +96,7 @@ def test_non_hashable_values(df_module):
     assert "[1, 2, 3]" in html
 
 
+@polars_installed_without_pyarrow
 def test_nat(df_module):
     # non-regression for:
     # https://github.com/skrub-data/skrub/issues/1111
@@ -103,6 +109,7 @@ def test_nat(df_module):
     TableReport(df).html()
 
 
+@polars_installed_without_pyarrow
 def test_bool_column_mean(df_module):
     df = df_module.make_dataframe({"a": [True, False, True, True, False, True]})
     html = TableReport(df).html()
@@ -116,6 +123,7 @@ def test_duplicate_columns(pd_module):
     TableReport(df).html()
 
 
+@polars_installed_without_pyarrow
 def test_infinite_values(df_module):
     # Non-regression for https://github.com/skrub-data/skrub/issues/1134
     # (histogram plot failing with infinite values)
@@ -129,6 +137,7 @@ def test_infinite_values(df_module):
     TableReport(df).html()
 
 
+@polars_installed_without_pyarrow
 def test_duration(df_module):
     df = df_module.make_dataframe(
         {"a": [datetime.timedelta(days=2), datetime.timedelta(days=3)]}
@@ -187,6 +196,7 @@ def test_write_html_with_not_utf8_encoding(tmp_path, pd_module):
     assert "</html>" not in saved_content
 
 
+@polars_installed_without_pyarrow
 def test_verbosity_parameter(df_module, capsys):
     df = df_module.make_dataframe(
         dict(
@@ -209,6 +219,7 @@ def test_verbosity_parameter(df_module, capsys):
     assert capsys.readouterr().err != ""
 
 
+@polars_installed_without_pyarrow
 def test_write_to_stderr(df_module, capsys):
     df = df_module.make_dataframe(
         dict(
@@ -229,6 +240,7 @@ def test_write_to_stderr(df_module, capsys):
     assert re.search(pattern, captured.err)
 
 
+@polars_installed_without_pyarrow
 def test_max_plot_columns_parameter(df_module):
     df = df_module.make_dataframe(
         {f"col_{i}": [i + j for j in range(3)] for i in range(10)}
@@ -288,6 +300,7 @@ def test_error_input_type():
         TableReport(df)
 
 
+@polars_installed_without_pyarrow
 def test_single_column_report(df_module):
     # Check that single column report works
     single_col = df_module.example_column
diff --git a/skrub/conftest.py b/skrub/conftest.py
index e4cc361ad..0bc4684ad 100644
--- a/skrub/conftest.py
+++ b/skrub/conftest.py
@@ -95,6 +95,21 @@ def _example_data_dict():
 except ImportError:
     _POLARS_INSTALLED = False
 
+if _POLARS_INSTALLED:
+    try:
+        import pyarrow  # noqa: F401
+
+        _polars_installed_without_pyarrow = False
+    except ImportError:
+        _polars_installed_without_pyarrow = True
+else:
+    _polars_installed_without_pyarrow = False
+
+polars_installed_without_pyarrow = pytest.mark.skipif(
+    _polars_installed_without_pyarrow=False,
+    reason="When polars is installed, requires pyarrow to be installed too",
+)
+
 
 def _pl_from_dict(data):
     import polars as pl
diff --git a/skrub/tests/test_check_input.py b/skrub/tests/test_check_input.py
index 688a95470..fcaed5edd 100644
--- a/skrub/tests/test_check_input.py
+++ b/skrub/tests/test_check_input.py
@@ -4,6 +4,7 @@
 
 from skrub import _dataframe as sbd
 from skrub._check_input import CheckInputDataFrame
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 def test_good_input(df_module):
@@ -38,6 +39,7 @@ def test_input_is_an_array():
         check.fit_transform(np.ones((2,)))
 
 
+@polars_installed_without_pyarrow
 def test_wrong_dataframe_library_in_transform():
     pl = pytest.importorskip("polars")
     df = pl.DataFrame({"a": [0, 1], "b": [10, 20]})
diff --git a/skrub/tests/test_column_associations.py b/skrub/tests/test_column_associations.py
index fed6f9f20..2bd23e86e 100644
--- a/skrub/tests/test_column_associations.py
+++ b/skrub/tests/test_column_associations.py
@@ -5,8 +5,10 @@
 
 from skrub import _dataframe as sbd
 from skrub import column_associations
+from skrub.conftest import polars_installed_without_pyarrow
 
 
+@polars_installed_without_pyarrow
 def test_column_associations(df_module):
     x = (np.ones((7, 3)) * np.arange(3)).ravel()
     y = 2 - 3 * x
@@ -26,6 +28,7 @@ def test_column_associations(df_module):
     )
 
 
+@polars_installed_without_pyarrow
 def test_infinite(df_module):
     # non-regression test for https://github.com/skrub-data/skrub/issues/1133
     # (column associations would raise an exception on low-cardinality float
diff --git a/skrub/tests/test_fuzzy_join.py b/skrub/tests/test_fuzzy_join.py
index 804be1115..a20e88bc3 100644
--- a/skrub/tests/test_fuzzy_join.py
+++ b/skrub/tests/test_fuzzy_join.py
@@ -8,6 +8,7 @@
 from skrub import ToDatetime, _join_utils, fuzzy_join
 from skrub import selectors as s
 from skrub._dataframe import _common as ns
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 @pytest.mark.parametrize(
@@ -237,6 +238,7 @@ def test_numerical_column(df_module):
     assert ns.shape(fj_num3) == (2, n_cols)
 
 
+@polars_installed_without_pyarrow
 def test_datetime_column(df_module):
     """
     Testing that ``fuzzy_join`` works with datetime columns.
@@ -292,6 +294,7 @@ def to_dt(lst):
     assert ns.shape(fj_time3) == (2, n_cols)
 
 
+@polars_installed_without_pyarrow
 def test_mixed_joins(df_module):
     """
     Test fuzzy joining on mixed and multiple column types.
diff --git a/skrub/tests/test_join_utils.py b/skrub/tests/test_join_utils.py
index ad169fa7d..771f11055 100644
--- a/skrub/tests/test_join_utils.py
+++ b/skrub/tests/test_join_utils.py
@@ -6,6 +6,7 @@
 
 from skrub import _dataframe as sbd
 from skrub import _join_utils
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 @pytest.mark.parametrize(
@@ -173,6 +174,7 @@ def test_left_join_wrong_right_type(df_module, left):
         )
 
 
+@polars_installed_without_pyarrow
 def test_left_join_types_not_equal(df_module, left):
     try:
         import polars as pl
diff --git a/skrub/tests/test_to_datetime.py b/skrub/tests/test_to_datetime.py
index e0c97e77f..d4ce9e74b 100644
--- a/skrub/tests/test_to_datetime.py
+++ b/skrub/tests/test_to_datetime.py
@@ -16,6 +16,7 @@
     _get_time_zone,
     to_datetime,
 )
+from skrub.conftest import polars_installed_without_pyarrow
 
 ISO = "%Y-%m-%dT%H:%M:%S"
 
@@ -44,6 +45,7 @@ def datetime_col(df_module):
     return sbd.col(df_module.example_dataframe, "datetime-col")
 
 
+@polars_installed_without_pyarrow
 @pytest.mark.parametrize(
     "format",
     [
@@ -85,6 +87,7 @@ def test_datetime_to_datetime(datetime_col):
     assert encoder.format_ is None
 
 
+@polars_installed_without_pyarrow
 def test_rejected_columns(df_module):
     with pytest.raises(ValueError, match=".*does not contain strings"):
         ToDatetime().fit_transform(sbd.col(df_module.example_dataframe, "float-col"))
@@ -96,6 +99,7 @@ def test_rejected_columns(df_module):
         )
 
 
+@polars_installed_without_pyarrow
 def test_transform_failures(datetime_col, df_module):
     encoder = ToDatetime().fit(strftime(datetime_col, ISO))
     test_col = df_module.make_column(
@@ -106,6 +110,7 @@ def test_transform_failures(datetime_col, df_module):
     assert sbd.to_list(sbd.fill_nulls(strftime(transformed, ISO), "????")) == expected
 
 
+@polars_installed_without_pyarrow
 def test_mixed_offsets(df_module):
     s = df_module.make_column(
         "when", ["2020-01-02T08:00:01+02:00", "2020-01-02T08:00:01+04:00"]
diff --git a/skrub/tests/test_to_float32.py b/skrub/tests/test_to_float32.py
index b9054a77e..ba923c8f9 100644
--- a/skrub/tests/test_to_float32.py
+++ b/skrub/tests/test_to_float32.py
@@ -6,6 +6,7 @@
 from skrub._to_categorical import ToCategorical
 from skrub._to_datetime import ToDatetime
 from skrub._to_float32 import ToFloat32
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 def is_float32(df_module, column):
@@ -30,6 +31,7 @@ def test_to_float_32(values, df_module):
     assert is_float32(df_module, out)
 
 
+@polars_installed_without_pyarrow
 def test_rejected_columns(df_module):
     columns = [
         df_module.make_column("c", ["1", "2", "hello"]),
diff --git a/skrub/tests/test_to_str.py b/skrub/tests/test_to_str.py
index d82a97204..9b9140159 100644
--- a/skrub/tests/test_to_str.py
+++ b/skrub/tests/test_to_str.py
@@ -6,6 +6,7 @@
 from skrub._apply_to_cols import RejectColumn
 from skrub._to_datetime import ToDatetime
 from skrub._to_str import ToStr
+from skrub.conftest import polars_installed_without_pyarrow
 
 
 def test_to_str(df_module):
@@ -26,6 +27,7 @@ def test_to_str(df_module):
     df_module.assert_column_equal(sbd.is_null(out), sbd.is_null(expected))
 
 
+@polars_installed_without_pyarrow
 def test_rejected_columns(df_module):
     columns = [
         ToDatetime().fit_transform(df_module.make_column("", ["2020-02-02"])),