diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index caf38d16..b78e43e1 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -6,11 +6,6 @@ repos:
       - id: end-of-file-fixer
       - id: trailing-whitespace
 
-  - repo: https://github.com/asottile/setup-cfg-fmt
-    rev: v2.4.0
-    hooks:
-      - id: setup-cfg-fmt
-
   - repo: https://github.com/psf/black
     rev: 23.7.0
     hooks:
@@ -22,14 +17,14 @@ repos:
       - id: napari-plugin-checks
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.4.1
+    rev: v1.5.1
     hooks:
      - id: mypy
        additional_dependencies: [numpy, matplotlib]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.0.280'
+    rev: 'v0.0.285'
     hooks:
       - id: ruff
 
diff --git a/baseline/test_feature_histogram2.png b/baseline/test_feature_histogram2.png
new file mode 100644
index 00000000..b7bb19e0
Binary files /dev/null and b/baseline/test_feature_histogram2.png differ
diff --git a/docs/changelog.rst b/docs/changelog.rst
index 103cd80e..6f77e0c3 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -1,5 +1,23 @@
 Changelog
 =========
+1.1.0
+-----
+Additions
+~~~~~~~~~
+- Added a widget to draw a histogram of features.
+
+Changes
+~~~~~~~
+- The slice widget is now limited to slicing along the x/y dimensions. Support
+  for slicing along z has been removed for now to make the code simpler.
+- The slice widget now uses a slider to select the slice value.
+
+Bug fixes
+~~~~~~~~~
+- Fixed creating 1D slices of 2D images.
+- Removed the limitation that only the first 99 indices could be sliced using
+  the slice widget.
+
 1.0.2
 -----
 Bug fixes
diff --git a/docs/user_guide.rst b/docs/user_guide.rst
index 0872e540..fbd48db1 100644
--- a/docs/user_guide.rst
+++ b/docs/user_guide.rst
@@ -30,6 +30,7 @@ These widgets plot the data stored in the ``.features`` attribute of individual
 Currently available are:
 
 - 2D scatter plots of two features against each other.
+- Histograms of individual features.
 
 To use these:
 
diff --git a/setup.cfg b/setup.cfg
index 229b5777..e1fc9e73 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -55,7 +55,7 @@ docs =
     sphinx-automodapi
     sphinx-gallery
 testing =
-    napari[pyqt6-experimental]>=0.4.18
+    napari[pyqt6_experimental]>=0.4.18
     pooch
     pyqt6
     pytest
diff --git a/src/napari_matplotlib/features.py b/src/napari_matplotlib/features.py
new file mode 100644
index 00000000..34abf104
--- /dev/null
+++ b/src/napari_matplotlib/features.py
@@ -0,0 +1,9 @@
+from napari.layers import Labels, Points, Shapes, Tracks, Vectors
+
+FEATURES_LAYER_TYPES = (
+    Labels,
+    Points,
+    Shapes,
+    Tracks,
+    Vectors,
+)
diff --git a/src/napari_matplotlib/histogram.py b/src/napari_matplotlib/histogram.py
index ab098f38..66aa7acc 100644
--- a/src/napari_matplotlib/histogram.py
+++ b/src/napari_matplotlib/histogram.py
@@ -1,13 +1,15 @@
-from typing import Optional
+from typing import Any, List, Optional, Tuple
 
 import napari
 import numpy as np
-from qtpy.QtWidgets import QWidget
+import numpy.typing as npt
+from qtpy.QtWidgets import QComboBox, QLabel, QVBoxLayout, QWidget
 
 from .base import SingleAxesWidget
+from .features import FEATURES_LAYER_TYPES
 from .util import Interval
 
-__all__ = ["HistogramWidget"]
+__all__ = ["HistogramWidget", "FeaturesHistogramWidget"]
 
 _COLORS = {"r": "tab:red", "g": "tab:green", "b": "tab:blue"}
 
@@ -61,3 +63,112 @@ def draw(self) -> None:
             self.axes.hist(data.ravel(), bins=bins, label=layer.name)
 
         self.axes.legend()
+
+
+class FeaturesHistogramWidget(SingleAxesWidget):
+    """
+    Display a histogram of selected feature attached to selected layer.
+    """
+
+    n_layers_input = Interval(1, 1)
+    # All layers that have a .features attributes
+    input_layer_types = FEATURES_LAYER_TYPES
+
+    def __init__(
+        self,
+        napari_viewer: napari.viewer.Viewer,
+        parent: Optional[QWidget] = None,
+    ):
+        super().__init__(napari_viewer, parent=parent)
+
+        self.layout().addLayout(QVBoxLayout())
+        self._key_selection_widget = QComboBox()
+        self.layout().addWidget(QLabel("Key:"))
+        self.layout().addWidget(self._key_selection_widget)
+
+        self._key_selection_widget.currentTextChanged.connect(
+            self._set_axis_keys
+        )
+
+        self._update_layers(None)
+
+    @property
+    def x_axis_key(self) -> Optional[str]:
+        """Key to access x axis data from the FeaturesTable"""
+        return self._x_axis_key
+
+    @x_axis_key.setter
+    def x_axis_key(self, key: Optional[str]) -> None:
+        self._x_axis_key = key
+        self._draw()
+
+    def _set_axis_keys(self, x_axis_key: str) -> None:
+        """Set both axis keys and then redraw the plot"""
+        self._x_axis_key = x_axis_key
+        self._draw()
+
+    def _get_valid_axis_keys(self) -> List[str]:
+        """
+        Get the valid axis keys from the layer FeatureTable.
+
+        Returns
+        -------
+        axis_keys : List[str]
+            The valid axis keys in the FeatureTable. If the table is empty
+            or there isn't a table, returns an empty list.
+        """
+        if len(self.layers) == 0 or not (hasattr(self.layers[0], "features")):
+            return []
+        else:
+            return self.layers[0].features.keys()
+
+    def _get_data(self) -> Tuple[Optional[npt.NDArray[Any]], str]:
+        """Get the plot data.
+
+        Returns
+        -------
+        data : List[np.ndarray]
+            List contains X and Y columns from the FeatureTable. Returns
+            an empty array if nothing to plot.
+        x_axis_name : str
+            The title to display on the x axis. Returns
+            an empty string if nothing to plot.
+        """
+        if not hasattr(self.layers[0], "features"):
+            # if the selected layer doesn't have a featuretable,
+            # skip draw
+            return None, ""
+
+        feature_table = self.layers[0].features
+
+        if (len(feature_table) == 0) or (self.x_axis_key is None):
+            return None, ""
+
+        data = feature_table[self.x_axis_key]
+        x_axis_name = self.x_axis_key.replace("_", " ")
+
+        return data, x_axis_name
+
+    def on_update_layers(self) -> None:
+        """
+        Called when the layer selection changes by ``self.update_layers()``.
+        """
+        # reset the axis keys
+        self._x_axis_key = None
+
+        # Clear combobox
+        self._key_selection_widget.clear()
+        self._key_selection_widget.addItems(self._get_valid_axis_keys())
+
+    def draw(self) -> None:
+        """Clear the axes and histogram the currently selected layer/slice."""
+        data, x_axis_name = self._get_data()
+
+        if data is None:
+            return
+
+        self.axes.hist(data, bins=50, edgecolor="white", linewidth=0.3)
+
+        # set ax labels
+        self.axes.set_xlabel(x_axis_name)
+        self.axes.set_ylabel("Counts [#]")
diff --git a/src/napari_matplotlib/napari.yaml b/src/napari_matplotlib/napari.yaml
index b736592b..71af0ca6 100644
--- a/src/napari_matplotlib/napari.yaml
+++ b/src/napari_matplotlib/napari.yaml
@@ -14,6 +14,10 @@ contributions:
       python_name: napari_matplotlib:FeaturesScatterWidget
       title: Make a scatter plot of layer features
 
+    - id: napari-matplotlib.features_histogram
+      python_name: napari_matplotlib:FeaturesHistogramWidget
+      title: Plot feature histograms
+
     - id: napari-matplotlib.slice
       python_name: napari_matplotlib:SliceWidget
       title: Plot a 1D slice
@@ -28,5 +32,8 @@ contributions:
     - command: napari-matplotlib.features_scatter
       display_name: FeaturesScatter
 
+    - command: napari-matplotlib.features_histogram
+      display_name: FeaturesHistogram
+
     - command: napari-matplotlib.slice
       display_name: 1D slice
diff --git a/src/napari_matplotlib/scatter.py b/src/napari_matplotlib/scatter.py
index db86c7f3..a4148bd2 100644
--- a/src/napari_matplotlib/scatter.py
+++ b/src/napari_matplotlib/scatter.py
@@ -5,6 +5,7 @@
 from qtpy.QtWidgets import QComboBox, QLabel, QVBoxLayout, QWidget
 
 from .base import SingleAxesWidget
+from .features import FEATURES_LAYER_TYPES
 from .util import Interval
 
 __all__ = ["ScatterBaseWidget", "ScatterWidget", "FeaturesScatterWidget"]
@@ -94,13 +95,7 @@ class FeaturesScatterWidget(ScatterBaseWidget):
 
     n_layers_input = Interval(1, 1)
     # All layers that have a .features attributes
-    input_layer_types = (
-        napari.layers.Labels,
-        napari.layers.Points,
-        napari.layers.Shapes,
-        napari.layers.Tracks,
-        napari.layers.Vectors,
-    )
+    input_layer_types = FEATURES_LAYER_TYPES
 
     def __init__(
         self,
diff --git a/src/napari_matplotlib/slice.py b/src/napari_matplotlib/slice.py
index e3aa80b2..393f2e45 100644
--- a/src/napari_matplotlib/slice.py
+++ b/src/napari_matplotlib/slice.py
@@ -1,19 +1,23 @@
-from typing import Any, Dict, Optional, Tuple
+from typing import Any, List, Optional, Tuple
 
 import matplotlib.ticker as mticker
 import napari
 import numpy as np
 import numpy.typing as npt
-from qtpy.QtWidgets import QComboBox, QHBoxLayout, QLabel, QSpinBox, QWidget
+from qtpy.QtCore import Qt
+from qtpy.QtWidgets import (
+    QComboBox,
+    QLabel,
+    QSlider,
+    QVBoxLayout,
+    QWidget,
+)
 
 from .base import SingleAxesWidget
 from .util import Interval
 
 __all__ = ["SliceWidget"]
 
-_dims_sel = ["x", "y"]
-_dims = ["x", "y", "z"]
-
 
 class SliceWidget(SingleAxesWidget):
     """
@@ -31,28 +35,46 @@ def __init__(
         # Setup figure/axes
         super().__init__(napari_viewer, parent=parent)
 
-        button_layout = QHBoxLayout()
-        self.layout().addLayout(button_layout)
-
         self.dim_selector = QComboBox()
+        self.dim_selector.addItems(["x", "y"])
+
+        self.slice_selector = QSlider(orientation=Qt.Orientation.Horizontal)
+
+        # Create widget layout
+        button_layout = QVBoxLayout()
         button_layout.addWidget(QLabel("Slice axis:"))
         button_layout.addWidget(self.dim_selector)
-        self.dim_selector.addItems(_dims)
-
-        self.slice_selectors = {}
-        for d in _dims_sel:
-            self.slice_selectors[d] = QSpinBox()
-            button_layout.addWidget(QLabel(f"{d}:"))
-            button_layout.addWidget(self.slice_selectors[d])
+        button_layout.addWidget(self.slice_selector)
+        self.layout().addLayout(button_layout)
 
         # Setup callbacks
-        # Re-draw when any of the combon/spin boxes are updated
+        # Re-draw when any of the combo/slider is updated
         self.dim_selector.currentTextChanged.connect(self._draw)
-        for d in _dims_sel:
-            self.slice_selectors[d].textChanged.connect(self._draw)
+        self.slice_selector.valueChanged.connect(self._draw)
 
         self._update_layers(None)
 
+    def on_update_layers(self) -> None:
+        """
+        Called when layer selection is updated.
+        """
+        if not len(self.layers):
+            return
+        if self.current_dim_name == "x":
+            max = self._layer.data.shape[-2]
+        elif self.current_dim_name == "y":
+            max = self._layer.data.shape[-1]
+        else:
+            raise RuntimeError("dim name must be x or y")
+        self.slice_selector.setRange(0, max - 1)
+
+    @property
+    def _slice_width(self) -> int:
+        """
+        Width of the slice being plotted.
+        """
+        return self._layer.data.shape[self.current_dim_index]
+
     @property
     def _layer(self) -> napari.layers.Layer:
         """
@@ -61,7 +83,7 @@ def _layer(self) -> napari.layers.Layer:
         return self.layers[0]
 
     @property
-    def current_dim(self) -> str:
+    def current_dim_name(self) -> str:
         """
         Currently selected slice dimension.
         """
@@ -74,36 +96,40 @@ def current_dim_index(self) -> int:
         """
         # Note the reversed list because in napari the z-axis is the first
         # numpy axis
-        return _dims[::-1].index(self.current_dim)
+        return self._dim_names.index(self.current_dim_name)
 
     @property
-    def _selector_values(self) -> Dict[str, int]:
+    def _dim_names(self) -> List[str]:
         """
-        Values of the slice selectors.
+        List of dimension names. This is a property as it varies depending on the
+        dimensionality of the currently selected data.
         """
-        return {d: self.slice_selectors[d].value() for d in _dims_sel}
+        if self._layer.data.ndim == 2:
+            return ["y", "x"]
+        elif self._layer.data.ndim == 3:
+            return ["z", "y", "x"]
+        else:
+            raise RuntimeError("Don't know how to handle ndim != 2 or 3")
 
     def _get_xy(self) -> Tuple[npt.NDArray[Any], npt.NDArray[Any]]:
         """
         Get data for plotting.
         """
-        x = np.arange(self._layer.data.shape[self.current_dim_index])
-
-        vals = self._selector_values
-        vals.update({"z": self.current_z})
+        val = self.slice_selector.value()
 
         slices = []
-        for d in _dims:
-            if d == self.current_dim:
+        for dim_name in self._dim_names:
+            if dim_name == self.current_dim_name:
                 # Select all data along this axis
                 slices.append(slice(None))
+            elif dim_name == "z":
+                # Only select the currently viewed z-index
+                slices.append(slice(self.current_z, self.current_z + 1))
             else:
                 # Select specific index
-                val = vals[d]
                 slices.append(slice(val, val + 1))
 
-        # Reverse since z is the first axis in napari
-        slices = slices[::-1]
+        x = np.arange(self._slice_width)
         y = self._layer.data[tuple(slices)].ravel()
 
         return x, y
@@ -115,7 +141,7 @@ def draw(self) -> None:
         x, y = self._get_xy()
 
         self.axes.plot(x, y)
-        self.axes.set_xlabel(self.current_dim)
+        self.axes.set_xlabel(self.current_dim_name)
         self.axes.set_title(self._layer.name)
         # Make sure all ticks lie on integer values
         self.axes.xaxis.set_major_locator(
diff --git a/src/napari_matplotlib/tests/baseline/test_feature_histogram.png b/src/napari_matplotlib/tests/baseline/test_feature_histogram.png
new file mode 100644
index 00000000..1892af44
Binary files /dev/null and b/src/napari_matplotlib/tests/baseline/test_feature_histogram.png differ
diff --git a/src/napari_matplotlib/tests/baseline/test_feature_histogram2.png b/src/napari_matplotlib/tests/baseline/test_feature_histogram2.png
new file mode 100644
index 00000000..b7bb19e0
Binary files /dev/null and b/src/napari_matplotlib/tests/baseline/test_feature_histogram2.png differ
diff --git a/src/napari_matplotlib/tests/baseline/test_slice_2D.png b/src/napari_matplotlib/tests/baseline/test_slice_2D.png
index 639f25b8..ee3ce3b6 100644
Binary files a/src/napari_matplotlib/tests/baseline/test_slice_2D.png and b/src/napari_matplotlib/tests/baseline/test_slice_2D.png differ
diff --git a/src/napari_matplotlib/tests/baseline/test_slice_3D.png b/src/napari_matplotlib/tests/baseline/test_slice_3D.png
index 43c8c3b6..c30211da 100644
Binary files a/src/napari_matplotlib/tests/baseline/test_slice_3D.png and b/src/napari_matplotlib/tests/baseline/test_slice_3D.png differ
diff --git a/src/napari_matplotlib/tests/test_histogram.py b/src/napari_matplotlib/tests/test_histogram.py
index 4d170014..006c042f 100644
--- a/src/napari_matplotlib/tests/test_histogram.py
+++ b/src/napari_matplotlib/tests/test_histogram.py
@@ -1,8 +1,13 @@
 from copy import deepcopy
 
+import numpy as np
 import pytest
 
-from napari_matplotlib import HistogramWidget
+from napari_matplotlib import FeaturesHistogramWidget, HistogramWidget
+from napari_matplotlib.tests.helpers import (
+    assert_figures_equal,
+    assert_figures_not_equal,
+)
 
 
 @pytest.mark.mpl_image_compare
@@ -28,3 +33,90 @@ def test_histogram_3D(make_napari_viewer, brain_data):
     # Need to return a copy, as original figure is too eagerley garbage
     # collected by the widget
     return deepcopy(fig)
+
+
+def test_feature_histogram(make_napari_viewer):
+    n_points = 1000
+    random_points = np.random.random((n_points, 3)) * 10
+    feature1 = np.random.random(n_points)
+    feature2 = np.random.normal(size=n_points)
+
+    viewer = make_napari_viewer()
+    viewer.add_points(
+        random_points,
+        properties={"feature1": feature1, "feature2": feature2},
+        name="points1",
+    )
+    viewer.add_points(
+        random_points,
+        properties={"feature1": feature1, "feature2": feature2},
+        name="points2",
+    )
+
+    widget = FeaturesHistogramWidget(viewer)
+    viewer.window.add_dock_widget(widget)
+
+    # Check whether changing the selected key changes the plot
+    widget._set_axis_keys("feature1")
+    fig1 = deepcopy(widget.figure)
+
+    widget._set_axis_keys("feature2")
+    assert_figures_not_equal(widget.figure, fig1)
+
+    # check whether selecting a different layer produces the same plot
+    viewer.layers.selection.clear()
+    viewer.layers.selection.add(viewer.layers[1])
+    assert_figures_equal(widget.figure, fig1)
+
+
+@pytest.mark.mpl_image_compare
+def test_feature_histogram2(make_napari_viewer):
+    import numpy as np
+
+    np.random.seed(0)
+    n_points = 1000
+    random_points = np.random.random((n_points, 3)) * 10
+    feature1 = np.random.random(n_points)
+    feature2 = np.random.normal(size=n_points)
+
+    viewer = make_napari_viewer()
+    viewer.add_points(
+        random_points,
+        properties={"feature1": feature1, "feature2": feature2},
+        name="points1",
+    )
+    viewer.add_points(
+        random_points,
+        properties={"feature1": feature1, "feature2": feature2},
+        name="points2",
+    )
+
+    widget = FeaturesHistogramWidget(viewer)
+    viewer.window.add_dock_widget(widget)
+    widget._set_axis_keys("feature1")
+
+    fig = FeaturesHistogramWidget(viewer).figure
+    return deepcopy(fig)
+
+
+def test_change_layer(make_napari_viewer, brain_data, astronaut_data):
+    viewer = make_napari_viewer()
+    widget = HistogramWidget(viewer)
+
+    viewer.add_image(brain_data[0], **brain_data[1])
+    viewer.add_image(astronaut_data[0], **astronaut_data[1])
+
+    # Select first layer
+    viewer.layers.selection.clear()
+    viewer.layers.selection.add(viewer.layers[0])
+    fig1 = deepcopy(widget.figure)
+
+    # Re-selecting first layer should produce identical plot
+    viewer.layers.selection.clear()
+    viewer.layers.selection.add(viewer.layers[0])
+    assert_figures_equal(widget.figure, fig1)
+
+    # Plotting the second layer should produce a different plot
+    viewer.layers.selection.clear()
+    viewer.layers.selection.add(viewer.layers[1])
+    assert_figures_not_equal(widget.figure, fig1)
diff --git a/src/napari_matplotlib/tests/test_slice.py b/src/napari_matplotlib/tests/test_slice.py
index 412e71c3..368a7ded 100644
--- a/src/napari_matplotlib/tests/test_slice.py
+++ b/src/napari_matplotlib/tests/test_slice.py
@@ -9,9 +9,13 @@
 def test_slice_3D(make_napari_viewer, brain_data):
     viewer = make_napari_viewer()
     viewer.theme = "light"
-    viewer.add_image(brain_data[0], **brain_data[1])
+
+    data = brain_data[0]
+    assert data.ndim == 3, data.shape
+    viewer.add_image(data, **brain_data[1])
+
     axis = viewer.dims.last_used
-    slice_no = brain_data[0].shape[0] - 1
+    slice_no = data.shape[0] - 1
     viewer.dims.set_current_step(axis, slice_no)
     fig = SliceWidget(viewer).figure
     # Need to return a copy, as original figure is too eagerley garbage
@@ -23,8 +27,37 @@ def test_slice_3D(make_napari_viewer, brain_data):
 def test_slice_2D(make_napari_viewer, astronaut_data):
     viewer = make_napari_viewer()
     viewer.theme = "light"
-    viewer.add_image(astronaut_data[0], **astronaut_data[1])
+
+    # Take first RGB channel
+    data = astronaut_data[0][:, :, 0]
+    assert data.ndim == 2, data.shape
+    viewer.add_image(data)
+
     fig = SliceWidget(viewer).figure
     # Need to return a copy, as original figure is too eagerley garbage
     # collected by the widget
     return deepcopy(fig)
+
+
+def test_slice_axes(make_napari_viewer, astronaut_data):
+    viewer = make_napari_viewer()
+    viewer.theme = "light"
+
+    # Take first RGB channel
+    data = astronaut_data[0][:256, :, 0]
+    # Shape:
+    # x: 0 > 512
+    # y: 0 > 256
+    assert data.ndim == 2, data.shape
+    # Make sure data isn't square for later tests
+    assert data.shape[0] != data.shape[1]
+    viewer.add_image(data)
+
+    widget = SliceWidget(viewer)
+    assert widget._dim_names == ["y", "x"]
+    assert widget.current_dim_name == "x"
+    assert widget.slice_selector.value() == 0
+    assert widget.slice_selector.minimum() == 0
+    assert widget.slice_selector.maximum() == data.shape[0] - 1
+    # x/y are flipped in napari
+    assert widget._slice_width == data.shape[1]