Add ggplot.layer_data to the public API

plotnine/ggplot.py

@@ -47,6 +47,7 @@
 if TYPE_CHECKING:
     from typing import Protocol
 
+    import pandas as pd
     from matplotlib.axes import Axes
     from matplotlib.figure import Figure
     from typing_extensions import Self
@@ -771,6 +772,25 @@ def save(
         with plot_context(self).rc_context:
             sv.figure.savefig(**sv.kwargs)
 
+    def layer_data(self, i: int = 0) -> pd.DataFrame:
+        """
+        Return the data used to draw a specific plot layer
+
+        Parameters
+        ----------
+        i :
+            Index of the layer to retrieve, starting from 0.
+
+        Returns
+        -------
+        pd.DataFrame
+            Data used by the specified layer after all transformations,
+            statistics, and position adjustments have been applied.
+        """
+        p = deepcopy(self)
+        p._build()
+        return p.layers.data[i]
+
 
 ggsave = ggplot.save
 

tests/conftest.py

@@ -218,27 +218,6 @@ def __exit__(self, exc_type, exc_value, exc_traceback):
         warnings.resetwarnings()
 
 
-def layer_data(p, i=0):
-    """
-    Return layer information used to draw the plot
-
-    Parameters
-    ----------
-    p : ggplot
-        ggplot object
-    i : int
-        Layer number
-
-    Returns
-    -------
-    out : dataframe
-        Layer information
-    """
-    p = deepcopy(p)
-    p._build()
-    return p.layers.data[i]
-
-
 def composition_equals(cmp: Compose, name: str) -> bool:
     """
     Compare plot composition to image determined by `right`

tests/test_geom_bar_col_histogram.py

@@ -13,8 +13,6 @@
 )
 from plotnine.stats.binning import freedman_diaconis_bins
 
-from .conftest import layer_data
-
 n = 10  # Some even number greater than 2
 
 # ladder: 0 1 times, 1 2 times, 2 3 times, ...
@@ -60,8 +58,8 @@ def test_histogram_count():
 def test_scale_transformed_breaks():
     data = pd.DataFrame({"x": np.repeat(range(1, 5), range(1, 5))})
     p = ggplot(data, aes("x")) + geom_histogram(breaks=[1, 2.5, 4])
-    out1 = layer_data(p)
-    out2 = layer_data(p + scale_x_sqrt())
+    out1 = p.layer_data()
+    out2 = (p + scale_x_sqrt()).layer_data()
     np.testing.assert_allclose(out1.xmin, [1, 2.5])
     np.testing.assert_allclose(out2.xmin, np.sqrt([1, 2.5]))
 

tests/test_geom_bin_2d.py

@@ -3,8 +3,6 @@
 
 from plotnine import aes, geom_bin_2d, ggplot, scale_x_log10
 
-from .conftest import layer_data
-
 n = 20  # Make even for best results
 reps = np.hstack(
     [np.arange(int(np.ceil(n / 2))), np.arange(int(np.ceil(n // 2)))[::-1]]
@@ -34,7 +32,7 @@ def test_scale_transformed_breaks():
     p = ggplot(data, aes("x", "y")) + geom_bin_2d(
         breaks=([5, 50, 500], [0.5, 1.5, 2.5])
     )
-    out1 = layer_data(p)
-    out2 = layer_data(p + scale_x_log10())
+    out1 = p.layer_data()
+    out2 = (p + scale_x_log10()).layer_data()
     np.testing.assert_allclose(out1.xmax, [50, 500])
     np.testing.assert_allclose(out2.xmax, np.log10([50, 500]))