From d8d8c3c5619ca5b2ce2dc37cf0f0e081ab8414d0 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Thu, 21 May 2020 15:49:34 +0100
Subject: [PATCH 01/19] add legend with colors if coloring by categorical

---
 pandas/plotting/_matplotlib/core.py | 25 ++++++++++++++++++++++---
 1 file changed, 22 insertions(+), 3 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index a049ac99f0e08..2d5c6ef1d089a 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -8,6 +8,7 @@
 from pandas.util._decorators import cache_readonly
 
 from pandas.core.dtypes.common import (
+    is_categorical_dtype,
     is_hashable,
     is_integer,
     is_iterator,
@@ -413,7 +414,8 @@ def _compute_plot_data(self):
         # np.ndarray before plot.
         numeric_data = numeric_data.copy()
         for col in numeric_data:
-            numeric_data[col] = np.asarray(numeric_data[col])
+            if not is_categorical_dtype(numeric_data[col]):
+                numeric_data[col] = np.asarray(numeric_data[col])
 
         self.data = numeric_data
 
@@ -965,7 +967,11 @@ def _make_plot(self):
         elif color is not None:
             c_values = color
         elif c_is_column:
-            c_values = self.data[c].values
+            if not is_categorical_dtype(self.data[c]):
+                c_values = self.data[c].values
+
+            else:
+                c_values = self.data[c].cat.codes
         else:
             c_values = c
 
@@ -983,7 +989,20 @@ def _make_plot(self):
         )
         if cb:
             cbar_label = c if c_is_column else ""
-            self._plot_colorbar(ax, label=cbar_label)
+            if not is_categorical_dtype(self.data[c]):
+                self._plot_colorbar(ax, label=cbar_label)
+            else:
+                codes = (self.data[c].cat.codes).unique()
+                handles = [
+                    self.plt.scatter(
+                        [],
+                        [],
+                        color=scatter.cmap(scatter.norm(i)),
+                        label=self.data[c].cat.categories[i],
+                    )
+                    for i in codes
+                ]
+                ax.legend(handles=handles, title=cbar_label)
 
         if label is not None:
             self._add_legend_handle(scatter, label)

From a1673136d98312f91c44e6c615acb9fd038a1b1b Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Thu, 21 May 2020 15:50:53 +0100
Subject: [PATCH 02/19] add legend with colors if coloring by categorical

---
 pandas/plotting/_matplotlib/core.py | 9 +++------
 1 file changed, 3 insertions(+), 6 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index 2d5c6ef1d089a..bfd72376dd0ba 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -993,13 +993,10 @@ def _make_plot(self):
                 self._plot_colorbar(ax, label=cbar_label)
             else:
                 codes = (self.data[c].cat.codes).unique()
+                colors = [scatter.cmap(scatter.norm(i)) for i in codes]
+                labels = [self.data[c].cat.categories[i] for i in codes]
                 handles = [
-                    self.plt.scatter(
-                        [],
-                        [],
-                        color=scatter.cmap(scatter.norm(i)),
-                        label=self.data[c].cat.categories[i],
-                    )
+                    self.plt.scatter([], [], color=colors[i], label=labels[i],)
                     for i in codes
                 ]
                 ax.legend(handles=handles, title=cbar_label)

From d10c5c12e51f7a61e343aab4ce46810750fbc47a Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Thu, 21 May 2020 15:51:14 +0100
Subject: [PATCH 03/19] add legend with colors if coloring by categorical

---
 pandas/plotting/_matplotlib/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index bfd72376dd0ba..8170063fcfc12 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -996,7 +996,7 @@ def _make_plot(self):
                 colors = [scatter.cmap(scatter.norm(i)) for i in codes]
                 labels = [self.data[c].cat.categories[i] for i in codes]
                 handles = [
-                    self.plt.scatter([], [], color=colors[i], label=labels[i],)
+                    self.plt.scatter([], [], color=colors[i], label=labels[i])
                     for i in codes
                 ]
                 ax.legend(handles=handles, title=cbar_label)

From 7294aa2e90663efe21e110e5e39894cd7aec443f Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Thu, 21 May 2020 15:53:12 +0100
Subject: [PATCH 04/19] add legend with colors if coloring by categorical

---
 pandas/plotting/_matplotlib/core.py | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index 8170063fcfc12..684e853137a12 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -993,12 +993,13 @@ def _make_plot(self):
                 self._plot_colorbar(ax, label=cbar_label)
             else:
                 codes = (self.data[c].cat.codes).unique()
-                colors = [scatter.cmap(scatter.norm(i)) for i in codes]
-                labels = [self.data[c].cat.categories[i] for i in codes]
-                handles = [
-                    self.plt.scatter([], [], color=colors[i], label=labels[i])
-                    for i in codes
-                ]
+                empty_plot = lambda i: self.plt.scatter(
+                    [],
+                    [],
+                    color=scatter.cmap(scatter.norm(i)),
+                    label=self.data[c].cat.categories[i],
+                )
+                handles = [empty_plot(i) for i in codes]
                 ax.legend(handles=handles, title=cbar_label)
 
         if label is not None:

From 50cd05f65370c60e6c0ba23880eafa6e7ca613e7 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Thu, 21 May 2020 15:53:40 +0100
Subject: [PATCH 05/19] add legend with colors if coloring by categorical

---
 pandas/plotting/_matplotlib/core.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index 684e853137a12..5b6c875ca4d35 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -992,14 +992,13 @@ def _make_plot(self):
             if not is_categorical_dtype(self.data[c]):
                 self._plot_colorbar(ax, label=cbar_label)
             else:
-                codes = (self.data[c].cat.codes).unique()
                 empty_plot = lambda i: self.plt.scatter(
                     [],
                     [],
                     color=scatter.cmap(scatter.norm(i)),
                     label=self.data[c].cat.categories[i],
                 )
-                handles = [empty_plot(i) for i in codes]
+                handles = [empty_plot(i) for i in self.data[c].cat.codes.unique()]
                 ax.legend(handles=handles, title=cbar_label)
 
         if label is not None:

From 4579142391bde091db732342f2fc7cfd42263759 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Thu, 21 May 2020 15:54:24 +0100
Subject: [PATCH 06/19] add legend with colors if coloring by categorical

---
 pandas/plotting/_matplotlib/core.py | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index 5b6c875ca4d35..dba82c403c79c 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -992,13 +992,15 @@ def _make_plot(self):
             if not is_categorical_dtype(self.data[c]):
                 self._plot_colorbar(ax, label=cbar_label)
             else:
-                empty_plot = lambda i: self.plt.scatter(
-                    [],
-                    [],
-                    color=scatter.cmap(scatter.norm(i)),
-                    label=self.data[c].cat.categories[i],
-                )
-                handles = [empty_plot(i) for i in self.data[c].cat.codes.unique()]
+                handles = [
+                    self.plt.scatter(
+                        [],
+                        [],
+                        color=scatter.cmap(scatter.norm(i)),
+                        label=self.data[c].cat.categories[i],
+                    )
+                    for i in self.data[c].cat.codes.unique()
+                ]
                 ax.legend(handles=handles, title=cbar_label)
 
         if label is not None:

From 6d3fe9e36c7bc5844f963a3c1bf1b522ec8786a8 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Thu, 21 May 2020 16:14:00 +0100
Subject: [PATCH 07/19] add test

---
 pandas/tests/plotting/test_frame.py | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index c84a09f21f46b..1b40413b58ef0 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -1190,6 +1190,16 @@ def test_scatterplot_object_data(self):
         _check_plot_works(df.plot.scatter, x="a", y="b")
         _check_plot_works(df.plot.scatter, x=0, y=1)
 
+    def test_scatterplot_color_by_categorical(self):
+        df = pd.DataFrame(
+            [[5.1, 3.5], [4.9, 3.0], [7.0, 3.2], [6.4, 3.2], [5.9, 3.0]],
+            columns=["length", "width"],
+        )
+        df["species"] = pd.Categorical(
+            ["setosa", "setosa", "virginica", "virginica", "versicolor"]
+        )
+        _check_plot_works(df.plot.scatter, x=0, y=1, c="species")
+
     @pytest.mark.slow
     def test_if_scatterplot_colorbar_affects_xaxis_visibility(self):
         # addressing issue #10611, to ensure colobar does not

From 3846804120886849c6dcff6a2712304502f1223b Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Thu, 21 May 2020 16:16:47 +0100
Subject: [PATCH 08/19] revert empty line

---
 pandas/plotting/_matplotlib/core.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index dba82c403c79c..7f22188009dbc 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -969,7 +969,6 @@ def _make_plot(self):
         elif c_is_column:
             if not is_categorical_dtype(self.data[c]):
                 c_values = self.data[c].values
-
             else:
                 c_values = self.data[c].cat.codes
         else:

From ef4b03deabef2aa6f129b3e97e4094b31b3c21c2 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Fri, 22 May 2020 11:43:57 +0100
Subject: [PATCH 09/19] discrete colorbar in case of ordered categorical

---
 pandas/plotting/_matplotlib/core.py | 71 ++++++++++++++++++++++-------
 1 file changed, 55 insertions(+), 16 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index 7f22188009dbc..dedc5226591e6 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -913,7 +913,7 @@ def _plot_colorbar(self, ax, **kwds):
 
         if _mpl_ge_3_0_0():
             # The workaround below is no longer necessary.
-            return
+            return cbar
 
         points = ax.get_position().get_points()
         cbar_points = cbar.ax.get_position().get_points()
@@ -931,6 +931,8 @@ def _plot_colorbar(self, ax, **kwds):
         # print(points[1, 1] - points[0, 1])
         # print(cbar_points[1, 1] - cbar_points[0, 1])
 
+        return cbar
+
 
 class ScatterPlot(PlanePlot):
     _kind = "scatter"
@@ -953,6 +955,12 @@ def _make_plot(self):
 
         c_is_column = is_hashable(c) and c in self.data.columns
 
+        color_by_categorical = c_is_column and is_categorical_dtype(self.data[c])
+        color_by_ordered_categorical = color_by_categorical and self.data[c].cat.ordered
+        color_by_unordered_categorical = (
+            color_by_categorical and not self.data[c].cat.ordered
+        )
+
         # plot a colorbar only if a colormap is provided or necessary
         cb = self.kwds.pop("colorbar", self.colormap or c_is_column)
 
@@ -967,40 +975,71 @@ def _make_plot(self):
         elif color is not None:
             c_values = color
         elif c_is_column:
-            if not is_categorical_dtype(self.data[c]):
+            if not color_by_categorical:
                 c_values = self.data[c].values
             else:
                 c_values = self.data[c].cat.codes
+
         else:
             c_values = c
 
+        if color_by_categorical:
+            from matplotlib import colors
+
+            n_cats = len(self.data[c].cat.categories)
+            cmap = colors.ListedColormap([cmap(i) for i in range((cmap.N))])
+            bounds = np.linspace(0, n_cats, n_cats + 1)
+            ticks = np.linspace(0.5, n_cats - 0.5, n_cats)
+            norm = colors.BoundaryNorm(bounds, cmap.N)
+
         if self.legend and hasattr(self, "label"):
             label = self.label
         else:
             label = None
-        scatter = ax.scatter(
-            data[x].values,
-            data[y].values,
-            c=c_values,
-            label=label,
-            cmap=cmap,
-            **self.kwds,
-        )
+        if color_by_categorical:
+            scatter = ax.scatter(
+                data[x].values,
+                data[y].values,
+                c=c_values,
+                label=label,
+                cmap=cmap,
+                norm=norm,
+                **self.kwds,
+            )
+        else:
+            scatter = ax.scatter(
+                data[x].values,
+                data[y].values,
+                c=c_values,
+                label=label,
+                cmap=cmap,
+                **self.kwds,
+            )
         if cb:
             cbar_label = c if c_is_column else ""
-            if not is_categorical_dtype(self.data[c]):
-                self._plot_colorbar(ax, label=cbar_label)
-            else:
+            if color_by_unordered_categorical:
                 handles = [
                     self.plt.scatter(
-                        [],
-                        [],
+                        *([], []),
                         color=scatter.cmap(scatter.norm(i)),
                         label=self.data[c].cat.categories[i],
+                        norm=norm,
                     )
-                    for i in self.data[c].cat.codes.unique()
+                    for i in range(n_cats)
                 ]
                 ax.legend(handles=handles, title=cbar_label)
+            elif color_by_ordered_categorical:
+                cbar = self._plot_colorbar(
+                    ax,
+                    label=cbar_label,
+                    cmap=cmap,
+                    boundaries=bounds,
+                    ticks=ticks,
+                    norm=norm,
+                )
+                cbar.ax.set_yticklabels(self.data[c].cat.categories)
+            else:
+                self._plot_colorbar(ax, label=cbar_label)
 
         if label is not None:
             self._add_legend_handle(scatter, label)

From cf218f7d4d26db3e8ab50b5d1dacf1c2e782266a Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Fri, 22 May 2020 12:06:04 +0100
Subject: [PATCH 10/19] cleanup

---
 pandas/plotting/_matplotlib/core.py | 47 +++++++++++------------------
 1 file changed, 17 insertions(+), 30 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index dedc5226591e6..8356edcbf5ab0 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -991,30 +991,24 @@ def _make_plot(self):
             bounds = np.linspace(0, n_cats, n_cats + 1)
             ticks = np.linspace(0.5, n_cats - 0.5, n_cats)
             norm = colors.BoundaryNorm(bounds, cmap.N)
+            yticklabels = self.data[c].cat.categories
+        else:
+            ticks = None
+            norm = None
 
         if self.legend and hasattr(self, "label"):
             label = self.label
         else:
             label = None
-        if color_by_categorical:
-            scatter = ax.scatter(
-                data[x].values,
-                data[y].values,
-                c=c_values,
-                label=label,
-                cmap=cmap,
-                norm=norm,
-                **self.kwds,
-            )
-        else:
-            scatter = ax.scatter(
-                data[x].values,
-                data[y].values,
-                c=c_values,
-                label=label,
-                cmap=cmap,
-                **self.kwds,
-            )
+        scatter = ax.scatter(
+            data[x].values,
+            data[y].values,
+            c=c_values,
+            label=label,
+            cmap=cmap,
+            norm=norm,
+            **self.kwds,
+        )
         if cb:
             cbar_label = c if c_is_column else ""
             if color_by_unordered_categorical:
@@ -1028,18 +1022,11 @@ def _make_plot(self):
                     for i in range(n_cats)
                 ]
                 ax.legend(handles=handles, title=cbar_label)
-            elif color_by_ordered_categorical:
-                cbar = self._plot_colorbar(
-                    ax,
-                    label=cbar_label,
-                    cmap=cmap,
-                    boundaries=bounds,
-                    ticks=ticks,
-                    norm=norm,
-                )
-                cbar.ax.set_yticklabels(self.data[c].cat.categories)
             else:
-                self._plot_colorbar(ax, label=cbar_label)
+                cbar = self._plot_colorbar(ax, label=cbar_label,)
+                if color_by_ordered_categorical:
+                    cbar.set_ticks(ticks)
+                    cbar.ax.set_yticklabels(yticklabels)
 
         if label is not None:
             self._add_legend_handle(scatter, label)

From 7aae1648efe4c3dd43d92afbf5a6e07d8c62de3b Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Fri, 22 May 2020 12:06:20 +0100
Subject: [PATCH 11/19] cleanup

---
 pandas/plotting/_matplotlib/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index 8356edcbf5ab0..bc054ada08b1e 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -1023,7 +1023,7 @@ def _make_plot(self):
                 ]
                 ax.legend(handles=handles, title=cbar_label)
             else:
-                cbar = self._plot_colorbar(ax, label=cbar_label,)
+                cbar = self._plot_colorbar(ax, label=cbar_label)
                 if color_by_ordered_categorical:
                     cbar.set_ticks(ticks)
                     cbar.ax.set_yticklabels(yticklabels)

From 0ab903d12ca1bb905a35da6cba333d1d7a4d1609 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Fri, 22 May 2020 13:49:42 +0100
Subject: [PATCH 12/19] plot colorbar in both cases

---
 pandas/plotting/_matplotlib/core.py | 34 ++++++-----------------------
 1 file changed, 7 insertions(+), 27 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index bc054ada08b1e..9c29e8d336f57 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -956,10 +956,6 @@ def _make_plot(self):
         c_is_column = is_hashable(c) and c in self.data.columns
 
         color_by_categorical = c_is_column and is_categorical_dtype(self.data[c])
-        color_by_ordered_categorical = color_by_categorical and self.data[c].cat.ordered
-        color_by_unordered_categorical = (
-            color_by_categorical and not self.data[c].cat.ordered
-        )
 
         # plot a colorbar only if a colormap is provided or necessary
         cb = self.kwds.pop("colorbar", self.colormap or c_is_column)
@@ -975,11 +971,10 @@ def _make_plot(self):
         elif color is not None:
             c_values = color
         elif c_is_column:
-            if not color_by_categorical:
-                c_values = self.data[c].values
-            else:
+            if color_by_categorical:
                 c_values = self.data[c].cat.codes
-
+            else:
+                c_values = self.data[c].values
         else:
             c_values = c
 
@@ -989,11 +984,8 @@ def _make_plot(self):
             n_cats = len(self.data[c].cat.categories)
             cmap = colors.ListedColormap([cmap(i) for i in range((cmap.N))])
             bounds = np.linspace(0, n_cats, n_cats + 1)
-            ticks = np.linspace(0.5, n_cats - 0.5, n_cats)
             norm = colors.BoundaryNorm(bounds, cmap.N)
-            yticklabels = self.data[c].cat.categories
         else:
-            ticks = None
             norm = None
 
         if self.legend and hasattr(self, "label"):
@@ -1011,22 +1003,10 @@ def _make_plot(self):
         )
         if cb:
             cbar_label = c if c_is_column else ""
-            if color_by_unordered_categorical:
-                handles = [
-                    self.plt.scatter(
-                        *([], []),
-                        color=scatter.cmap(scatter.norm(i)),
-                        label=self.data[c].cat.categories[i],
-                        norm=norm,
-                    )
-                    for i in range(n_cats)
-                ]
-                ax.legend(handles=handles, title=cbar_label)
-            else:
-                cbar = self._plot_colorbar(ax, label=cbar_label)
-                if color_by_ordered_categorical:
-                    cbar.set_ticks(ticks)
-                    cbar.ax.set_yticklabels(yticklabels)
+            cbar = self._plot_colorbar(ax, label=cbar_label)
+            if color_by_categorical:
+                cbar.set_ticks(np.linspace(0.5, n_cats - 0.5, n_cats))
+                cbar.ax.set_yticklabels(self.data[c].cat.categories)
 
         if label is not None:
             self._add_legend_handle(scatter, label)

From b93ddf1fefa28ed36b8531ecc9540ad50446eada Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Fri, 22 May 2020 14:08:49 +0100
Subject: [PATCH 13/19] update test

---
 pandas/tests/plotting/test_frame.py | 29 ++++++++++++++++++++++++++---
 1 file changed, 26 insertions(+), 3 deletions(-)

diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 1b40413b58ef0..c48e738aa422e 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -1190,15 +1190,38 @@ def test_scatterplot_object_data(self):
         _check_plot_works(df.plot.scatter, x="a", y="b")
         _check_plot_works(df.plot.scatter, x=0, y=1)
 
-    def test_scatterplot_color_by_categorical(self):
+    @pytest.mark.parametrize("ordered", [True, False])
+    @pytest.mark.parametrize(
+        "categories",
+        (["setosa", "versicolor", "virginica"], ["versicolor", "virginica", "setosa"]),
+    )
+    def test_scatterplot_color_by_categorical(self, ordered, categories):
         df = pd.DataFrame(
             [[5.1, 3.5], [4.9, 3.0], [7.0, 3.2], [6.4, 3.2], [5.9, 3.0]],
             columns=["length", "width"],
         )
         df["species"] = pd.Categorical(
-            ["setosa", "setosa", "virginica", "virginica", "versicolor"]
+            ["setosa", "setosa", "virginica", "virginica", "versicolor"],
+            ordered=ordered,
+            categories=categories,
+        )
+        ax = df.plot.scatter(x=0, y=1, c="species")
+        colorbar = ax.collections[0].colorbar
+
+        expected_ticks = np.array([0.5, 1.5, 2.5])
+        result_ticks = colorbar.get_ticks()
+        tm.assert_numpy_array_equal(result_ticks, expected_ticks)
+
+        expected_boundaries = np.array([0.0, 1.0, 2.0, 3.0])
+        result_boundaries = colorbar._boundaries
+        tm.assert_numpy_array_equal(result_boundaries, expected_boundaries)
+
+        expected_yticklabels = categories
+        result_yticklabels = [i.get_text() for i in colorbar.ax.get_ymajorticklabels()]
+        assert all(
+            result == expected
+            for result, expected in zip(result_yticklabels, expected_yticklabels)
         )
-        _check_plot_works(df.plot.scatter, x=0, y=1, c="species")
 
     @pytest.mark.slow
     def test_if_scatterplot_colorbar_affects_xaxis_visibility(self):

From 5fbc117c1c942c1c77d4299f081dfc99ff4be5cf Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Fri, 22 May 2020 14:09:35 +0100
Subject: [PATCH 14/19] update test

---
 pandas/tests/plotting/test_frame.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index c48e738aa422e..71fd000c58845 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -1218,10 +1218,7 @@ def test_scatterplot_color_by_categorical(self, ordered, categories):
 
         expected_yticklabels = categories
         result_yticklabels = [i.get_text() for i in colorbar.ax.get_ymajorticklabels()]
-        assert all(
-            result == expected
-            for result, expected in zip(result_yticklabels, expected_yticklabels)
-        )
+        assert all(i == j for i, j in zip(result_yticklabels, expected_yticklabels))
 
     @pytest.mark.slow
     def test_if_scatterplot_colorbar_affects_xaxis_visibility(self):

From b2a8b28ecd795767371b2b6e32c2985f6a674f42 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <m.e.gorelli@gmail.com>
Date: Sun, 3 Jan 2021 15:58:41 +0000
Subject: [PATCH 15/19] :art:

---
 pandas/plotting/_matplotlib/core.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index 2891148886459..04094d1f11df5 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -440,6 +440,7 @@ def _compute_plot_data(self):
         # no non-numeric frames or series allowed
         if is_empty:
             raise TypeError("no numeric data to plot")
+
         self.data = numeric_data.apply(
             lambda x: self._convert_to_ndarray(x) if not is_categorical_dtype(x) else x
         )

From b0a8cfa5e8d00c62156074893d08a67b8ed5f6e6 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <marcogorelli@protonmail.com>
Date: Sun, 17 Jan 2021 10:22:37 +0000
Subject: [PATCH 16/19] simplify logic

---
 pandas/plotting/_matplotlib/core.py | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
index 08292c6af9b13..6ad0e7b8b62d5 100644
--- a/pandas/plotting/_matplotlib/core.py
+++ b/pandas/plotting/_matplotlib/core.py
@@ -387,6 +387,10 @@ def result(self):
                 return self.axes[0]
 
     def _convert_to_ndarray(self, data):
+        # GH31357: categorical columns are processed separately
+        if is_categorical_dtype(data):
+            return data
+
         # GH32073: cast to float if values contain nulled integers
         if (
             is_integer_dtype(data.dtype) or is_float_dtype(data.dtype)
@@ -440,9 +444,7 @@ def _compute_plot_data(self):
         if is_empty:
             raise TypeError("no numeric data to plot")
 
-        self.data = numeric_data.apply(
-            lambda x: self._convert_to_ndarray(x) if not is_categorical_dtype(x) else x
-        )
+        self.data = numeric_data.apply(self._convert_to_ndarray)
 
     def _make_plot(self):
         raise AbstractMethodError(self)
@@ -1029,11 +1031,10 @@ def _make_plot(self):
             c_values = self.plt.rcParams["patch.facecolor"]
         elif color is not None:
             c_values = color
+        elif color_by_categorical:
+            c_values = self.data[c].cat.codes
         elif c_is_column:
-            if color_by_categorical:
-                c_values = self.data[c].cat.codes
-            else:
-                c_values = self.data[c].values
+            c_values = self.data[c].values
         else:
             c_values = c
 

From 4c15a83c0aa6bb3971e4663524595e10780fc069 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <marcogorelli@protonmail.com>
Date: Sun, 17 Jan 2021 11:24:37 +0000
Subject: [PATCH 17/19] whatsnew entry

---
 doc/source/whatsnew/v1.3.0.rst            | 1 +
 pandas/tests/plotting/frame/test_frame.py | 3 ++-
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v1.3.0.rst b/doc/source/whatsnew/v1.3.0.rst
index ab00b749d5725..60bf15658a9f4 100644
--- a/doc/source/whatsnew/v1.3.0.rst
+++ b/doc/source/whatsnew/v1.3.0.rst
@@ -52,6 +52,7 @@ Other enhancements
 - :meth:`DataFrame.apply` can now accept NumPy unary operators as strings, e.g. ``df.apply("sqrt")``, which was already the case for :meth:`Series.apply` (:issue:`39116`)
 - :meth:`DataFrame.apply` can now accept non-callable DataFrame properties as strings, e.g. ``df.apply("size")``, which was already the case for :meth:`Series.apply` (:issue:`39116`)
 - :meth:`Series.apply` can now accept list-like or dictionary-like arguments that aren't lists or dictionaries, e.g. ``ser.apply(np.array(["sum", "mean"]))``, which was already the case for :meth:`DataFrame.apply` (:issue:`39140`)
+- :meth:`DataFrame.plot.scatter` can now accept a categorical column as the argument to ``c`` (:issue:`31357`)
 
 .. ---------------------------------------------------------------------------
 
diff --git a/pandas/tests/plotting/frame/test_frame.py b/pandas/tests/plotting/frame/test_frame.py
index f433b8f39e862..12d70e7e82604 100644
--- a/pandas/tests/plotting/frame/test_frame.py
+++ b/pandas/tests/plotting/frame/test_frame.py
@@ -712,7 +712,8 @@ def test_scatterplot_color_by_categorical(self, ordered, categories):
             categories=categories,
         )
         ax = df.plot.scatter(x=0, y=1, c="species")
-        colorbar = ax.collections[0].colorbar
+        (colorbar_collection,) = ax.collections
+        colorbar = colorbar_collection.colorbar
 
         expected_ticks = np.array([0.5, 1.5, 2.5])
         result_ticks = colorbar.get_ticks()

From cce3461977168b9099f2a2ac460f3eb67af53e10 Mon Sep 17 00:00:00 2001
From: Marco Gorelli <marcogorelli@protonmail.com>
Date: Tue, 26 Jan 2021 21:11:48 +0000
Subject: [PATCH 18/19] add example to visualisation

---
 doc/source/user_guide/visualization.rst | 16 ++++++++++++++++
 doc/source/whatsnew/v1.3.0.rst          |  2 +-
 2 files changed, 17 insertions(+), 1 deletion(-)

diff --git a/doc/source/user_guide/visualization.rst b/doc/source/user_guide/visualization.rst
index c4ee8677a6b0d..29ab73473bd6d 100644
--- a/doc/source/user_guide/visualization.rst
+++ b/doc/source/user_guide/visualization.rst
@@ -552,6 +552,9 @@ These can be specified by the ``x`` and ``y`` keywords.
 .. ipython:: python
 
    df = pd.DataFrame(np.random.rand(50, 4), columns=["a", "b", "c", "d"])
+   df["species"] = pd.Categorical(
+       ["setosa"] * 20 + ["versicolor"] * 20 + ["virginica"] * 10
+   )
 
    @savefig scatter_plot.png
    df.plot.scatter(x="a", y="b");
@@ -579,6 +582,19 @@ each point:
    df.plot.scatter(x="a", y="b", c="c", s=50);
 
 
+.. ipython:: python
+   :suppress:
+
+   plt.close("all")
+
+If a categorical column is passed to ``c``, then a discrete colorbar will be produced:
+
+.. ipython:: python
+
+   @savefig scatter_plot_categorical.png
+   df.plot.scatter(x="a", y="b", c="species", cmap="viridis", s=50);
+
+
 .. ipython:: python
    :suppress:
 
diff --git a/doc/source/whatsnew/v1.3.0.rst b/doc/source/whatsnew/v1.3.0.rst
index a2804b9d49f9a..886e034f60d27 100644
--- a/doc/source/whatsnew/v1.3.0.rst
+++ b/doc/source/whatsnew/v1.3.0.rst
@@ -52,7 +52,7 @@ Other enhancements
 - :meth:`DataFrame.apply` can now accept NumPy unary operators as strings, e.g. ``df.apply("sqrt")``, which was already the case for :meth:`Series.apply` (:issue:`39116`)
 - :meth:`DataFrame.apply` can now accept non-callable DataFrame properties as strings, e.g. ``df.apply("size")``, which was already the case for :meth:`Series.apply` (:issue:`39116`)
 - :meth:`Series.apply` can now accept list-like or dictionary-like arguments that aren't lists or dictionaries, e.g. ``ser.apply(np.array(["sum", "mean"]))``, which was already the case for :meth:`DataFrame.apply` (:issue:`39140`)
-- :meth:`DataFrame.plot.scatter` can now accept a categorical column as the argument to ``c`` (:issue:`31357`)
+- :meth:`DataFrame.plot.scatter` can now accept a categorical column as the argument to ``c`` (:issue:`12380`, :issue:`31357`)
 - :meth:`.Styler.set_tooltips` allows on hover tooltips to be added to styled HTML dataframes.
 
 .. ---------------------------------------------------------------------------

From 6e010915e1bfbc55557f91d39594b32e5a73c42d Mon Sep 17 00:00:00 2001
From: Marco Gorelli <marcogorelli@protonmail.com>
Date: Wed, 27 Jan 2021 14:57:22 +0000
Subject: [PATCH 19/19] add versionadded tag

---
 doc/source/user_guide/visualization.rst | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/doc/source/user_guide/visualization.rst b/doc/source/user_guide/visualization.rst
index 29ab73473bd6d..7911c58b9867e 100644
--- a/doc/source/user_guide/visualization.rst
+++ b/doc/source/user_guide/visualization.rst
@@ -589,6 +589,8 @@ each point:
 
 If a categorical column is passed to ``c``, then a discrete colorbar will be produced:
 
+.. versionadded:: 1.3.0
+
 .. ipython:: python
 
    @savefig scatter_plot_categorical.png