DOC: Add user_guide examples and docstring example for df.plot.box and df.plot.hist (pandas-dev#42520)

Author: charlesdong1991

doc/source/user_guide/visualization.rst

@@ -316,6 +316,34 @@ The ``by`` keyword can be specified to plot grouped histograms:
    @savefig grouped_hist.png
    data.hist(by=np.random.randint(0, 4, 1000), figsize=(6, 4));
 
+.. ipython:: python
+   :suppress:
+
+   plt.close("all")
+   np.random.seed(123456)
+
+In addition, the ``by`` keyword can also be specified in :meth:`DataFrame.plot.hist`.
+
+.. versionchanged:: 1.4.0
+
+.. ipython:: python
+
+   data = pd.DataFrame(
+       {
+           "a": np.random.choice(["x", "y", "z"], 1000),
+           "b": np.random.choice(["e", "f", "g"], 1000),
+           "c": np.random.randn(1000),
+           "d": np.random.randn(1000) - 1,
+       },
+   )
+
+   @savefig grouped_hist_by.png
+   data.plot.hist(by=["a", "b"], figsize=(10, 5));
+
+.. ipython:: python
+   :suppress:
+
+   plt.close("all")
 
 .. _visualization.box:
 
@@ -448,6 +476,32 @@ columns:
 
     plt.close("all")
 
+You could also create groupings with :meth:`DataFrame.plot.box`, for instance:
+
+.. versionchanged:: 1.4.0
+
+.. ipython:: python
+   :suppress:
+
+   plt.close("all")
+   np.random.seed(123456)
+
+.. ipython:: python
+   :okwarning:
+
+   df = pd.DataFrame(np.random.rand(10, 3), columns=["Col1", "Col2", "Col3"])
+   df["X"] = pd.Series(["A", "A", "A", "A", "A", "B", "B", "B", "B", "B"])
+
+   plt.figure();
+
+   @savefig box_plot_ex4.png
+   bp = df.plot.box(column=["Col1", "Col2"], by="X")
+
+.. ipython:: python
+   :suppress:
+
+    plt.close("all")
+
 .. _visualization.box.return:
 
 In ``boxplot``, the return type can be controlled by the ``return_type``, keyword. The valid choices are ``{"axes", "dict", "both", None}``.

pandas/plotting/_core.py

@@ -1267,6 +1267,18 @@ def box(self, by=None, **kwargs):
             >>> data = np.random.randn(25, 4)
             >>> df = pd.DataFrame(data, columns=list('ABCD'))
             >>> ax = df.plot.box()
+
+        You can also generate groupings if you specify the `by` parameter (which
+        can take a column name, or a list or tuple of column names):
+
+        .. versionchanged:: 1.4.0
+
+        .. plot::
+            :context: close-figs
+
+            >>> age_list = [8, 10, 12, 14, 72, 74, 76, 78, 20, 25, 30, 35, 60, 85]
+            >>> df = pd.DataFrame({"gender": list("MMMMMMMMFFFFFF"), "age": age_list})
+            >>> ax = df.plot.box(column="age", by="gender", figsize=(10, 8))
         """
         return self(kind="box", by=by, **kwargs)