DOC: Improve docs for plotting

Author: bashtage

pandas/plotting/_core.py

@@ -266,6 +266,7 @@ def hist_frame(
 
 Parameters
 ----------
+%(data)s\
 column : str or list of str, optional
     Column name or list of names, or vector.
     Can be any valid input to :meth:`pandas.DataFrame.groupby`.
@@ -466,7 +467,7 @@ def hist_frame(
 """
 
 
-@Substitution(backend="")
+@Substitution(data="data : DataFrame\n    The data to visualize.\n", backend="")
 @Appender(_boxplot_doc)
 def boxplot(
     data: DataFrame,
@@ -497,7 +498,7 @@ def boxplot(
     )
 
 
-@Substitution(backend=_backend_doc)
+@Substitution(data="", backend=_backend_doc)
 @Appender(_boxplot_doc)
 def boxplot_frame(
     self,

pandas/plotting/_misc.py

@@ -19,7 +19,7 @@
     )
 
 
-def table(ax, data, rowLabels=None, colLabels=None, **kwargs):
+def table(ax, data, **kwargs):
     """
     Helper function to convert DataFrame and Series to matplotlib.table.
 
@@ -285,14 +285,18 @@ def andrews_curves(
     ----------
     frame : DataFrame
         Data to be plotted, preferably normalized to (0.0, 1.0).
-    class_column : Name of the column containing class names
-    ax : matplotlib axes object, default None
-    samples : Number of points to plot in each curve
-    color : list or tuple, optional
-        Colors to use for the different classes.
+    class_column : label
+        Name of the column containing class names
+    ax : axes object, default None
+        Axes to use
+    samples : int
+        Number of points to plot in each curve
+    color : {str, list, tuple}, optional
+        Colors to use for the different classes. Colors can be strings
+        or 3-element floating point RBG values.
     colormap : str or matplotlib colormap object, default None
-        Colormap to select colors from. If string, load colormap with that name
-        from matplotlib.
+        Colormap to select colors from. If a string, load colormap with that
+        name from matplotlib.
     **kwargs
         Options to pass to matplotlib plotting method.
 
@@ -430,7 +434,7 @@ def parallel_coordinates(
 
     Returns
     -------
-    class:`matplotlib.axis.Axes`
+    matplotlib.axis.Axes
 
     Examples
     --------
@@ -470,19 +474,21 @@ def lag_plot(series: Series, lag: int = 1, ax: Axes | None = None, **kwds) -> Ax
 
     Parameters
     ----------
-    series : Time series
-    lag : lag of the scatter plot, default 1
+    series : Series
+        The time series to visualize.
+    lag : int, optional
+        lag of the scatter plot, default 1.
     ax : Matplotlib axis object, optional
+        The matplotlib axis object to use.
     **kwds
         Matplotlib scatter method keyword arguments.
 
     Returns
     -------
-    class:`matplotlib.axis.Axes`
+    matplotlib.axis.Axes
 
     Examples
     --------
-
     Lag plots are most commonly used to look for patterns in time series data.
 
     Given the following time series
@@ -514,18 +520,19 @@ def autocorrelation_plot(series: Series, ax: Axes | None = None, **kwargs) -> Ax
 
     Parameters
     ----------
-    series : Time series
+    series : Series
+        The time series to visualize.
     ax : Matplotlib axis object, optional
+        The matplotlib axis object to use.
     **kwargs
         Options to pass to matplotlib plotting method.
 
     Returns
     -------
-    class:`matplotlib.axis.Axes`
+    matplotlib.axis.Axes
 
     Examples
     --------
-
     The horizontal lines in the plot correspond to 95% and 99% confidence bands.
 
     The dashed line is 99% confidence band.