Altered whats new entry, docs and gallery example

Impaler343 · Impaler343 · commit 528baa1146f1 · 2024-06-04T18:07:40.000+05:30
diff --git a/doc/users/next_whats_new/histogram_vectorized_parameters.rst b/doc/users/next_whats_new/histogram_vectorized_parameters.rst
@@ -2,12 +2,12 @@ Vectorize ``hatch``, ``edgecolor``, ``linewidth`` and ``linestyle`` in *hist* me
 ---------------------------------------------------------------------------------------
 
 The parameters ``hatch``, ``edgecolor``, ``linewidth`` and ``linestyle`` of the `~matplotlib.axes.Axes.hist` method are now vectorized.
-This means that you can pass a list of values to these parameters, and the values will be applied to each dataset in the histogram.
+This means that you can pass in unique parameters for each histogram that is generated when the input *x* has multiple datasets.
 Note that the ``facecolor`` parameter is not vectorized, but the required behavior can be achieved by passing a list of colors to the ``color`` parameter.
 
 .. plot::
     :include-source: true
-    :alt: Three charts, identified as ax1, ax2 and ax3, include plots of three random datasets. The first, second and third plots have datasets differentiated by linewidths, hatches and linestyles, respectively. Edgecolors are used in all of the plots to accentuate the differences.
+    :alt: Three charts, identified as ax1, ax2 and ax3, show a stacking of three histograms representing Poisson distributions. The histograms in ax1, ax2, and ax3 are differentiated by linewidths, hatches and linestyles, respectively. In ax1, ax2, and ax3, each histogram is bordered by a different color.
 
     import matplotlib.pyplot as plt
     import numpy as np
diff --git a/galleries/examples/statistics/histogram_multihist.py b/galleries/examples/statistics/histogram_multihist.py
@@ -27,75 +27,100 @@
 fig, ((ax0, ax1), (ax2, ax3)) = plt.subplots(nrows=2, ncols=2)
 
 colors = ['red', 'tan', 'lime']
-ax0.hist(x, n_bins, density=True, histtype="bar", color=colors, label=colors)
+ax0.hist(x, n_bins, density=True, histtype='bar', color=colors, label=colors)
 ax0.legend(prop={'size': 10})
 ax0.set_title('bars with legend')
 
-ax1.hist(x, n_bins, density=True, histtype="bar", stacked=True)
+ax1.hist(x, n_bins, density=True, histtype='bar', stacked=True)
 ax1.set_title('stacked bar')
 
-ax2.hist(x, n_bins, histtype="step", stacked=True, fill=False)
+ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False)
 ax2.set_title('stack step (unfilled)')
 
 # Make a multiple-histogram of data-sets with different length.
 x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]
-ax3.hist(x_multi, n_bins, histtype="bar")
+ax3.hist(x_multi, n_bins, histtype='bar')
 ax3.set_title('different sample sizes')
 
 fig.tight_layout()
 plt.show()
 
 # %%
-# Setting properties for each sample set
-# --------------------------------------
+# -----------------------------------
+# Setting properties for each dataset
+# -----------------------------------
 #
-# Plotting a bar chart with sample sets differentiated using:
+# Plotting bar charts with datasets differentiated using:
 #
 # * edgecolors
 # * hatches
 # * linewidths
 # * linestyles
 #
-# Also, these parameters can be specified for all types of
-# histograms (stacked, step, etc.) and not just for the *bar*
-# type histogram as shown in the example.
+#
+# Histograms with Edge-Colors
+# ...........................
 
-hatches = ["-", "o", "x"]
-linewidths = [1, 2, 3]
-edgecolors = ["green", "red", "blue"]
-linestyles = ["-", ":", "--"]
+fig, ax = plt.subplots()
 
-fig, ((ax0, ax1), (ax2, ax3)) = plt.subplots(nrows=2, ncols=2)
+edgecolors = ['green', 'red', 'blue']
 
-ax0.hist(
-    x, n_bins, density=True, fill=False, histtype="bar",
+ax.hist(
+    x, n_bins, fill=False, histtype="step", stacked=True,
     edgecolor=edgecolors, label=edgecolors
 )
-ax0.legend(prop={"size": 10})
-ax0.set_title("Bars with Edgecolors")
+ax.legend()
+ax.set_title('Stacked Steps with Edgecolors')
 
-ax1.hist(
-    x, n_bins, density=True, histtype="bar",
-    hatch=hatches, label=hatches
-)
-ax1.legend(prop={"size": 10})
-ax1.set_title("Bars with Hatches")
+plt.show()
+
+
+# Histograms with Hatches
+# .......................
+
+fig, ax = plt.subplots()
+
+hatches = [".", "o", "x"]
+
+ax.hist(x, n_bins, histtype="barstacked", hatch=hatches, label=hatches)
+ax.legend()
+ax.set_title("Hatches on Stacked Bars")
+
+plt.show()
 
-ax2.hist(
-    x, n_bins, density=True, fill=False, histtype="bar",
-    linewidth=linewidths, edgecolor=edgecolors, label=linewidths
+
+# Histograms with Linewidths
+# ..........................
+
+fig, ax = plt.subplots()
+
+linewidths = [1, 2, 3]
+edgecolors = ["green", "red", "blue"]
+
+ax.hist(
+    x, n_bins, fill=False, histtype="bar", linewidth=linewidths,
+    edgecolor=edgecolors, label=linewidths,
 )
-ax2.legend(prop={"size": 10})
-ax2.set_title("Bars with Linewidths")
+ax.legend()
+ax.set_title("Bars with Linewidths")
 
-ax3.hist(
-    x, n_bins, density=True, fill=False, histtype="bar",
-    linestyle=linestyles, edgecolor=edgecolors, label=linestyles
+plt.show()
+
+
+# Histograms with LineStyles
+# ...........................
+
+fig, ax = plt.subplots()
+
+linestyles = ['-', ':', '--']
+
+ax.hist(
+    x, n_bins, fill=False, histtype='bar', linestyle=linestyles,
+    edgecolor=edgecolors, label=linestyles
 )
-ax3.legend(prop={"size": 10})
-ax3.set_title("Bars with Linestyles")
+ax.legend()
+ax.set_title('Bars with Linestyles')
 
-fig.tight_layout()
 plt.show()
 
 # %%
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -6938,7 +6938,8 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
 
         **kwargs
             `~matplotlib.patches.Patch` properties. The following properties
-            additionally accept lists of property values, one element for each dataset:
+            additionally accepts a sequence of properties values corresponding
+            to the datasets in *x*:
             *edgecolors*, *linewidths*, *linestyles*, *hatches*.
 
         See Also
