matplotlib
diff --git a/‎examples/lines_bars_and_markers/bar_label_demo.py
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+14-22Lines changed: 14 additions & 22 deletions b/‎examples/lines_bars_and_markers/bar_label_demo.py
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diff --git a/‎examples/lines_bars_and_markers/bar_stacked.py
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+20-16Lines changed: 20 additions & 16 deletions b/‎examples/lines_bars_and_markers/bar_stacked.py
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+20-16Lines changed: 20 additions & 16 deletions
diff --git a/‎examples/lines_bars_and_markers/barchart.py
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+22-17Lines changed: 22 additions & 17 deletions b/‎examples/lines_bars_and_markers/barchart.py
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+22-17Lines changed: 22 additions & 17 deletions
@@ -18,35 +18,27 @@
 import numpy as np
 
 ###############################################################################
-# Define the data
+# data from https://allisonhorst.github.io/palmerpenguins/
 
-N = 5
-coffee_means = (20, 25, -10, 32, 10)
-tea_means = (30, 13, -14, 21, 17)
-coffee_std = (3, 2, 4, 1, 2)
-tea_std = (4, 3, 2, 3, 5)
-ind = np.arange(N)    # the x locations for the groups
-width = 0.25       # the width of the bars: can also be len(x) sequence
+species = ('Adelie', 'Chinstrap', 'Gentoo')
+sex_counts = {
+    'Male': np.array([73, 34, 61]),
+    'Female': np.array([73, 34, 58]),
+}
+width = 0.6  # the width of the bars: can also be len(x) sequence
 
-###############################################################################
-# Stacked bar plot with error bars
 
 fig, ax = plt.subplots()
+bottom = np.zeros(3)
 
-p1 = ax.bar(ind, coffee_means, width, yerr=coffee_std, label='Coffee')
-p2 = ax.bar(ind, tea_means, width,
-            bottom=coffee_means, yerr=tea_std, label='Tea')
+for sex, sex_count in sex_counts.items():
+    p = ax.bar(species, sex_count, width, label=sex, bottom=bottom)
+    bottom += sex_count
 
-ax.axhline(0, color='grey', linewidth=0.8)
-ax.set_ylabel('Scores')
-ax.set_title('Scores by group and their beverage choices')
-ax.set_xticks(ind, labels=['G1', 'G2', 'G3', 'G4', 'G5'])
-ax.legend()
+    ax.bar_label(p, label_type='center')
 
-# Label with label_type 'center' instead of the default 'edge'
-ax.bar_label(p1, label_type='center')
-ax.bar_label(p2, label_type='center')
-ax.bar_label(p2)
+ax.set_title('Number of penguins by sex')
+ax.legend()
 
 plt.show()
 
 
@@ -3,30 +3,34 @@
 Stacked bar chart
 =================
 
-This is an example of creating a stacked bar plot with error bars
-using `~matplotlib.pyplot.bar`.  Note the parameters *yerr* used for
-error bars, and *bottom* to stack the coffee's bars on top of the tea's
-bars.
+This is an example of creating a stacked bar plot
+using `~matplotlib.pyplot.bar`.
 """
 
 import matplotlib.pyplot as plt
+import numpy as np
 
+# data from https://allisonhorst.github.io/palmerpenguins/
 
-labels = ['G1', 'G2', 'G3', 'G4', 'G5']
-tea_means = [20, 35, 30, 35, 27]
-coffee_means = [25, 32, 34, 20, 25]
-tea_std = [2, 3, 4, 1, 2]
-coffee_std = [3, 5, 5, 3, 3]
-width = 0.25       # the width of the bars: can also be len(x) sequence
+species = (
+    "Adelie\n $\\mu=$3700.66g",
+    "Chinstrap\n $\\mu=$3733.09g",
+    "Gentoo\n $\\mu=5076.02g$",
+)
+weight_counts = {
+    "Below": np.array([70, 31, 58]),
+    "Above": np.array([82, 37, 66]),
+}
+width = 0.5
 
 fig, ax = plt.subplots()
+bottom = np.zeros(3)
 
-ax.bar(labels, tea_means, width, yerr=tea_std, label='Tea')
-ax.bar(labels, coffee_means, width, yerr=coffee_std, bottom=tea_means,
-       label='Coffee')
+for boolean, weight_count in weight_counts.items():
+    p = ax.bar(species, weight_count, width, label=boolean, bottom=bottom)
+    bottom += weight_count
 
-ax.set_ylabel('Scores')
-ax.set_title('Scores by group and beverage preferences')
-ax.legend()
+ax.set_title("Number of penguins with above average body mass")
+ax.legend(loc="upper right")
 
 plt.show()
@@ -7,31 +7,36 @@
 bars with labels.
 """
 
+# data from https://allisonhorst.github.io/palmerpenguins/
+
 import matplotlib.pyplot as plt
 import numpy as np
 
+species = ("Adelie", "Chinstrap", "Gentoo")
+penguin_means = {
+    'Bill Depth': (18.35, 18.43, 14.98),
+    'Bill Length': (38.79, 48.83, 47.50),
+    'Flipper Length': (189.95, 195.82, 217.19),
+}
 
-labels = ['G1', 'G2', 'G3', 'G4', 'G5']
-tea_means = [20, 34, 31, 35, 27]
-coffee_means = [25, 32, 34, 20, 25]
-
-x = np.arange(len(labels))  # the label locations
+x = np.arange(len(species))  # the label locations
 width = 0.25  # the width of the bars
+multiplier = 0
 
-fig, ax = plt.subplots()
-rects1 = ax.bar(x - width/2, tea_means, width, label='Tea')
-rects2 = ax.bar(x + width/2, coffee_means, width, label='Coffee')
+fig, ax = plt.subplots(constrained_layout=True)
 
-# Add some text for labels, title and custom x-axis tick labels, etc.
-ax.set_ylabel('Scores')
-ax.set_title('Scores by group and beverage preferences')
-ax.set_xticks(x, labels)
-ax.legend()
+for attribute, measurement in penguin_means.items():
+    offset = width * multiplier
+    rects = ax.bar(x + offset, measurement, width, label=attribute)
+    ax.bar_label(rects, padding=3)
+    multiplier += 1
 
-ax.bar_label(rects1, padding=3)
-ax.bar_label(rects2, padding=3)
-
-fig.tight_layout()
+# Add some text for labels, title and custom x-axis tick labels, etc.
+ax.set_ylabel('Length (mm)')
+ax.set_title('Penguin attributes by species')
+ax.set_xticks(x + width, species)
+ax.legend(loc='upper left', ncols=3)
+ax.set_ylim(0, 250)
 
 plt.show()