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Doc: examples update #13399

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4 changes: 1 addition & 3 deletions examples/images_contours_and_fields/interpolation_methods.py
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Expand Up @@ -28,11 +28,9 @@

grid = np.random.rand(4, 4)

fig, axs = plt.subplots(nrows=3, ncols=6, figsize=(9.3, 6),
fig, axs = plt.subplots(nrows=3, ncols=6, figsize=(9, 6),
subplot_kw={'xticks': [], 'yticks': []})

fig.subplots_adjust(left=0.03, right=0.97, hspace=0.3, wspace=0.05)

for ax, interp_method in zip(axs.flat, methods):
ax.imshow(grid, interpolation=interp_method, cmap='viridis')
ax.set_title(str(interp_method))
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77 changes: 77 additions & 0 deletions examples/lines_bars_and_markers/barchart.py
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@@ -0,0 +1,77 @@
"""
=============================
Grouped bar chart with labels
=============================

Bar charts are useful for visualizing counts, or summary statistics
with error bars. This example shows a ways to create a grouped bar chart
with Matplotlib and also how to annotate bars with labels.
"""

import matplotlib
import matplotlib.pyplot as plt
import numpy as np


men_means, men_std = (20, 35, 30, 35, 27), (2, 3, 4, 1, 2)
women_means, women_std = (25, 32, 34, 20, 25), (3, 5, 2, 3, 3)

ind = np.arange(len(men_means)) # the x locations for the groups
width = 0.35 # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(ind - width/2, men_means, width, yerr=men_std,
label='Men')
rects2 = ax.bar(ind + width/2, women_means, width, yerr=women_std,
label='Women')

# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(ind)
ax.set_xticklabels(('G1', 'G2', 'G3', 'G4', 'G5'))
ax.legend()


def autolabel(rects, xpos='center'):
"""
Attach a text label above each bar in *rects*, displaying its height.

*xpos* indicates which side to place the text w.r.t. the center of
the bar. It can be one of the following {'center', 'right', 'left'}.
"""

ha = {'center': 'center', 'right': 'left', 'left': 'right'}
offset = {'center': 0, 'right': 1, 'left': -1}

for rect in rects:
height = rect.get_height()
ax.annotate('{}'.format(height),
xy=(rect.get_x() + rect.get_width() / 2, height),
xytext=(offset[xpos]*3, 3), # use 3 points offset
textcoords="offset points", # in both directions
ha=ha[xpos], va='bottom')


autolabel(rects1, "left")
autolabel(rects2, "right")

fig.tight_layout()

plt.show()


#############################################################################
#
# ------------
#
# References
# """"""""""
#
# The use of the following functions, methods and classes is shown
# in this example:

matplotlib.axes.Axes.bar
matplotlib.pyplot.bar
matplotlib.axes.Axes.annotate
matplotlib.pyplot.annotate
10 changes: 3 additions & 7 deletions examples/pie_and_polar_charts/polar_bar.py
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@@ -1,6 +1,6 @@
"""
=======================
Pie chart on polar axis
Bar chart on polar axis
=======================

Demo of bar plot on a polar axis.
Expand All @@ -17,14 +17,10 @@
theta = np.linspace(0.0, 2 * np.pi, N, endpoint=False)
radii = 10 * np.random.rand(N)
width = np.pi / 4 * np.random.rand(N)
colors = plt.cm.viridis(radii / 10.)

ax = plt.subplot(111, projection='polar')
bars = ax.bar(theta, radii, width=width, bottom=0.0)

# Use custom colors and opacity
for r, bar in zip(radii, bars):
bar.set_facecolor(plt.cm.viridis(r / 10.))
bar.set_alpha(0.5)
ax.bar(theta, radii, width=width, bottom=0.0, color=colors, alpha=0.5)

plt.show()

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121 changes: 44 additions & 77 deletions examples/statistics/barchart_demo.py
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@@ -1,74 +1,27 @@
"""
=============
Barchart Demo
=============

Bar charts of many shapes and sizes with Matplotlib.
===================================
Percentiles as horizontal bar chart
===================================

Bar charts are useful for visualizing counts, or summary statistics
with error bars. These examples show a few ways to do this with Matplotlib.
with error bars. Also see the :doc:`/gallery/lines_bars_and_markers/barchart`
or the :doc:`/gallery/lines_bars_and_markers/barh` example for simpler versions
of those features.

This example comes from an application in which grade school gym
teachers wanted to be able to show parents how their child did across
a handful of fitness tests, and importantly, relative to how other
children did. To extract the plotting code for demo purposes, we'll
just make up some data for little Johnny Doe.
"""

###############################################################################
# A bar plot with errorbars and height labels on individual bars.

# Credit: Josh Hemann

import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
from collections import namedtuple


men_means, men_std = (20, 35, 30, 35, 27), (2, 3, 4, 1, 2)
women_means, women_std = (25, 32, 34, 20, 25), (3, 5, 2, 3, 3)

ind = np.arange(len(men_means)) # the x locations for the groups
width = 0.35 # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(ind - width/2, men_means, width, yerr=men_std,
label='Men')
rects2 = ax.bar(ind + width/2, women_means, width, yerr=women_std,
label='Women')

# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(ind)
ax.set_xticklabels(('G1', 'G2', 'G3', 'G4', 'G5'))
ax.legend()


def autolabel(rects, xpos='center'):
"""
Attach a text label above each bar in *rects*, displaying its height.

*xpos* indicates which side to place the text w.r.t. the center of
the bar. It can be one of the following {'center', 'right', 'left'}.
"""

ha = {'center': 'center', 'right': 'left', 'left': 'right'}
offset = {'center': 0.5, 'right': 0.57, 'left': 0.43} # x_txt = x + w*off

for rect in rects:
height = rect.get_height()
ax.text(rect.get_x() + rect.get_width() * offset[xpos], 1.01 * height,
'{}'.format(height), ha=ha[xpos], va='bottom')


autolabel(rects1, "left")
autolabel(rects2, "right")

fig.tight_layout()


###############################################################################
# This example comes from an application in which grade school gym
# teachers wanted to be able to show parents how their child did across
# a handful of fitness tests, and importantly, relative to how other
# children did. To extract the plotting code for demo purposes, we'll
# just make up some data for little Johnny Doe...
np.random.seed(42)

Student = namedtuple('Student', ['name', 'grade', 'gender'])
Score = namedtuple('Score', ['score', 'percentile'])
Expand Down Expand Up @@ -142,10 +95,6 @@ def plot_student_results(student, scores, cohort_size):

# Plot a solid vertical gridline to highlight the median position
ax1.axvline(50, color='grey', alpha=0.25)
# set X-axis tick marks at the deciles
cohort_label = ax1.text(.5, -.07, 'Cohort Size: {0}'.format(cohort_size),
horizontalalignment='center', size='small',
transform=ax1.transAxes)

# Set the right-hand Y-axis ticks and labels
ax2 = ax1.twinx()
Expand All @@ -163,10 +112,11 @@ def plot_student_results(student, scores, cohort_size):

ax2.set_ylabel('Test Scores')

ax2.set_xlabel(('Percentile Ranking Across '
'{grade} Grade {gender}s').format(
grade=attach_ordinal(student.grade),
gender=student.gender.title()))
xlabel = ('Percentile Ranking Across {grade} Grade {gender}s\n'
'Cohort Size: {cohort_size}')
ax1.set_xlabel(xlabel.format(grade=attach_ordinal(student.grade),
gender=student.gender.title(),
cohort_size=cohort_size))

rect_labels = []
# Lastly, write in the ranking inside each bar to aid in interpretation
Expand All @@ -178,24 +128,25 @@ def plot_student_results(student, scores, cohort_size):

rankStr = attach_ordinal(width)
# The bars aren't wide enough to print the ranking inside
if width < 5:
if width < 40:
# Shift the text to the right side of the right edge
xloc = width + 1
xloc = 5
# Black against white background
clr = 'black'
align = 'left'
else:
# Shift the text to the left side of the right edge
xloc = 0.98 * width
xloc = -5
# White on magenta
clr = 'white'
align = 'right'

# Center the text vertically in the bar
yloc = rect.get_y() + rect.get_height() / 2
label = ax1.text(xloc, yloc, rankStr, horizontalalignment=align,
verticalalignment='center', color=clr, weight='bold',
clip_on=True)
label = ax1.annotate(rankStr, xy=(width, yloc), xytext=(xloc, 0),
textcoords="offset points",
ha=align, va='center',
color=clr, weight='bold', clip_on=True)
rect_labels.append(label)

# make the interactive mouse over give the bar title
Expand All @@ -205,8 +156,7 @@ def plot_student_results(student, scores, cohort_size):
'ax': ax1,
'ax_right': ax2,
'bars': rects,
'perc_labels': rect_labels,
'cohort_label': cohort_label}
'perc_labels': rect_labels}


student = Student('Johnny Doe', 2, 'boy')
Expand All @@ -219,3 +169,20 @@ def plot_student_results(student, scores, cohort_size):

arts = plot_student_results(student, scores, cohort_size)
plt.show()


#############################################################################
#
# ------------
#
# References
# """"""""""
#
# The use of the following functions, methods and classes is shown
# in this example:

matplotlib.axes.Axes.bar
matplotlib.pyplot.bar
matplotlib.axes.Axes.annotate
matplotlib.pyplot.annotate
matplotlib.axes.Axes.twinx
3 changes: 2 additions & 1 deletion examples/units/bar_unit_demo.py
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Expand Up @@ -3,7 +3,8 @@
Group barchart with units
=========================

This is the same example as :doc:`/gallery/statistics/barchart_demo` in
This is the same example as
:doc:`the barchart</gallery/lines_bars_and_markers/barchart>` in
centimeters.

.. only:: builder_html
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