百分位数作为水平条形图#

条形图可用于可视化计数或带有误差线的汇总统计信息。另请参阅带标签的分组条形图或水平条形图示例，了解这些功能的更简单版本。

这个例子来自一个应用程序，在该应用程序中，小学体育老师希望能够向父母展示他们的孩子在几次体能测试中的表现，重要的是，相对于其他孩子的表现。为了演示的目的提取绘图代码，我们将为小 Johnny Doe 制作一些数据。

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


Student = namedtuple('Student', ['name', 'grade', 'gender'])
Score = namedtuple('Score', ['value', 'unit', 'percentile'])


def to_ordinal(num):
    """Convert an integer to an ordinal string, e.g. 2 -> '2nd'."""
    suffixes = {str(i): v
                for i, v in enumerate(['th', 'st', 'nd', 'rd', 'th',
                                       'th', 'th', 'th', 'th', 'th'])}
    v = str(num)
    # special case early teens
    if v in {'11', '12', '13'}:
        return v + 'th'
    return v + suffixes[v[-1]]


def format_score(score):
    """
    Create score labels for the right y-axis as the test name followed by the
    measurement unit (if any), split over two lines.
    """
    return f'{score.value}\n{score.unit}' if score.unit else str(score.value)


def plot_student_results(student, scores_by_test, cohort_size):
    fig, ax1 = plt.subplots(figsize=(9, 7), constrained_layout=True)
    fig.canvas.manager.set_window_title('Eldorado K-8 Fitness Chart')

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

    test_names = list(scores_by_test.keys())
    percentiles = [score.percentile for score in scores_by_test.values()]

    rects = ax1.barh(test_names, percentiles, align='center', height=0.5)
    # Partition the percentile values to be able to draw large numbers in
    # white within the bar, and small numbers in black outside the bar.
    large_percentiles = [to_ordinal(p) if p > 40 else '' for p in percentiles]
    small_percentiles = [to_ordinal(p) if p <= 40 else '' for p in percentiles]
    ax1.bar_label(rects, small_percentiles,
                  padding=5, color='black', fontweight='bold')
    ax1.bar_label(rects, large_percentiles,
                  padding=-32, color='white', fontweight='bold')

    ax1.set_xlim([0, 100])
    ax1.set_xticks([0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100])
    ax1.xaxis.grid(True, linestyle='--', which='major',
                   color='grey', alpha=.25)
    ax1.axvline(50, color='grey', alpha=0.25)  # median position

    # Set the right-hand Y-axis ticks and labels
    ax2 = ax1.twinx()
    # Set equal limits on both yaxis so that the ticks line up
    ax2.set_ylim(ax1.get_ylim())
    # Set the tick locations and labels
    ax2.set_yticks(
        np.arange(len(scores_by_test)),
        labels=[format_score(score) for score in scores_by_test.values()])

    ax2.set_ylabel('Test Scores')


student = Student(name='Johnny Doe', grade=2, gender='Boy')
scores_by_test = {
    'Pacer Test': Score(7, 'laps', percentile=37),
    'Flexed Arm\n Hang': Score(48, 'sec', percentile=95),
    'Mile Run': Score('12:52', 'min:sec', percentile=73),
    'Agility': Score(17, 'sec', percentile=60),
    'Push Ups': Score(14, '', percentile=16),
}

plot_student_results(student, scores_by_test, cohort_size=62)
plt.show()

参考

此示例中显示了以下函数、方法、类和模块的使用：

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