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量。还可以参阅 带有标签的组合条形图水平条形图 示例以了解这些功能的更简单版本。

本示例来自一个应用程序,其中小学体育老师希望能够向家长展示孩子在一些体能测试中的表现,重要的是,要相对于其他孩子的表现来看。为了提取绘图代码以供演示,我们将只为小约翰·多伊编造一些数据。

from collections import namedtuple

import matplotlib.pyplot as plt
import numpy as np

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), layout='constrained')
    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()
Johnny Doe

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