# 条形图演示 使用Matplotlib的许多形状和大小的条形图。 条形图对于可视化计数或带有误差栏的汇总统计信息非常有用。这些示例显示了使用Matplotlib执行此操作的几种方法。 ```python # Credit: Josh Hemann import numpy as np import matplotlib.pyplot as plt from matplotlib.ticker import MaxNLocator from collections import namedtuple n_groups = 5 means_men = (20, 35, 30, 35, 27) std_men = (2, 3, 4, 1, 2) means_women = (25, 32, 34, 20, 25) std_women = (3, 5, 2, 3, 3) fig, ax = plt.subplots() index = np.arange(n_groups) bar_width = 0.35 opacity = 0.4 error_config = {'ecolor': '0.3'} rects1 = ax.bar(index, means_men, bar_width, alpha=opacity, color='b', yerr=std_men, error_kw=error_config, label='Men') rects2 = ax.bar(index + bar_width, means_women, bar_width, alpha=opacity, color='r', yerr=std_women, error_kw=error_config, label='Women') ax.set_xlabel('Group') ax.set_ylabel('Scores') ax.set_title('Scores by group and gender') ax.set_xticks(index + bar_width / 2) ax.set_xticklabels(('A', 'B', 'C', 'D', 'E')) ax.legend() fig.tight_layout() plt.show() ``` ![条形图演示](https://matplotlib.org/_images/sphx_glr_barchart_demo_001.png) 这个例子来自一个应用程序，在这个应用程序中，小学体育教师希望能够向父母展示他们的孩子在一些健身测试中的表现，而且重要的是，相对于其他孩子的表现。 为了演示目的提取绘图代码，我们只为小Johnny Doe编制一些数据...... ```python Student = namedtuple('Student', ['name', 'grade', 'gender']) Score = namedtuple('Score', ['score', 'percentile']) # GLOBAL CONSTANTS testNames = ['Pacer Test', 'Flexed Arm\n Hang', 'Mile Run', 'Agility', 'Push Ups'] testMeta = dict(zip(testNames, ['laps', 'sec', 'min:sec', 'sec', ''])) def attach_ordinal(num): """helper function to add ordinal string to integers 1 -> 1st 56 -> 56th """ 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(scr, test): """ Build up the score labels for the right Y-axis by first appending a carriage return to each string and then tacking on the appropriate meta information (i.e., 'laps' vs 'seconds'). We want the labels centered on the ticks, so if there is no meta info (like for pushups) then don't add the carriage return to the string """ md = testMeta[test] if md: return '{0}\n{1}'.format(scr, md) else: return scr def format_ycursor(y): y = int(y) if y < 0 or y >= len(testNames): return '' else: return testNames[y] def plot_student_results(student, scores, cohort_size): # create the figure fig, ax1 = plt.subplots(figsize=(9, 7)) fig.subplots_adjust(left=0.115, right=0.88) fig.canvas.set_window_title('Eldorado K-8 Fitness Chart') pos = np.arange(len(testNames)) rects = ax1.barh(pos, [scores[k].percentile for k in testNames], align='center', height=0.5, color='m', tick_label=testNames) ax1.set_title(student.name) ax1.set_xlim([0, 100]) ax1.xaxis.set_major_locator(MaxNLocator(11)) ax1.xaxis.grid(True, linestyle='--', which='major', color='grey', alpha=.25) # 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() scoreLabels = [format_score(scores[k].score, k) for k in testNames] # set the tick locations ax2.set_yticks(pos) # make sure that the limits are set equally on both yaxis so the # ticks line up ax2.set_ylim(ax1.get_ylim()) # set the tick labels ax2.set_yticklabels(scoreLabels) 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())) rect_labels = [] # Lastly, write in the ranking inside each bar to aid in interpretation for rect in rects: # Rectangle widths are already integer-valued but are floating # type, so it helps to remove the trailing decimal point and 0 by # converting width to int type width = int(rect.get_width()) rankStr = attach_ordinal(width) # The bars aren't wide enough to print the ranking inside if width < 5: # Shift the text to the right side of the right edge xloc = width + 1 # Black against white background clr = 'black' align = 'left' else: # Shift the text to the left side of the right edge xloc = 0.98*width # White on magenta clr = 'white' align = 'right' # Center the text vertically in the bar yloc = rect.get_y() + rect.get_height()/2.0 label = ax1.text(xloc, yloc, rankStr, horizontalalignment=align, verticalalignment='center', color=clr, weight='bold', clip_on=True) rect_labels.append(label) # make the interactive mouse over give the bar title ax2.fmt_ydata = format_ycursor # return all of the artists created return {'fig': fig, 'ax': ax1, 'ax_right': ax2, 'bars': rects, 'perc_labels': rect_labels, 'cohort_label': cohort_label} student = Student('Johnny Doe', 2, 'boy') scores = dict(zip(testNames, (Score(v, p) for v, p in zip(['7', '48', '12:52', '17', '14'], np.round(np.random.uniform(0, 1, len(testNames))*100, 0))))) cohort_size = 62 # The number of other 2nd grade boys arts = plot_student_results(student, scores, cohort_size) plt.show() ``` ![条形图演示2](https://matplotlib.org/_images/sphx_glr_barchart_demo_002.png) ## 下载这个示例 - [下载python源码: barchart_demo.py](https://matplotlib.org/_downloads/barchart_demo.py) - [下载Jupyter notebook: barchart_demo.ipynb](https://matplotlib.org/_downloads/barchart_demo.ipynb)