读取excel数据需要用到xlrd模块，在命令行运行下面命令进行安装

pip install xlrd

表格内容大致如下，有若干sheet，每个sheet记录了同一所学校的所有学生成绩，分为语文、数学、英语、综合、总分

考号 姓名 班级 学校 语文 数学 英语 综合 总分 ... ... ... ... 136 136 100 57 429 ... ... ... ... 128 106 70 54 358 ... ... ... ... 110.5 62 92 44 308.5

画多张子图需要用到subplot函数

subplot(nrows, ncols, index, **kwargs)

想要在一张画布上按如下格式画多张子图

语文 --- 数学

英语 --- 综合

----- 总分 ----

需要用的subplot参数分别为

subplot(321) --- subplot(322)

subplot(323) --- subplot(324)

subplot(313)

#!/usr/bin/env python# -*- coding:utf-8 -*-from xlrd import open_workbook as owbimport matplotlib.pyplot as plt#import matplotlib.colors as colors#from matplotlib.ticker import MultipleLocator, FormatStrFormatter, FuncFormatterimport numpy as np districts=[] # 存储各校名称--对应于excel表格的sheet名data_index = 0new_colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']wb = owb('raw_data.xlsx') # 数据文件active_districts = ['二小','一小','四小'] ## 填写需要画哪些学校的，名字需要与表格内一致avg_yuwen = []avg_shuxue = []avg_yingyu = []avg_zonghe = []avg_total = []'按页数依次读取表格数据作为Y轴参数'for s in wb.sheets(): #以下两行用于控制是否全部绘图，还是只绘选择的区 #if s.name not in active_districts: # continue print('Sheet: ', s.name) districts.append(s.name) avg_score = 0 yuwen = 0 shuxue = 0 yingyu = 0 zonghe = 0 zongfen = 0 total_student = 0 for row in range(1,s.nrows): total_student += 1 #读取各科成绩并计算平均分 yuwen = yuwen + (s.cell(row, 4).value - yuwen)/total_student # 语文 shuxue = shuxue + (s.cell(row, 5).value - shuxue) / total_student # 数学 yingyu = yingyu + (s.cell(row, 6).value - yingyu) / total_student # 英语 zonghe = zonghe + (s.cell(row, 7).value - zonghe) / total_student # 综合 zongfen = zongfen + (s.cell(row, 8).value - zongfen) / total_student # 总分 avg_yuwen.append(yuwen) avg_shuxue.append(shuxue) avg_yingyu.append(yingyu) avg_zonghe.append(zonghe) avg_total.append(zongfen) data_index += 1 print('开始画图...')plt.rcParams['font.sans-serif']=['SimHei'] # 中文支持plt.rcParams['axes.unicode_minus']=False # 中文支持figsize = 11,14fig = plt.figure(figsize=figsize)fig.suptitle('各校各科成绩平均分统计',fontsize=18)my_x=np.arange(len(districts))width=0.5 ax1 = plt.subplot(321)#total_width=width*(len(districts))b = ax1.bar(my_x , avg_yuwen, width, tick_label=districts, align='center', color=new_colors)for i in range(0,len(avg_yuwen)): ax1.text(my_x[i], avg_yuwen[i], '%.2f' % (avg_yuwen[i]), ha='center', va='bottom',fontsize=10)ax1.set_title(u'语文')ax1.set_ylabel(u"平均分")ax1.set_ylim(60, 130) ax2 = plt.subplot(322)ax2.bar(my_x, avg_shuxue, width, tick_label=districts, align='center', color=new_colors)for i in range(0, len(avg_shuxue)): ax2.text(my_x[i], avg_shuxue[i], '%.2f' %(avg_shuxue[i]), ha='center', va='bottom', fontsize=10)ax2.set_title(u'数学')ax2.set_ylabel(u'平均分')ax2.set_ylim(50,120) ax3 = plt.subplot(323)b = ax3.bar(my_x , avg_yingyu, width, tick_label=districts, align='center', color=new_colors)for i in range(0,len(avg_yingyu)): ax3.text(my_x[i], avg_yingyu[i], '%.2f' % (avg_yingyu[i]), ha='center', va='bottom',fontsize=10)ax3.set_title(u'英语')ax3.set_ylabel(u"平均分")ax3.set_ylim(30, 100) ax4 = plt.subplot(324)b = ax4.bar(my_x , avg_zonghe, width, tick_label=districts, align='center', color=new_colors)for i in range(0,len(avg_zonghe)): ax4.text(my_x[i], avg_zonghe[i], '%.2f' % (avg_zonghe[i]), ha='center', va='bottom',fontsize=10)ax4.set_title(u'综合')ax4.set_ylabel(u"平均分")ax4.set_ylim(0, 60) ax5 = plt.subplot(313)total_width=width*(len(districts))b = ax5.bar(my_x , avg_total, width, tick_label=districts, align='center', color=new_colors)for i in range(0,len(avg_total)): ax5.text(my_x[i], avg_total[i], '%.2f' % (avg_total[i]), ha='center', va='bottom',fontsize=10)ax5.set_title(u'总分')ax5.set_ylabel(u"平均分")ax5.set_ylim(250, 400) plt.savefig('avg.png')plt.show()

这样虽然能画出来，但是需要手动写每个subplot的代码，代码重复量太大，能不能用for循环的方式呢？

继续尝试，

先整理出for循环需要的不同参数

avg_scores = [] # 存储各科成绩，2维listsubjects = ['语文','数学','英语','综合','总分'] #每个子图的titleplot_pos = [321,322,323,324,313] # 每个子图的位置y_lims = [(60,130), (50,120), (30,100), (0,60), (200,400)] # 每个子图的ylim参数

数据读取的修改比较简单，但是到画图时，如果还用 ax = plt.subplots(plot_pos[pos])方法的话，会报错

Traceback (most recent call last): File "...xxx.py", line 66, in <module> b = ax.bar(my_x , y_data, width, tick_label=districts, align='center', color=new_colors) # 画柱状图AttributeError: 'tuple' object has no attribute 'bar'

搜索一番，没找到合适的答案，想到可以换fig.add_subplot(plot_pos[pos]) 试一试，结果成功了，整体代码如下

#!/usr/bin/env python# -*- coding:utf-8 -*-from xlrd import open_workbook as owbimport matplotlib.pyplot as plt#import matplotlib.colors as colors#from matplotlib.ticker import MultipleLocator, FormatStrFormatter, FuncFormatterimport numpy as np districts=[] # 存储各校名称--对应于excel表格的sheet名total_stu=[] # 存储各区学生总数data_index = 0new_colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']wb = owb('raw_data.xlsx') # 数据文件active_districts = ['BY','二小','一小','WR','四小'] ## 填写需要画哪些学校的，名字需要与表格内一致avg_scores = [] # 存储各科成绩，2维listsubjects = ['语文','数学','英语','综合','总分'] #每个子图的titleplot_pos = [321,322,323,324,313] # 每个子图的位置y_lims = [(60,130), (50,120), (30,100), (0,60), (200,400)] # 每个子图的ylim参数 '按页数依次读取表格数据作为Y轴参数'for s in wb.sheets(): #以下两行用于控制是否全部绘图，还是只绘选择的区 #if s.name not in active_districts: # continue print('Sheet: ', s.name) districts.append(s.name) avg_scores.append([]) yuwen = 0 shuxue = 0 yingyu = 0 zonghe = 0 zongfen = 0 total_student = 0 for row in range(1,s.nrows): total_student += 1 #tmp = s.cell(row,4).value yuwen = yuwen + (s.cell(row, 4).value - yuwen)/total_student # 语文 shuxue = shuxue + (s.cell(row, 5).value - shuxue) / total_student # 数学 yingyu = yingyu + (s.cell(row, 6).value - yingyu) / total_student # 英语 zonghe = zonghe + (s.cell(row, 7).value - zonghe) / total_student # 综合 zongfen = zongfen + (s.cell(row, 8).value - zongfen) / total_student # 总分 avg_scores[data_index].append(yuwen) avg_scores[data_index].append(shuxue) avg_scores[data_index].append(yingyu) avg_scores[data_index].append(zonghe) avg_scores[data_index].append(zongfen) data_index += 1 print('开始画图...')plt.rcParams['font.sans-serif']=['SimHei']plt.rcParams['axes.unicode_minus']=Falsefigsize = 11,14fig = plt.figure(figsize=figsize)fig.suptitle('各校各科成绩平均分统计',fontsize=18)my_x=np.arange(len(districts))width=0.5 print(avg_scores)for pos in np.arange(len(plot_pos)): #ax = plt.subplots(plot_pos[pos]) ax = fig.add_subplot(plot_pos[pos]) # 如果用ax = plt.subplots会报错'tuple' object has no attribute 'bar' y_data = [x[pos] for x in avg_scores] # 按列取数据 print(y_data) b = ax.bar(my_x , y_data, width, tick_label=districts, align='center', color=new_colors) # 画柱状图 for i in np.arange(len(y_data)): ax.text(my_x[i], y_data[i], '%.2f' % (y_data[i]), ha='center', va='bottom',fontsize=10) # 添加文字 ax.set_title(subjects[pos]) ax.set_ylabel(u"平均分") ax.set_ylim(y_lims[pos]) plt.savefig('jh_avg_auto.png')plt.show()

和之前的结果一样，能找到唯一一处细微差别嘛

以上这篇Python matplotlib读取excel数据并用for循环画多个子图subplot操作就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。