Python matplotlib读取excel数据并用for循环画多个子图subplot操作,英语,总分,平均,数据,语文

Python matplotlib读取excel数据并用for循环画多个子图subplot操作

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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 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

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