Python matplotlib讀取excel數(shù)據(jù)并用for循環(huán)畫多個(gè)子圖subplot操作

更新時(shí)間：2020年07月14日 09:35:01 作者：李逐風(fēng)

這篇文章主要介紹了Python matplotlib讀取excel數(shù)據(jù)并用for循環(huán)畫多個(gè)子圖subplot操作，具有很好的參考價(jià)值，希望對大家有所幫助。一起跟隨小編過來看看吧

讀取excel數(shù)據(jù)需要用到xlrd模塊，在命令行運(yùn)行下面命令進(jìn)行安裝

pip install xlrd

表格內(nèi)容大致如下，有若干sheet，每個(gè)sheet記錄了同一所學(xué)校的所有學(xué)生成績，分為語文、數(shù)學(xué)、英語、綜合、總分

考號(hào)	姓名	班級(jí)	學(xué)校	語文	數(shù)學(xué)	英語	綜合	總分
...	...	...	...	136	136	100	57	429
...	...	...	...	128	106	70	54	358
...	...	...	...	110.5	62	92	44	308.5

畫多張子圖需要用到subplot函數(shù)

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

想要在一張畫布上按如下格式畫多張子圖

語文 --- 數(shù)學(xué)

英語 --- 綜合

----- 總分 ----

需要用的subplot參數(shù)分別為

subplot(321) --- subplot(322)

subplot(323) --- subplot(324)

subplot(313)

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from xlrd import open_workbook as owb
import matplotlib.pyplot as plt
#import matplotlib.colors as colors
#from matplotlib.ticker import MultipleLocator, FormatStrFormatter, FuncFormatter
import numpy as np
 
districts=[] # 存儲(chǔ)各校名稱--對應(yīng)于excel表格的sheet名
data_index = 0
new_colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728',
    '#9467bd', '#8c564b', '#e377c2', '#7f7f7f',
    '#bcbd22', '#17becf']
wb = owb('raw_data.xlsx') # 數(shù)據(jù)文件
active_districts = ['二小','一小','四小'] ## 填寫需要畫哪些學(xué)校的，名字需要與表格內(nèi)一致
avg_yuwen = []
avg_shuxue = []
avg_yingyu = []
avg_zonghe = []
avg_total = []
'按頁數(shù)依次讀取表格數(shù)據(jù)作為Y軸參數(shù)'
for s in wb.sheets():
 #以下兩行用于控制是否全部繪圖，還是只繪選擇的區(qū)
 #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
  #讀取各科成績并計(jì)算平均分
  yuwen = yuwen + (s.cell(row, 4).value - yuwen)/total_student # 語文
  shuxue = shuxue + (s.cell(row, 5).value - shuxue) / total_student # 數(shù)學(xué)
  yingyu = yingyu + (s.cell(row, 6).value - yingyu) / total_student # 英語
  zonghe = zonghe + (s.cell(row, 7).value - zonghe) / total_student # 綜合
  zongfen = zongfen + (s.cell(row, 8).value - zongfen) / total_student # 總分
 avg_yuwen.append(yuwen)
 avg_shuxue.append(shuxue)
 avg_yingyu.append(yingyu)
 avg_zonghe.append(zonghe)
 avg_total.append(zongfen)
 data_index += 1
 
print('開始畫圖...')
plt.rcParams['font.sans-serif']=['SimHei'] # 中文支持
plt.rcParams['axes.unicode_minus']=False # 中文支持
figsize = 11,14
fig = plt.figure(figsize=figsize)
fig.suptitle('各校各科成績平均分統(tǒng)計(jì)',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'語文')
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'數(shù)學(xué)')
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'英語')
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'綜合')
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'總分')
ax5.set_ylabel(u"平均分")
ax5.set_ylim(250, 400)
 
plt.savefig('avg.png')
plt.show()

這樣雖然能畫出來，但是需要手動(dòng)寫每個(gè)subplot的代碼，代碼重復(fù)量太大，能不能用for循環(huán)的方式呢？

繼續(xù)嘗試，

先整理出for循環(huán)需要的不同參數(shù)

avg_scores = [] # 存儲(chǔ)各科成績，2維list
subjects = ['語文','數(shù)學(xué)','英語','綜合','總分'] #每個(gè)子圖的title
plot_pos = [321,322,323,324,313] # 每個(gè)子圖的位置
y_lims = [(60,130), (50,120), (30,100), (0,60), (200,400)] # 每個(gè)子圖的ylim參數(shù)

數(shù)據(jù)讀取的修改比較簡單，但是到畫圖時(shí)，如果還用 ax = plt.subplots(plot_pos[pos])方法的話，會(huì)報(bào)錯(cuò)

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) # 畫柱狀圖
AttributeError: 'tuple' object has no attribute 'bar'

搜索一番，沒找到合適的答案，想到可以換fig.add_subplot(plot_pos[pos]) 試一試，結(jié)果成功了，整體代碼如下

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from xlrd import open_workbook as owb
import matplotlib.pyplot as plt
#import matplotlib.colors as colors
#from matplotlib.ticker import MultipleLocator, FormatStrFormatter, FuncFormatter
import numpy as np
 
districts=[] # 存儲(chǔ)各校名稱--對應(yīng)于excel表格的sheet名
total_stu=[] # 存儲(chǔ)各區(qū)學(xué)生總數(shù)
data_index = 0
new_colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728',
    '#9467bd', '#8c564b', '#e377c2', '#7f7f7f',
    '#bcbd22', '#17becf']
wb = owb('raw_data.xlsx') # 數(shù)據(jù)文件
active_districts = ['BY','二小','一小','WR','四小'] ## 填寫需要畫哪些學(xué)校的，名字需要與表格內(nèi)一致
avg_scores = [] # 存儲(chǔ)各科成績，2維list
subjects = ['語文','數(shù)學(xué)','英語','綜合','總分'] #每個(gè)子圖的title
plot_pos = [321,322,323,324,313] # 每個(gè)子圖的位置
y_lims = [(60,130), (50,120), (30,100), (0,60), (200,400)] # 每個(gè)子圖的ylim參數(shù)
 
'按頁數(shù)依次讀取表格數(shù)據(jù)作為Y軸參數(shù)'
for s in wb.sheets():
 #以下兩行用于控制是否全部繪圖，還是只繪選擇的區(qū)
 #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 # 語文
  shuxue = shuxue + (s.cell(row, 5).value - shuxue) / total_student # 數(shù)學(xué)
  yingyu = yingyu + (s.cell(row, 6).value - yingyu) / total_student # 英語
  zonghe = zonghe + (s.cell(row, 7).value - zonghe) / total_student # 綜合
  zongfen = zongfen + (s.cell(row, 8).value - zongfen) / total_student # 總分
 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('開始畫圖...')
plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['axes.unicode_minus']=False
figsize = 11,14
fig = plt.figure(figsize=figsize)
fig.suptitle('各校各科成績平均分統(tǒng)計(jì)',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會(huì)報(bào)錯(cuò)'tuple' object has no attribute 'bar'
 y_data = [x[pos] for x in avg_scores] # 按列取數(shù)據(jù)
 print(y_data)
 b = ax.bar(my_x , y_data, width, tick_label=districts, align='center', color=new_colors) # 畫柱狀圖
 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()

和之前的結(jié)果一樣，能找到唯一一處細(xì)微差別嘛