python数据可视化matplotlib专题：带数据标签的双batch的Bar图绘制示例

基于matplotlib的双Batch带标签bar图生成函数

李俊才
邮箱&＃xff1a;291148484&＃64;163.com

【代码实现】

import matplotlib
import matplotlib.pyplot as plt
import numpy as npdef barchart_ax_2Batch(title,xlabel,ylabel,batch1_name,batch2_name,x_text,batch1,batch2,background_color,Batch1_color,Batch2_color):plt.rcParams[&＃39;font.sans-serif&＃39;] &＃61; [&＃39;KaiTi&＃39;] # 指定默认字体以解决中文乱码x &＃61; np.arange(len(x_text))width &＃61; 0.35fig, ax &＃61; plt.subplots()rects1 &＃61; ax.bar(x - width/2, batch1, width, label &＃61; batch1_name, color &＃61; Batch1_color) #- width/2右移一半宽度rects2 &＃61; ax.bar(x &＃43; width/2, batch2, width, label &＃61; batch2_name, color &＃61; Batch2_color) #&＃43; width/2左移一半宽度 否则两图会重合ax.patch.set_facecolor(background_color) #设置背景色# 设置各种标签名称的数据来源ax.set_title(title) #添加标题ax.set_xlabel(xlabel) #添加横轴标题&＃xff08;标签&＃xff09;ax.set_ylabel(ylabel) #添加纵轴标题&＃xff08;标签&＃xff09;ax.set_xticks(x) #以列表x中的内容为所作图横轴刻度ax.set_xticklabels(x_text) #添加横轴数据/文本ax.legend() #添加图例#为Batch1添加数据标签for rect in rects1:height &＃61; rect.get_height()ax.annotate(&＃39;{}&＃39;.format(height), xy&＃61;(rect.get_x() &＃43; rect.get_width() / 2, height),xytext&＃61;(0,3), # 3 points vertical offsettextcoords&＃61;"offset points",ha&＃61;&＃39;center&＃39;, va&＃61;&＃39;bottom&＃39;)#为Batch2添加数据标签for rect in rects2:height &＃61; rect.get_height()ax.annotate(&＃39;{}&＃39;.format(height), xy&＃61;(rect.get_x() &＃43; rect.get_width() / 2, height),xytext&＃61;(0,3), textcoords&＃61;"offset points",ha&＃61;&＃39;center&＃39;, va&＃61;&＃39;bottom&＃39;)plt.grid(linestyle &＃61; "dotted",color &＃61; "r") #添加网格线fig.tight_layout()plt.show()


【调用实例】

新手调用时&＃xff0c;请尽量按照两部走的原则&＃xff1a;

• 1.先定义各种待传入函数接口的数据&＃xff0c;
• 2.调用函数。
  参数很多时不要把所有参数的取值都写到调用函数处&＃xff0c;这样将降低可读性。

#定义各种名称
title &＃61; &＃39;期末平均考成绩比较图&＃39;
xlabel &＃61; &＃39;科目&＃39;
ylabel &＃61; &＃39;得分&＃39;
batch1_name &＃61; &＃39;高2020-07班&＃39;
batch2_name &＃61; &＃39;高2020-09班&＃39;
#定义数据值
x_text &＃61; [&＃39;语文&＃39;, &＃39;数学&＃39;, &＃39;英语&＃39;, &＃39;物理&＃39;, &＃39;化学&＃39; ,&＃39;生物&＃39;]
batch1 &＃61; [87, 118, 101, 106, 76, 71]
batch2 &＃61; [112, 97, 116, 99, 89, 83]
#定义颜色
background_color &＃61; "lightskyblue"
Batch1_color &＃61; "red"
Batch2_color &＃61; "blue"
#最后调用函数以绘图
barchart_ax_2Batch(title,xlabel,ylabel,batch1_name,batch2_name,x_text,batch1,batch2,background_color,Batch1_color,Batch2_color)


生成图片效果如下&＃xff1a;

内容仅供参考&＃xff0c;如需使用请指明出处。

202012.29.更新/回复

【事项记录】&＃xff1a;有同学留言&＃xff0c;说想要绘制百分比标签的。其实这不难。可以如下思路操作&＃xff1a;

• 1.输入数据前先表列表中的数据标准化&＃xff0c;即处理成百分数的一百倍。比如百分之97.15%则处理成97.15
• 2.对函数中格式化操作稍微更改。
  还是用上面的数据举个栗子吧&＃xff0c;假设我们想得到两个班同学各科成绩占满分的占比。

import matplotlib
import matplotlib.pyplot as plt
import seaborn as snsdef bar_2batch( x_labels,y1,y2,title&＃61;None,xtitle&＃61;None,ytitle&＃61;None,legend1&＃61;None,legend2&＃61;None,background_color&＃61;"#ffffff",Batch1_color&＃61;"#5B9BD5",Batch2_color&＃61;"#ED7D31"):plt.rcParams[&＃39;font.sans-serif&＃39;] &＃61; [&＃39;KaiTi&＃39;]pylab.rcParams[&＃39;figure.figsize&＃39;] &＃61; (7.0, 4.0)x &＃61; np.arange(len(x_labels))width &＃61; 0.25fig, ax &＃61; plt.subplots()rects1 &＃61; ax.bar(x - width/2, y1, width, label &＃61; legend1, color &＃61; Batch1_color) rects2 &＃61; ax.bar(x &＃43; width/2, y2, width, label &＃61; legend2, color &＃61; Batch2_color) ax.patch.set_facecolor(background_color)ax.set_title(title)ax.set_xlabel(xtitle)ax.set_ylabel(ytitle) ax.set_xticks(x) ax.set_xticklabels(x_labels)if (legend1 is not None) or (legend1 is not None): ax.legend()def add_dlb(rects):for rect in rects:height &＃61; rect.get_height()ax.annotate(&＃39;{0:.2f}%&＃39;.format(height), xy&＃61;(rect.get_x() &＃43; rect.get_width() / 2, height),xytext&＃61;(0,3), textcoords&＃61;"offset >points", ha&＃61;&＃39;center&＃39;, va&＃61;&＃39;bottom&＃39;)add_dlb(rects1)add_dlb(rects2)plt.grid(linestyle &＃61; "-",color &＃61; "#DBDBDB") fig.tight_layout()plt.show()# 定义各种名称
title &＃61; &＃39;两班学生各科目成绩满分比&＃39;
xtitle &＃61; &＃39;科目&＃39;
ytitle &＃61; &＃39;得分&＃39;
legend1 &＃61; &＃39;高2020-07班&＃39;
legend2 &＃61; &＃39;高2020-09班&＃39;
# 定义数据值
x_labels &＃61; [&＃39;语文&＃39;, &＃39;数学&＃39;, &＃39;英语&＃39;, &＃39;物理&＃39;, &＃39;化学&＃39; ,&＃39;生物&＃39;]
y1 &＃61; [87/150*100, 118/150*100, 101/150*100, 96/100*100, 76/100*100, 71/100*100]
y2 &＃61; [112/150*100, 97/150*100, 116/150*100, 99/100*100, 89/100*100, 83/100*100]# 最后调用函数以绘图
bar_2batch(x_labels,y1,y2,title&＃61;title,legend1&＃61;legend1,legend2&＃61;legend2)


效果如图所示&＃xff1a;

由于定义了默认参数&＃xff0c;当不需要要标题等参数的时候&＃xff0c;你甚至也可以只给出数据。比如&＃xff1a;

bar_2batch(x_labels,y1,y2)


其运行结果为&＃xff1a;

import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pylab
import seaborn as sns
sns.set(style&＃61;"darkgrid")def bar_1batch( x_labels,y1,title&＃61;None,xtitle&＃61;None,ytitle&＃61;None,legend1&＃61;None,Batch1_color&＃61;"#5B9BD5"):plt.rcParams[&＃39;font.sans-serif&＃39;] &＃61; [&＃39;KaiTi&＃39;] # 指定默认字体以解决中文乱码x &＃61; np.arange(len(x_labels))width &＃61; 0.75fig, ax &＃61; plt.subplots()rects1 &＃61; ax.bar(x - width/2, y1, width, label &＃61; legend1, color &＃61; Batch1_color)if legend1 !&＃61; None:ax.legend() #添加图例ax.set_title(title) #添加标题ax.set_xlabel(xtitle) #添加横轴标题&＃xff08;标签&＃xff09;ax.set_ylabel(ytitle) #添加纵轴标题&＃xff08;标签&＃xff09;ax.set_xticks(x) #以列表x中的内容为所作图横轴刻度ax.set_xticklabels(x_labels) #添加横轴数据/文本pylab.rcParams[&＃39;figure.figsize&＃39;] &＃61; (16.0, 5.0)plt.rcParams[&＃39;font.sans-serif&＃39;] &＃61; [&＃39;KaiTi&＃39;]matplotlib.rcParams[&＃39;axes.unicode_minus&＃39;] &＃61; Falsedef add_dlb(rects):for rect in rects:height &＃61; rect.get_height()ax.annotate(&＃39;{}&＃39;.format(height), xy&＃61;(rect.get_x() &＃43; rect.get_width() / 2, height),xytext&＃61;(0,3), textcoords&＃61;"offset points", ha&＃61;&＃39;center&＃39;, va&＃61;&＃39;bottom&＃39;)add_dlb(rects1)plt.grid(linestyle &＃61; "-",color &＃61; "#DBDBDB")fig.tight_layout()plt.show()# 定义数据
n&＃61;36
x_labels &＃61; [str(i) for i in range(n)]
y1 &＃61; np.random.randint(10,90,size&＃61;(1,n),dtype&＃61;int)[0]#最后调用写好的函数绘图
bar_1batch(x_labels,y1)

在jupyter中运行结果如下图所示&＃xff1a;

这样就控制图像的大小让我们看起来更“爽”。