Matplotlib形状代码:首选是折线图: # 导包import matplotlib.pyplot as plt# 导入字体库from matplotlib.font_manager import FontPropertiesfont = FontProperties(fname="C:/Windows/Fonts/simkai.ttf",size=15)# 填充数据# plt.plot(['3-1','3-2','3-3'],[1,10,9])# 绘制方法# plt.show()# 定制数据x1 = ['3-1','3-2','3-3','3-4','3-5']y1 = [2,6,4,9,7]x2 = ['3-1','3-2','3-3','3-4','3-5']y2 = [13,18,11,12,5]plt.plot(x1,y1,label='temperature')plt.plot(x2,y2,label='water')# 设置标题plt.title('温湿度显示图',FontProperties=font)plt.legend()plt.show() 树状图: # 导包import matplotlib.pyplot as plt# 导入字体库from matplotlib.font_manager import FontPropertiesfont = FontProperties(fname="C:/Windows/Fonts/simhei.ttf",size=15)# 设置数据salary = [9000,10000,12000,5000,4000]group = ['beijing','qinhuangdao','xingtai','handan','shijiazhuang']plt.bar(group,salary)plt.title('全国各市工资水平',FontProperties=font)plt.show() 散点图: # 导包import matplotlib.pyplot as plt# 导入字体库from matplotlib.font_manager import FontPropertiesimport numpy as npfont = FontProperties(fname="C:/Windows/Fonts/simhei.ttf",size=15)# 设置数据# plt.scatter(2,4)# 定义x轴数据x = list(range(0,101))y = [xvalue * np.random.rand() for xvalue in x]# 填充数据# s 代表点的大小,和粗细# c 点表点的颜色plt.scatter(x,y,s=20,c='skyblue')# 绘制plt.show() 还可以运用面向对象来吧 图形封装成类,以下是封装成面向对象的图形代码。# 导包import matplotlib.pyplot as plt# 定义一个绘图类class TestPlot(object):# 初始化赋值def __init__(self,plt):self.plt = plt#定义内部属性#解决中文乱码问题(第二种,第一种在d6中)# 'font.sans-serif' 是matplotlib的内置keyplt.rcParams['font.sans-serif'] = ['SimHei']plt.rcParams['font.family']='sans-serif'#指定编码plt.rcParams['axes.unicode_minus'] = False# 定义横向条形图def my_barh(self):my_plt = self.plt# 定义价格price = [40.7,55,66,42.3]# 将数据传入my_plt.barh(range(4),price,align='center',color='skyblue',alpha=0.5)# 设置标签my_plt.xlabel('价格')# 将数据传入y轴my_plt.yticks(range(4),['红楼梦','三国演义','西游记','水浒传'])# 设置上下限制my_plt.xlim([10,80])my_plt.title('四大名著')my_plt.show()# 定义柱状图def my_bar(self):my_plt =self.plt# 定义数据GDP = [11313.3,14131.3,14553.5,23452.6]# 传入数据my_plt.bar(['唐山','邢台','石家庄','邯郸'],GDP,align='center',color ='steelblue',alpha = 0.8)my_plt.ylabel('生产总值')my_plt.title('河北省GDP大比拼')# 刻度范围my_plt.ylim([5000,25000])my_plt.show()def my_pie(self):my_plt = self.plt # 定义数据xingtai = [44,22,16,18]# 定义标签label = ['2-3年','3-4年','5-6年','6年以上']color = ['red','skyblue','yellow','pink']indic = []# 使用enumerate方法来添加索引 for index,item in enumerate(xingtai):if item == max(xingtai):indic.append(0.5) elif index == 1:indic.append(0.3)else:indic.append(0) # if item == max(xingtai):# indic.append(0.1)# else:# indic.append(0)my_plt.pie(# 数据xingtai,# 标签labels=label,# 颜色colors=color,# 角度startangle=90,# 阴影shadow=True,# 突出显示explode=tuple(indic),# 格式化数字autopct='%1.1f%%',)# 设置标题my_plt.title('饼图示例-统计邢台工龄占比')my_plt.show()# 定义面积图方法def my_area(self):# 定义日期区间date = ['2019.3.1','2019.3.2','2019.3.3','2019.3.4','2019.3.5','2019.3.6']# 定义数据# 收入earn = [313,344,222,111,414,212] # 支出pay = [[15,44,33,56,33,77],[33,22,11,13,42,19]]self.plt.stackplot(date,earn,pay,colors=['skyblue','yellow','red'])# 生成图例self.plt.plot([],[],color='skyblue',label='收入')self.plt.plot([],[],color='yellow',label='午餐')self.plt.plot([],[],color='red',label='晚餐')# 设置标题self.plt.title('面积图例,统一六天收入')self.plt.legend()self.plt.show()if __name__ == "__main__":# 实例化一个对象testplot =TestPlot(plt)testplot.my_area()# testplot.my_bar()# testplot.my_pie()# testplot.my_barh() 以上全都是内置图形 ,还可以有扩展别的图形,例如小提琴图形。首选要下载一个 seaborn 包下载方式:pip install seaborn下载之后利用此代码,就可以生成小提琴形状的比例了。# 导包import numpy as npimport pandas as pdimport matplotlib.pyplot as pltimport seaborn as snsif __name__ == "__main__": # 读取数据集df = pd.read_excel('test.xlsx','sheet1')print(df)# 绘制小提琴图sns.violinplot(df['Age'],df['Gender'])# 初始化数据sns.despine()# 绘制plt.show()