matplotlib各种案例总结（python经典编程案例）-阿里云开发者社区

一. 绘制基本图表

颜色color和简写：

红色 r: red
绿色 g: green
蓝色 b: blue
青色 c: cyan
洋红色 m: magenta
黄色 y: yellow
黑色 k: black
白色 w: white

1.1 绘制柱状图

import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5, 6, 7, 8]
y = [60, 45, 49, 36, 42, 67, 40, 50]
plt.bar(x, y)
plt.show()

import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5, 6, 7, 8]
y = [60, 45, 49, 36, 42, 67, 40, 50]
plt.bar(x, y, width = 0.5, color = 'r')
plt.show()

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['上海', '成都', '重庆', '深圳', '北京', '长沙', '南京', '青岛']
y = [60, 45, 49, 36, 42, 67, 40, 50]
plt.bar(x, y, width = 0.5, color = 'r')
plt.show()

1.2 绘制条形图

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['上海', '成都', '重庆', '深圳', '北京', '长沙', '南京', '青岛']
y = [60, 45, 49, 36, 42, 67, 40, 50]
plt.barh(x, y, height = 0.5, color = 'r')
plt.show()

1.3 绘制折线图

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['1月', '2月', '3月', '4月', '5月', '6月', '7月', '8月', '9月', '10月', '11月', '12月']
y = [50, 45, 65, 76, 75, 85, 55, 78, 86, 89, 94, 90]
plt.plot(x, y, color = 'r', linestyle = 'dashdot', linewidth = 2)
plt.show()

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['1月', '2月', '3月', '4月', '5月', '6月', '7月', '8月', '9月', '10月', '11月', '12月']
y = [50, 45, 65, 76, 75, 85, 55, 78, 86, 89, 94, 90]
plt.plot(x, y, color = 'r', linestyle = 'dashdot', linewidth = 2, marker = '*', markersize = 10)
plt.show()

1.4 绘制面积图

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['1月', '2月', '3月', '4月', '5月', '6月', '7月', '8月', '9月', '10月', '11月', '12月']
y = [50, 45, 65, 76, 75, 85, 55, 78, 86, 89, 94, 90]
plt.stackplot(x, y, color = 'r')
# plt.show()
plt.savefig('1_4绘制面积图.png')

1.5 绘制散点图

import pandas as pd
import matplotlib.pyplot as plt
data = pd.read_excel('汽车速度和刹车距离表.xlsx') 
x = data['汽车速度(km/h)']
y = data['刹车距离(m)'] 
plt.scatter(x, y, s = 100, color = 'r', marker = 'o', edgecolor = 'k') 
plt.show()

import pandas as pd
import matplotlib.pyplot as plt
from sklearn import linear_model
data = pd.read_excel('汽车速度和刹车距离表.xlsx') 
x = data['汽车速度(km/h)']
y = data['刹车距离(m)'] 
plt.scatter(x, y, s = 100, color = 'r', marker = 'o', edgecolor = 'k')
model = linear_model.LinearRegression().fit(x.values.reshape(-1,1), y)
pred = model.predict(x.values.reshape(-1,1)) 
plt.plot(x, pred,  color = 'k', linewidth = 3, linestyle = 'solid')
plt.show()

1.6 绘制饼图和圆环图

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['上海', '成都', '重庆', '深圳', '北京', '青岛', '南京']
y = [10, 45, 25, 36, 45, 56, 78]
plt.pie(y, labels = x, labeldistance = 1.1, autopct = '%.2f%%', pctdistance = 1.5)
plt.show()

plt.pie(y, labels = x, labeldistance = 1.1, autopct = '%.2f%%', pctdistance = 1.5, explode = [0,0,0,0,0,0.3,0], startangle = 90, counterclock = False)
plt.show()


import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['上海', '成都', '重庆', '深圳', '北京', '青岛', '南京']
y = [10, 45, 25, 36, 45, 56, 78]
plt.pie(y, labels = x, labeldistance = 1.1, autopct = '%.2f%%', pctdistance = 1.5, wedgeprops = {
   'width' : 0.3, 'linewidth' : 2, 'edgecolor' : 'white'})
plt.show()

二. 图表的绘制和美化技巧

2.1 在一张画布中绘制多张图表

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['1月', '2月', '3月', '4月', '5月', '6月', '7月', '8月', '9月', '10月', '11月', '12月']
y = [50, 45, 65, 76, 75, 85, 55, 78, 86, 89, 94, 90]
plt.subplot(2, 2, 1)
plt.pie(y, labels = x, labeldistance = 1.1, startangle = 90, counterclock = False)
plt.subplot(2, 2, 2)
plt.bar(x, y, width = 0.5, color = 'r')
plt.subplot(2, 2, 3)
plt.stackplot(x, y, color = 'r')
plt.subplot(2, 2, 4)
plt.plot(x, y, color = 'r', linestyle = 'solid', linewidth = 2, marker = 'o', markersize = 10)
plt.show()

2.2 添加图表元素

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['1月', '2月', '3月', '4月', '5月', '6月', '7月', '8月', '9月', '10月', '11月', '12月']
y = [50, 45, 65, 76, 75, 85, 55, 78, 86, 89, 94, 90]
plt.bar(x, y, width=0.6, color='r', label='销售额(万元)')
plt.title(label='销售额对比图', fontdict={
   'family': 'KaiTi', 'color': 'k', 'size': 30}, loc='center')
plt.xlabel('月份', fontdict={
   'family': 'SimSun', 'color': 'k', 'size': 20}, labelpad=20)  
plt.ylabel('销售额', fontdict={
   'family': 'SimSun', 'color': 'k', 'size': 20}, labelpad=20)  
plt.legend(loc='upper left', fontsize=15)
for a,b in zip(x, y):
    plt.text(x=a, y=b, s=b, ha='center', va='bottom', fontdict={
   'family': 'KaiTi', 'color': 'k', 'size': 20})
plt.show()

2.3 添加并设置网格线

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['1月', '2月', '3月', '4月', '5月', '6月', '7月', '8月', '9月', '10月', '11月', '12月']
y = [50, 45, 65, 76, 75, 85, 55, 78, 86, 89, 94, 90]
plt.plot(x, y, color = 'r', linestyle = 'solid', linewidth = 2)
plt.title(label = '销售额趋势图',fontdict = {
   'family' : 'KaiTi', 'color' : 'k', 'size' : 30}, loc = 'center')
plt.xlabel('月份', fontdict = {
   'family' : 'SimSun', 'color' : 'k', 'size' : 20}, labelpad = 20)  
plt.ylabel('销售额(万元)', fontdict = {
   'family' : 'SimSun', 'color' : 'k', 'size' : 20}, labelpad = 20)  
plt.grid(b = True, color = 'r', linestyle = 'dotted', linewidth = 1) 
plt.show()

plt.grid(b = True, axis = 'y', color = 'r', linestyle = 'dotted', linewidth = 1) 
plt.show()

2.4 调整坐标轴的刻度范围

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['1月', '2月', '3月', '4月', '5月', '6月', '7月', '8月', '9月', '10月', '11月', '12月']
y = [50, 45, 65, 76, 75, 85, 55, 78, 86, 89, 94, 90]
plt.plot(x, y, color = 'r', linestyle = 'solid', linewidth = 2, label = '销售额(万元)')
plt.title(label = '销售额趋势图',fontdict = {
   'family' : 'KaiTi', 'color' : 'k', 'size' : 30}, loc = 'center')
plt.legend(loc = 'upper left', fontsize = 15)
for a,b in zip(x, y):
    plt.text(a, b, b, ha = 'center', va = 'bottom', fontdict = {
   'family' : 'KaiTi', 'color' : 'k', 'size': 20})
plt.ylim(40, 100)
plt.show()

plt.axis('off')

三. 绘制高级图表

3.1 绘制气泡图

import matplotlib.pyplot as plt
import pandas as pd
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
data = pd.read_excel('产品销售统计.xlsx')
n = data['产品名称']
x = data['销售量(件)']
y = data['销售额(元)']
z = data['毛利率(%)']
plt.scatter(x, y, s=z * 300, color='r', marker='o')
plt.xlabel('销售量(件)', fontdict={
   'family': 'Microsoft YaHei', 'color': 'k', 'size': 20}, labelpad=20)
plt.ylabel('销售额(元)', fontdict={
   'family': 'Microsoft YaHei', 'color': 'k', 'size': 20}, labelpad=20)
plt.title('销售量、销售额与毛利率关系图', fontdict={
   'family': 'Microsoft YaHei', 'color': 'k', 'size': 30}, loc='center')
for a, b, c in zip(x, y, n):
    plt.text(x=a, y=b, s=c, ha='center', va='center', fontsize=15, color='w')
plt.xlim(50, 600)
plt.ylim(2900, 11000)
plt.show()

3.2 绘制组合图

import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
data = pd.read_excel('销售业绩表.xlsx')
x = data['月份']
y1 = data['销售额(万元)']
y2 = data['同比增长率'] 
plt.bar(x, y1, color = 'c', label = '销售额(万元)')  
plt.plot(x, y2, color = 'r', linewidth = 3, label = '同比增长率')
plt.legend(loc = 'upper left', fontsize = 15)
plt.show()

import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
data = pd.read_excel('销售业绩表.xlsx')
x = data['月份']  
y1 = data['销售额(万元)'] 
y2 = data['同比增长率'] 
plt.bar(x, y1, color = 'c', label = '销售额(万元)')  
plt.legend(loc = 'upper left', fontsize = 15)  
plt.twinx()  
plt.plot(x, y2, color = 'r', linewidth = 3, label = '同比增长率')  
plt.legend(loc = 'upper right', fontsize = 15)  
plt.show()

3.3 绘制直方图

import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
data = pd.read_excel('客户年龄统计表.xlsx')
x = data['年龄']
plt.hist(x, bins = 9)
plt.xlim(15, 60)
plt.ylim(0, 40)
plt.title('年龄分布直方图', fontsize = 20)
plt.xlabel('年龄')
plt.ylabel('人数')
plt.grid(b = True, linestyle = 'dotted', linewidth = 1)
plt.show()

3.4 绘制雷达图

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei']  
plt.rcParams['axes.unicode_minus'] = False 
data = pd.read_excel('汽车性能指标分值统计表.xlsx')  
data = data.set_index('性能评价指标')  
data = data.T  
data.index.name = '品牌'  
def plot_radar(data, feature):  
    columns = ['动力性', '燃油经济性', '制动性', '操控稳定性', '行驶平顺性', '通过性', '安全性', '环保性', '方便性', '舒适性', '经济性', '容量性'] 
    colors = ['r', 'g', 'y']  
    angles = np.linspace(0.1 * np.pi, 2.1 * np.pi, len(columns), endpoint = False)  
    angles = np.concatenate((angles, [angles[0]]))    
    figure = plt.figure(figsize = (6, 6))  
    ax = figure.add_subplot(1, 1, 1, projection = 'polar')
    for i, c in enumerate(feature):
        stats = data.loc[c]  
        stats = np.concatenate((stats, [stats[0]]))  
        ax.plot(angles, stats, '-', linewidth = 2, c = colors[i], label = str(c))
        ax.fill(angles, stats, color = colors[i], alpha = 0.75)  
    ax.legend(loc = 4, bbox_to_anchor = (1.15, -0.07))  
    ax.set_yticklabels([2, 4, 6, 8, 10])  
    ax.set_thetagrids(angles * 180 / np.pi, columns, fontsize = 12)  
    plt.show()
    return figure
figure = plot_radar(data, ['A品牌', 'B品牌', 'C品牌'])
figure = plot_radar(data, ['B品牌'])

3.5 绘制树状图

import squarify as sf
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
x = ['上海', '北京', '重庆', '成都', '南京', '青岛', '长沙', '武汉', '深圳']  
y = [260, 45, 69, 800, 290, 360, 450, 120, 50] 
colors = ['lightgreen', 'pink', 'yellow', 'skyblue', 'cyan', 'silver', 'lightcoral', 'orange', 'violet']
percent = ['11%', '2%', '3%', '33%', '12%', '15%', '18%', '5%', '2%']
chart = sf.plot(sizes = y, label = x, color = colors, value = percent, edgecolor = 'white', linewidth = 2)
plt.title(label = '城市销售额分布及占比图',fontdict = {
   'family' : 'KaiTi', 'color' : 'k', 'size' : 25})
plt.axis('off')
# plt.show()
plt.savefig('3_5树状图.png')

3.6 绘制箱型图

import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
plt.rcParams['axes.unicode_minus'] = False
data = pd.read_excel('1月销售统计表.xlsx')
x1 = data['成都']
x2 = data['上海']
x3 = data['北京']
x4 = data['重庆']
x5 = data['南京']
x = [x1, x2, x3, x4, x5]
labels = ['成都', '上海', '北京', '重庆', '南京']
plt.boxplot(x, vert = True, widths = 0.5, labels = labels, showmeans = True )
plt.title('各地区1月销售额箱形图', fontsize=20)
plt.ylabel('销售额(万元)')

plt.rcParams['font.sans-serif'] = ['KaiTi']  # 指定默认字体
plt.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题

# plt.show()
plt.savefig("3_6绘制箱型图.png")

3.7 绘制玫瑰图

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei']   
plt.rcParams['axes.unicode_minus'] = False
index = ['0~0.5', '0.6~2.0', '2.1~4.0', '4.1~6.0']
columns = ['N', 'NNE', 'NE', 'ENE', 'E', 'ESE', 'SE', 'SSE', 'S', 'SSW', 'SW', 'WSW', 'W', 'WNW', 'NW', 'NNW']
np.random.seed(0)
data = pd.DataFrame(np.random.randint(30, 300, (4, 16)), index = index, columns = columns)
N = 16
theta = np.linspace(0, 2 * np.pi, N, endpoint = False)
width = np.pi / N 
labels = list(data.columns) 
plt.figure(figsize = (6, 6))
ax = plt.subplot(1, 1, 1, projection = 'polar')
for i in data.index:
    radius = data.loc[i] 
    ax.bar(theta, radius, width = width, bottom = 0.0, label = i, tick_label = labels)
ax.set_theta_zero_location('N') 
ax.set_theta_direction(-1)    
plt.title('各方向风速频数玫瑰图', fontsize = 20)
plt.legend(loc = 4, bbox_to_anchor = (1.3, 0.2)) 
plt.show()

代码在git上：https://gitee.com/cuiyonghua/Deep-Learning-Cases/tree/master/机器学习模块使用/matplotlib模块

matplotlib各种案例总结（python经典编程案例）

一. 绘制基本图表

1.1 绘制柱状图

1.2 绘制条形图

1.3 绘制折线图

1.4 绘制面积图

1.5 绘制散点图

1.6 绘制饼图和圆环图

二. 图表的绘制和美化技巧

2.1 在一张画布中绘制多张图表

2.2 添加图表元素

2.3 添加并设置网格线

2.4 调整坐标轴的刻度范围

三. 绘制高级图表

3.1 绘制气泡图

3.2 绘制组合图

3.3 绘制直方图

3.4 绘制雷达图

3.5 绘制树状图

3.6 绘制箱型图

3.7 绘制玫瑰图

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matplotlib各种案例总结（python经典编程案例）

一. 绘制基本图表

1.1 绘制柱状图

1.2 绘制条形图

1.3 绘制折线图

1.4 绘制面积图

1.5 绘制散点图

1.6 绘制饼图和圆环图

二. 图表的绘制和美化技巧

2.1 在一张画布中绘制多张图表

2.2 添加图表元素

2.3 添加并设置网格线

2.4 调整坐标轴的刻度范围

三. 绘制高级图表

3.1 绘制气泡图

3.2 绘制组合图

3.3 绘制直方图

3.4 绘制雷达图

3.5 绘制树状图

3.6 绘制箱型图

3.7 绘制玫瑰图

热门文章

最新文章

相关课程

相关电子书

相关实验场景

推荐镜像