机器学习三剑客之Matplotlib

 

matplotlib

Matplotlib 是Python 2D绘图领域的基础套件，它让使用者将数据图形化，并提供多样化的输出格式。这里将会以四个小案例探索Matplotlib的常见用法

绘制折线图

 

折线图

import matplotlib.pyplot as plt
import random
# 保证生成的图片在浏览器内显示
%matplotlib inline
# 保证能正常显示中文(Mac) plt.rcParams['font.family'] = ['Arial Unicode MS'] # 模拟海南一天的温度变化 # 生成x轴的24小时 hainan_x = [h for h in range(0, 24)] # 生成y轴的温度随机值(15, 25) hainan_y = [random.randint(15, 25) for t in range(0, 24)] # 设置画板属性 plt.figure(figsize = (10, 8), dpi = 100) # 往画板绘图 plt.plot(hainan_x, hainan_y, label="海南") # 模拟北京一天内温度的变化 # 生成x轴的24小时 beijing_x = [h for h in range(0, 24)] # 生成y轴的温度随机值(5, 10) beijing_y = [random.randint(5, 10) for t in range(0, 24)] # 往画板绘图 plt.plot(beijing_x, beijing_y, label="北京") # 模拟河北一天内温度的变化 hebei_x = beijing_x hebei_y = [random.randint(1, 5) for t in range(0, 24)] # 自定义绘制属性: 颜色color="#0c8ac5", linestyle"-"""--""-.":", 线宽linewidth, 透明度alpha plt.plot(hebei_x, hebei_y, label="河北",color="#823384", linestyle=":", linewidth=3, alpha=0.3) # 坐标轴显示设置 # 生成24小时的描述 x_ = [x_ for x_ in range(0, 24)] x_desc = ["{}时".format(x_desc) for x_desc in x_] # 设置x轴显示 24小时 plt.xticks(x_, x_desc) # 生成10至30度的描述 y_ = [y_ for y_ in range(0, 30)][::2] y_desc = ["{}℃".format(y_desc) for y_desc in y_] # 设置y轴显示温度描述 plt.yticks(y_, y_desc) # 指定x y轴的名称 plt.xlabel("时间") plt.ylabel("温度") # 指定标题 plt.title("一天内温度的变化") # 显示图例 plt.legend(loc="best") # 将数据生成图片, 保存到当前目录下 plt.savefig("./t.png") # 在浏览器内展示图片 plt.show() 

绘制条形图

 

名侦探柯南主要人物年龄

import matplotlib.pyplot as plt
import random
# 保证生成的图片在浏览器内显示
%matplotlib inline
# 保证能正常显示中文(Mac) plt.rcParams['font.family'] = ['Arial Unicode MS'] # 条形图绘制名侦探柯南主要角色年龄 role_list = ["柯南", "毛利兰", "灰原哀", "琴酒","贝尔摩德", "伏特加", "赤井秀一", "目暮十三"] role_age = [7, 17, 7, 34, 32, 30, 27, 46] # 实际年龄 role_ture_age = [18, 17, 18, 34, 45, 30, 27, 46] x = [i for i in range(1, len(role_list)+1)] y = role_age y2 =role_ture_age # 设置画板属性 plt.figure(figsize = (15, 8), dpi = 100) # width以x为基准,向右为正,向左为负(如果多了,就需要为基准x加减响应的数值) plt.bar(x, y, width= -0.3, label="现实年龄", color="#509839") plt.bar(x, y2, width = 0.3, label="实际年龄", color="#c03035") x_ = [i for i in range(0, len(role_list)+1)] x_desc = ["{}".format(x_desc) for x_desc in role_list] x_desc.insert(0, "") y_ = range(0, 50)[::5] y_desc = ["{}岁".format(y_desc) for y_desc in range(0, 50)][::5] # x轴的数值和描述 plt.xticks(x_, x_desc) plt.yticks(y_, y_desc) plt.xlabel("角色姓名") plt.ylabel("年龄") plt.title("名侦探柯南主要角色年龄(部分)") plt.legend(loc="best") plt.savefig("./mzt.png") plt.show() 

直方图

 

IMDB

import matplotlib.pyplot as plt
import random

# 保证能正常显示中文
plt.rcParams['font.family'] = ['Arial Unicode MS'] # 时长数据 time = [131, 98, 125, 131, 124, 139, 131, 117, 128, 108, 135, 138, 131, 102, 107, 114, 119, 128, 121, 142, 127, 130, 124, 101, 110, 116, 117, 110, 128, 128, 115, 99, 136, 126, 134, 95, 138, 117, 111,78, 132, 124, 113, 150, 110, 117, 86, 95, 144, 105, 126, 130,126, 130, 126, 116, 123, 106, 112, 138, 123, 86, 101, 99, 136,123, 117, 119, 105, 137, 123, 128, 125, 104, 109, 134, 125, 127,105, 120, 107, 129, 116, 108, 132, 103, 136, 118, 102, 120, 114,105, 115, 132, 145, 119, 121, 112, 139, 125, 138, 109, 132, 134,156, 106, 117, 127, 144, 139, 139, 119, 140, 83, 110, 102,123,107, 143, 115, 136, 118, 139, 123, 112, 118, 125, 109, 119, 133,112, 114, 122, 109, 106, 123, 116, 131, 127, 115, 118, 112, 135,115, 146, 137, 116, 103, 144, 83, 123, 111, 110, 111, 100, 154,136, 100, 118, 119, 133, 134, 106, 129, 126, 110, 111, 109, 141,120, 117, 106, 149, 122, 122, 110, 118, 127, 121, 114, 125, 126,114, 140, 103, 130, 141, 117, 106, 114, 121, 114, 133, 137, 92,121, 112, 146, 97, 137, 105, 98, 117, 112, 81, 97, 139, 113,134, 106, 144, 110, 137, 137, 111, 104, 117, 100, 111, 101, 110,105, 129, 137, 112, 120, 113, 133, 112, 83, 94, 146, 133, 101,131, 116, 111, 84, 137, 115, 122, 106, 144, 109, 123, 116, 111,111, 133, 150] max_time = max(time) min_time = min(time) # 指定分组宽度 width = 5 # 指定分组数量 num_bins = int((max_time - min_time)/2) # 直方图统计电影时长频数 plt.figure(figsize=(15, 8), dpi=80) # 绘制直方图 plt.hist(time, num_bins, color="#509839",normed=1) # 指定显示刻度的个数 x_ = [i for i in range(min_time, max_time+1)] plt.xticks(x_[::width]) # 显示网格 plt.grid(True, linestyle="--", alpha=0.5) # 指定标题 plt.title("Top250的IMDB电影时长统计") plt.savefig("./IMDB.png") plt.show() 

饼图

 

pro_learn

import matplotlib.pyplot as plt
import random

# 保证能正常显示中文(Mac)
plt.rcParams['font.family'] = ['Arial Unicode MS'] # 学习时间分配 pro_name = ["C++", "Python", "Java", "Go", "Swift"] pro_time = [10, 15, 5, 3, 1] # 画饼 plt.pie(pro_time, labels=pro_name, autopct="%3.2f%%", colors=["#ea6f5a", "#509839", "#0c8ac5", "#d29922", "#fdf6e3"]) # 指定标题 plt.title("学习时间分配") # 保证为图形为正圆 plt.axis("equal") # 显示图示 plt.legend(loc="best") plt.savefig("./pro_learn.png") plt.show()