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()


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