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Matplotlib

[TOC]

导入

常用的需要导入的是 pyplot 模块，并命名为 plt

import matplotlib.pyplot as plt

中文

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

方法

plot

绘制图片

示例

import matplotlib.pyplot as plt
import numpy as np

plt.figure(figsize=(10, 10))

data = np.random.randint(10, 100, size=10)
plt.plot(data)
plt.show()

将得到

img

可以在一张图中绘制多条曲线

import matplotlib.pyplot as plt
import numpy as np

plt.figure(figsize=(10, 10))

t = np.arange(1, 10, 1)
plt.plot(t, t, t, t * 2, t, t ** 2)
plt.show()

将得到

img

import matplotlib.pyplot as plt
import numpy as np

plt.figure(figsize=(10, 10))

t = np.arange(1, 10, 1)
plt.plot(t, t, color='red', linestyle='-', linewidth=1, label='Label 1')
plt.plot(t, t * 2, color='green', linestyle='-.', linewidth=2, label='Label 2')
plt.plot(t, t ** 2, color='blue', linestyle='--', linewidth=3, label='Label 3')
plt.show()

将得到

img

参数

参数名 含义
color 颜色 color=red
linestyle 线形 linestyle='-.'
linewidth 线宽 linewidth=3
label 标签 label='Label 1'

scatter

绘制散点图

例如

import matplotlib.pyplot as plt
import numpy as np

plt.figure(figsize=(10,10))

data = np.random.randint(10, 100, size=10)
plt.scatter(x=range(len(data)), y=data, marker='*')
plt.show()

将得到

img

参数

参数名 含义
x x 轴坐标数据
y y 轴坐标数据
marker 标志点样式

bar

绘制条形图

例如

import matplotlib.pyplot as plt
import numpy as np

plt.figure(figsize=(10,10))

data = np.random.randint(10, 100, size=10)
plt.bar(x=range(len(data)), height=data)
plt.show()

将得到

img

figure

参数

参数名 含义 例
figsize 尺寸 figsize=(100, 100)
dpi 分辨列 dpi=100

legend

图例

plt.legend(loc='best')

例如

import matplotlib.pyplot as plt
import numpy as np

plt.figure(figsize=(10, 10))

t = np.arange(1, 10, 1)
plt.plot(t, t, color='red', linestyle='-', linewidth=1, label='Label 1')
plt.plot(t, t * 2, color='green', linestyle='-.', linewidth=2, label='Label 2')
plt.plot(t, t ** 2, color='blue', linestyle='--', linewidth=3, label='Label 3')
plt.legend(loc='best')
plt.show()

将得到

img

savefig

保存图片

plt.savefig('路径名')

title

图片标题

xlabel

x 轴标签

ylabel

y 轴标签

子图

subplot

import numpy as np
import matplotlib.pyplot as plt

plt.figure(figsize=(10,10))
  
x = np.linspace(-np.pi, np.pi, 300)
plt.figure(1)
plt.subplot(211)
plt.plot(x, np.sin(x), color='red')
plt.subplot(212)
plt.plot(x, np.cos(x), color='blue')
plt.show()

将得到

img

subplots

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(-np.pi, np.pi, 300)

fig, (ax0, ax1) = plt.subplots(2, 1, figsize=(10, 10))

ax0.plot(x, np.sin(x), color='red')
ax0.set_title('sin(x)')
ax1.plot(x, np.cos(x), color='blue')
ax1.set_title('cos(x)')
plt.show()

将得到

img

axes

import matplotlib.pyplot as plt
import numpy as np

plt.figure(figsize=(10, 10))

x = np.linspace(-np.pi, np.pi, 300)
plt.axes((0.1, 0.1, 0.8, 0.8))
plt.plot(x, np.sin(x), color='red')
plt.axes((0.4, 0.15, 0.4, 0.3))
plt.plot(x, np.cos(x), color='blue')
plt.show()

可得到

img

示例

import matplotlib.pyplot as plt
import numpy as np

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = True

plt.figure()
start_val = 0
end_val = 10
num_val = 100
x = np.linspace(start=start_val, stop=end_val, num=num_val)
y = np.sin(x)

plt.plot(x, y, '--g', lw=2, label='sin(x)')

x_min = 0
x_max = 10
y_min = -1.5
y_max = 1.5
plt.xlim(x_min, x_max)
plt.ylim(y_min, y_max)

plt.xlabel('X Axis', fontsize=15)
plt.ylabel('Y Axis', fontsize=15)

x_location = np.arange(x_min, x_max, 2)
x_labels = ('2019-1-1', '2019-1-2', '2019-1-3', '2019-1-4', '2019-1-5')
plt.xticks(x_location, x_labels, rotation=45, fontsize=15)

y_location = np.arange(y_min, y_max, 1)
y_labels = ('最小值', '零值', '最大值')
plt.yticks(y_location, y_labels, fontsize=15)

plt.grid(True, ls=':', color='r', alpha=0.5)

plt.legend(loc='best')
plt.title('Figure of sin(x)', fontsize=15)
plt.show()

img

import matplotlib.pyplot as plt
import numpy as np

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = True

fig = plt.figure()

ax = fig.add_subplot(111)

start_val = 0
end_val = 10
num_val = 100
x = np.linspace(start=start_val, stop=end_val, num=num_val)
y = np.sin(x)

ax.plot(x, y, '--g', lw=2, label='sin(x)')

x_min = 0
x_max = 10
y_min = -1.5
y_max = 1.5
ax.set_xlim(x_min, x_max)
ax.set_ylim(y_min, y_max)

ax.set_xlabel('X Axis', fontsize=15)
ax.set_ylabel('Y Axis', fontsize=15)

x_location = np.arange(x_min, x_max, 2)
x_labels = ('2019-1-1', '2019-1-2', '2019-1-3', '2019-1-4', '2019-1-5')
ax.set_xticks(x_location)
ax.set_xticklabels(x_labels, rotation=45, fontsize=15)

y_location = np.arange(y_min, y_max, 1)
y_labels = ('最小值', '零值', '最大值')
ax.set_yticks(y_location)
ax.set_yticklabels(y_labels, fontsize=15)

ax.grid(True, ls=':', color='r', alpha=0.5)

ax.legend(loc='best')
ax.set_title('Figure of sin(x)', fontsize=15)
plt.show()

img