在 Matplotlib 中并排放置图

Matplotlib 是最流行的Python库，用于绘制图形和可视化我们的数据。在 Matplotlib 中，我们可以通过调用一次来创建多个图。为了创建多个图，我们使用 Matplotlib 中 pyplot 模块的 subplot函数。

Syntax: plt.subplot(nrows, .ncolumns, index)

Parameters:

• nrows is for number of rows means if the row is 1 then the plots lie horizontally.
• ncolumns stands for column means if the column is 1 then the plot lie vertically.
• and index is the count/index of plots. It starts with 1.

方法：

• 导入库和模块。
• 为绘图创建数据。
• 现在，使用上面的函数创建一个子图。
• 根据需要给函数赋予参数。

示例 1：

Python3

# importing libraries
import numpy as np
import matplotlib.pyplot as plt
 
 
# creating an array of data for x-axis
x = np.array([2, 4, 6, 8, 10, 12, 14, 16, 18, 20])
 
# data for y-axis
y_1 = 2*x
 
# dat for y-axis for another plot
y_2 = 3*x
 
# using subplot function and creating plot one
plt.subplot(1, 2, 1)  # row 1, column 2, count 1
plt.plot(x, y_1, 'r', linewidth=5, linestyle=':')
plt.title('FIRST PLOT')
plt.xlabel('x-axis')
plt.ylabel('y-axis')
 
# using subplot function and creating plot two
# row 1, column 2, count 2
plt.subplot(1, 2, 2)
 
# g is gor green color
plt.plot(x, y_2, 'g', linewidth=5)
plt.title('SECOND PLOT')
plt.xlabel('x-axis')
plt.ylabel('y-axis')
 
# space between the plots
plt.tight_layout(4)
 
# show plot
plt.show()

输出：

示例 2：垂直形式。

蟒蛇3

# importing libraries
import numpy as np
import matplotlib.pyplot as plt
 
# creating an array of data for x-axis
x = np.array([2, 4, 6, 8, 10, 12, 14, 16, 18, 20])
 
# data for y-axis
y_1 = 2*x
 
# dat for y-axis for another plot
y_2 = 3*x
 
# using subplot function and creating plot one
# row 2, column 1, count 1
plt.subplot(2, 1, 1)
plt.plot(x, y_1, 'r', linewidth=5, linestyle=':')
plt.title('FIRST PLOT')
plt.xlabel('x-axis')
plt.ylabel('y-axis')
 
# using subplot function and creating plot two
# row 2, column 1, count 2
plt.subplot(2, 1, 2)
plt.plot(x, y_2, 'g', linewidth=5)
plt.title('SECOND PLOT')
plt.xlabel('x-axis')
plt.ylabel('y-axis')
 
# space between the plots
plt.tight_layout()
 
# show plot
plt.show()

输出：

为了增加图的大小，我们可以这样写

plt.subplots(figsize(l, b))

示例 3：

蟒蛇3

# importing libraries
import numpy as np
import matplotlib.pyplot as plt
 
# creating an array of data for x-axis
x = np.array([2, 4, 6, 8, 10, 12, 14, 16, 18, 20])
 
# data for y-axis
y_1 = 2*x
 
# dat for y-axis for another plot
y_2 = 3*x
 
# figsize() function to adjust the size
# og function
plt.subplots(figsize=(15, 5))
 
# using subplot function and creating
# plot one
plt.subplot(1, 2, 1)
plt.plot(x, y_1, 'r', linewidth=5, linestyle=':')
plt.title('FIRST PLOT')
plt.xlabel('x-axis')
plt.ylabel('y-axis')
 
# using subplot function and creating plot two
plt.subplot(1, 2, 2)
plt.plot(x, y_2, 'g', linewidth=5)
plt.title('SECOND PLOT')
plt.xlabel('x-axis')
plt.ylabel('y-axis')
 
# space between the plots
plt.tight_layout(4)
 
# show plot
plt.show()

输出：