[Matplotlib drawing]

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Matplotlib Study （ To continue ）

Python expanded memory bank Matplotlib Depends on the extension library NumPy And the standard library Tkinter,
You can draw a variety of shapes , Include Broken line diagram 、 Scatter plot 、 The pie chart 、 Histogram 、 Radar map wait .

Python expanded memory bank Matplotlib Include pylab、pyplot And other drawing modules, as well as a large number of fonts 、 Color 、 Legend and other graphic elements of the management and control module . among pylab and pyplot The module provides information similar to MATLAB Drawing interface for , Support line style 、 Font properties 、 Management and control of axis attributes and other attributes , You can use very simple code to draw beautiful patterns .

Use pylab or pyplot The general process of drawing ：

1. Read in the data
2. Draw a line chart according to actual needs 、 Scatter plot 、 Histogram 、 Radar chart or three-dimensional curve and surface
3. Next, set the axis and image properties
4. Display or save drawing results

Broken line diagram

#  Broken line diagram 
import pandas as pd
import pylab as plt

plt.rc('font', family='SimHei')     #  Used to display Chinese labels normally 
plt.rc('font', size=20)             #  Set the display font size 

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

lxw = pd.read_excel('data2.xlsx', header=None)
tsj = lxw.values                    #  Extract the data from it 
# print(tsj)

x = tsj[0]                          #  Extract the data in the first row 
y = tsj[1:]                         #  Extract data except the first row 

plt.plot(x, y[0], '-*b', label=' water consumption ')
plt.plot(x, y[1], '--pr', label=' Electricity consumption ')

plt.xlabel(' month ')
plt.ylabel(' Monthly dosage ')

plt.legend(loc='upper left')
plt.grid()
plt.show()

Relevant operation effects are as follows ：

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Histogram

#  Histogram 
import pandas as pd
import pylab as plt

#  Used to display Chinese labels normally 
plt.rc('font', family='SimHei')
plt.rc('font', size=20)

lxw2 = pd.read_excel('data2.xlsx', header=None)

sz = lxw2.T
sz.plot(kind='bar')
plt.legend([' water consumption ', ' Electricity consumption '])

plt.xticks(range(6), sz[0], rotation=0)
plt.ylabel(' The dosage ')

plt.show()

Relevant operation effects are as follows ：

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Subgraphs

#  Subgraphs 
import numpy as np
import pylab as plt

# plt.rc('text', usetex=True)
y1 = np.random.randint(2, 6, 6)
y1 = y1/sum(y1)

plt.subplot(2, 2, 1)
su = ['Python', 'Java', 'MySQL', 'C', 'Math', 'English']

plt.barh(su, y1)
plt.subplot(222)
plt.pie(y1, labels=su)
plt.subplot(212)

x2 = np.linspace(0.01, 10, 100)
y2 = np.sin(10*x2)/x2

plt.plot(x2, y2)

plt.xlabel('$x$')
plt.ylabel('$\\mathrm{sin}(10x)/x$')

plt.show()

Relevant operation effects are as follows ：

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Three dimensional curve

#  Three dimensional curve 
import pylab as plt
import numpy as np

swx = plt.axes(projection='3d')

z = np.linspace(-50, 50, 1000)
x = z ** 2 * np.sin(z)
y = z ** 2 * np.cos(z)

swx.plot(x, y, z, 'b')

plt.show()

Relevant operation effects are as follows ：

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Three dimensional surface maps

#  Three dimensional surface maps 
import pylab as plt
import numpy as np

swt = plt.axes(projection='3d')

x = np.linspace(-5, 5, 100)
x, y = np.meshgrid(x, x)

z = 50 * np.sin(x+y)

swt.plot_surface(x, y, z, color='r')

plt.show()

Relevant operation effects are as follows ：

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Three dimensional surface drawing

#  Three dimensional surface drawing 
import pylab as plt
import numpy as np

swb = plt.axes(projection='3d')

x = np.arange(-8, 8, 0.25)
y = np.arange(-8, 8, 0.25)
x, y = np.meshgrid(x, y)

z = np.sin(np.sqrt(x**2+y**2))

tx = swb.plot_surface(x, y, z, cmap='coolwarm')

plt.colorbar(tx)

plt.show()

Relevant operation effects are as follows ：

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