The line chart is to use lines to represent data. It is generally used to see the trend of the data, whether it is a positive ratio (increasing) or an inverse ratio (decreasing)
For example, here is a piece of data about income and outlay
If we use the following procedure, we can draw a clear diagram of the relationship between income and expenditure:
income = [1200, 1400, 1600, 1800, 2000, 2200, 2400]
outlay = [1000, 1240, 1320, 1500, 1790, 1924, 2218.75]
import matplotlib.pyplot as plt
plt.plot(income, outlay)
plt.title('The relationship between income and outlay')
plt.xlabel('income')
plt.ylabel('outlay')
plt.grid()
plt.show()
In this graph, we will find that when income increases, expenditures will increase accordingly.
A typical use scheme of line chart is to draw function image.
For example, we can use the following code to draw an image of a quadratic function.
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(-10, 10, 0.1)
y = x ** 2
plt.plot(x, y)
plt.title('Draw function graph')
plt.xlabel('x')
plt.ylabel('y')
plt.grid()
plt.show()
We can also draw images of two functions in the same picture.
For example, in the figure below, I have drawn the sine and cosine images at the same time.
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(-np.pi, np.pi, 0.1)
y1 = np.sin(x)
y2 = np.cos(x)
plt.plot(x, y1, label = 'sin')
plt.plot(x, y2, label = 'cos')
plt.title('Draw function graph')
plt.xlabel('x')
plt.ylabel('y')
plt.grid()
plt.legend()
plt.show()
The following code block can draw multiple functions with gradually color:
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
x = np.arange( 0, 5, 0.01 )
N = 30
cmap = plt.get_cmap( 'jet', N )
for i, n in enumerate( np.linspace(0, 0.5, N) ):
y = x ** n
plt.plot( x, y, c=cmap(i) )
plt.xlabel('x')
plt.ylabel('y')
plt.title('Automatically add multiple functions')
# Draw colorbar
norm = matplotlib.colors.Normalize( 0, 0.5 )
sm = plt.cm.ScalarMappable( cmap=cmap, norm=norm )
plt.colorbar(sm)
plt.grid()
plt.show()
This method is very useful when drawing a large number of function images, and can show the difference between different function images.
