line chart

line chart

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

income = [1200, 1400, 1600, 1800, 2000, 2200, 2400]
outlay = [1000, 1240, 1320, 1500, 1790, 1924, 2218.75]

Each income corresponds to an 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()

The relationship between income and outlay

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()

quadratic function

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()

Plot two functions at the same time

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()

N = 10

N = 20

N = 30

N = 50

N = 100

N = 1000

This method is very useful when drawing a large number of function images, and can show the difference between different function images.

Statistics

Start time of this page: December 19, 2021

Completion time of this page: December 19, 2021