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Basic plotting with 'plot'

  • plot is a key function of the pyplot library, used to add most major features (such as lines and markers) to the plot

How do we plot an array?

  • Just pass the array as argument to the plot function. See the example below.
In [1]:
import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline

f = np.array([1,2,3,4,5,6,7,8,9,10]) 
plt.plot(f)
Out[1]:
[<matplotlib.lines.Line2D at 0x7530748>]
  • How was the above plot created?

    By simply calling 'plot(f)' a graph of the array N values is plotted against the [0,N-1] values in x-axis using the default line style (blue color, continuous line)

How do I define the values in x-axis?

Just call plot(x, f) where x is the array with the x-axis values

In [2]:
import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline

x = np.array([1,2,3,4,5,6,7,8,9,10])/2 
f = 2*x
plt.plot(x,f)

# Now the array f = 2*x is plotted against the x values [0.5, 5.0]
Out[2]:
[<matplotlib.lines.Line2D at 0x7911e80>]

How do I change the line style?

Add a style string as in the examples below. For example the 'g' string defines: 'green' color and asterisk ('') marks

  • See more options about style strings here
In [3]:
import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline

x = np.array([i for i in range(20)]) 
f2 = 2*x
plt.plot(x,f2, 'g*')

f3 = 3*x
plt.plot(x,f3, 'r--')

f5 = 5*x
plt.plot(x,f5, 'm^')
Out[3]:
[<matplotlib.lines.Line2D at 0x75c1f98>]
  • 'plot' can contain more than one groups of x, y, 'format string' values
In [4]:
import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline

x = np.linspace(0,10,30)
                
f1 = x 
f2 = 2*x
f3 = 3*x
plt.plot(x, f1, 'k--', x, f2, 'mo', x, f3, 'g.')
Out[4]:
[<matplotlib.lines.Line2D at 0x79e9668>,
 <matplotlib.lines.Line2D at 0x79e9828>,
 <matplotlib.lines.Line2D at 0x79f01d0>]
  • If x and/or f are 2-dimensional then the corresponding columns pairs will be plotted.

    For example, the red line below is plotted based on column (x, f) pairs: (3,8), (6, 64) and (9, 512)

In [5]:
import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline

x = np.array([[1,2,3],[4,5,6],[7,8,9]]) #reshape(3,3)
f = 2**x
print(x)
print(f)
plt.plot(x, f)

[[1 2 3]
 [4 5 6]
 [7 8 9]]
[[  2   4   8]
 [ 16  32  64]
 [128 256 512]]
Out[5]:
[<matplotlib.lines.Line2D at 0x7a56fd0>,
 <matplotlib.lines.Line2D at 0x7a5d1d0>,
 <matplotlib.lines.Line2D at 0x7a5d470>]

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