如何在 Python 中绘制元组列表？

How do I plot list of tuples in Python?

提问by olliepower

I have the following data set. I would like to use Python or Gnuplot to plot the data. The tuples are of the form (x, y). The Y-axis should be a log axis, that is, log(y). A scatter plot or line plot would be ideal.

我有以下数据集。我想使用 Python 或 Gnuplot 来绘制数据。元组的形式为(x, y)。Y 轴应为对数轴，即log(y)。散点图或线图将是理想的。

How can this be done?

如何才能做到这一点？

 [(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08), 
 (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09), 
 (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]

采纳答案by Sukrit Kalra

If I get your question correctly, you could do something like this.

如果我正确理解你的问题，你可以做这样的事情。

>>> import matplotlib.pyplot as plt
>>> testList =[(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08), 
 (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09), 
 (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]
>>> from math import log
>>> testList2 = [(elem1, log(elem2)) for elem1, elem2 in testList]
>>> testList2
[(0, -16.617236475334405), (1, -17.67799605473062), (2, -18.691431541177973), (3, -18.9767093108359), (4, -19.420021520728017), (5, -19.298411635970396)]
>>> zip(*testList2)
[(0, 1, 2, 3, 4, 5), (-16.617236475334405, -17.67799605473062, -18.691431541177973, -18.9767093108359, -19.420021520728017, -19.298411635970396)]
>>> plt.scatter(*zip(*testList2))
>>> plt.show()

which would give you something like

这会给你类似的东西

Or as a line plot,

或者作为线图，

>>> plt.plot(*zip(*testList2))
>>> plt.show()

EDIT- If you want to add a title and labels for the axis, you could do something like

编辑- 如果要为轴添加标题和标签，可以执行以下操作

>>> plt.scatter(*zip(*testList2))
>>> plt.title('Random Figure')
>>> plt.xlabel('X-Axis')
>>> plt.ylabel('Y-Axis')
>>> plt.show()

which would give you

这会给你

回答by K DawG

In matplotlib it would be:

在 matplotlib 中，它将是：

import matplotlib.pyplot as plt

data =  [(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08),
 (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09),
 (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]

x_val = [x[0] for x in data]
y_val = [x[1] for x in data]

print x_val
plt.plot(x_val,y_val)
plt.plot(x_val,y_val,'or')
plt.show()

which would produce:

这将产生：

回答by Bennett Brown

As others have answered, scatter()or plot()will generate the plot you want. I suggest two refinements to answers that are already here:

正如其他人所回答的那样，scatter()或plot()将生成您想要的情节。我建议对已经在这里的答案进行两项改进：

1. Use numpy to create the x-coordinate list and y-coordinate list. Working with large data sets is faster in numpy than using the iteration in Python suggested in other answers.

2. Use pyplot to apply the logarithmic scale rather than operating directly on the data, unless you actually want to have the logs.

   import matplotlib.pyplot as plt
   import numpy as np
   
   data = [(2, 10), (3, 100), (4, 1000), (5, 100000)]
   data_in_array = np.array(data)
   '''
   That looks like array([[     2,     10],
                          [     3,    100],
                          [     4,   1000],
                          [     5, 100000]])
   '''
   
   transposed = data_in_array.T
   '''
   That looks like array([[     2,      3,      4,      5],
                          [    10,    100,   1000, 100000]])
   '''    
   
   x, y = transposed 
   
   # Here is the OO method
   # You could also the state-based methods of pyplot
   fig, ax = plt.subplots(1,1) # gets a handle for the AxesSubplot object
   ax.plot(x, y, 'ro')
   ax.plot(x, y, 'b-')
   ax.set_yscale('log')
   fig.show()
   

1. 使用 numpy 创建 x 坐标列表和 y 坐标列表。在 numpy 中处理大型数据集比在其他答案中建议的 Python 中使用迭代更快。

2. 使用 pyplot 应用对数刻度而不是直接对数据进行操作，除非您确实想要日志。

   import matplotlib.pyplot as plt
   import numpy as np
   
   data = [(2, 10), (3, 100), (4, 1000), (5, 100000)]
   data_in_array = np.array(data)
   '''
   That looks like array([[     2,     10],
                          [     3,    100],
                          [     4,   1000],
                          [     5, 100000]])
   '''
   
   transposed = data_in_array.T
   '''
   That looks like array([[     2,      3,      4,      5],
                          [    10,    100,   1000, 100000]])
   '''    
   
   x, y = transposed 
   
   # Here is the OO method
   # You could also the state-based methods of pyplot
   fig, ax = plt.subplots(1,1) # gets a handle for the AxesSubplot object
   ax.plot(x, y, 'ro')
   ax.plot(x, y, 'b-')
   ax.set_yscale('log')
   fig.show()
   

I've also used ax.set_xlim(1, 6)and ax.set_ylim(.1, 1e6)to make it pretty.

我也用过ax.set_xlim(1, 6)，ax.set_ylim(.1, 1e6)让它变得漂亮。

I've used the object-oriented interface to matplotlib. Because it offers greater flexibility and explicit clarity by using names of the objects created, the OO interface is preferred over the interactive state-based interface.

我已经将面向对象的接口用于 matplotlib。因为它通过使用创建的对象的名称提供了更大的灵活性和明确的清晰度，所以 OO 接口优于交互式基于状态的接口。

回答by Philippe Chavanne

You could also use zip

你也可以使用 zip

import matplotlib.pyplot as plt

l = [(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08),
     (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09),
     (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]

x, y = zip(*l)

plt.plot(x, y)

回答by Friedrich

With gnuplotusing gplot.py

用gnuplot使用gplot.py

from gplot import *

l = [(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08), 
 (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09), 
 (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]

gplot.log('y')
gplot(*zip(*l))