CODEWITHSUNDEEP
pythonpython-3.xmatplotlib
Afke
Afke

Reputation: 989

Python3: using matplotlib to create figure, using a dictionary

I have got a dictionary in the form of {test_size: (test_error, training_error)} Here it is:

{0.1: (0.94736842105263153, 0.90294117647058825), 0.2: (0.92105263157894735, 0.90397350993377479), 0.3: (0.82456140350877194, 0.9242424242424242), 0.6: (0.8722466960352423, 0.91390728476821192), 0.8: (0.76897689768976896, 0.98666666666666669), 0.5: (0.79894179894179895, 0.95767195767195767), 0.7: (0.8226415094339623, 0.99115044247787609), 0.9: (0.62463343108504399, 1.0), 0.4: (0.79605263157894735, 0.92920353982300885)}

I am trying to create a figure with matplotlib that looks like this:

figure

I would like to get the key of the dictionary (the test_size) on the x axis and the test and training error on the y axis.

How to solve this? Should I use a DataFrame? 

df = pd.DataFrame(dictionary)
plt.plot(df)
???

I read things about that plotting dictionaries is only valuable using Python 2.. I am using Python 3 and I am really lost with this so far.. Hope anyone can help!

Upvotes: 1

Views: 575

Answers (1)

SparkAndShine
SparkAndShine

Reputation: 18007

How about this,

enter image description here

The source code, 

import matplotlib.pyplot as plt
import operator

fig, ax = plt.subplots()

d = {0.1: (0.94736842105263153, 0.90294117647058825), 0.2: (0.92105263157894735, 0.90397350993377479), 0.3: (0.82456140350877194, 0.9242424242424242), 0.6: (0.8722466960352423, 0.91390728476821192), 0.8: (0.76897689768976896, 0.98666666666666669), 0.5: (0.79894179894179895, 0.95767195767195767), 0.7: (0.8226415094339623, 0.99115044247787609), 0.9: (0.62463343108504399, 1.0), 0.4: (0.79605263157894735, 0.92920353982300885)}
lists = sorted(d.items())

x = list(map(operator.itemgetter(0), lists))
y = list(map(operator.itemgetter(1), lists))

y1 = list(map(operator.itemgetter(0), y))
ax.plot(x, y1, label='Test error', color='b', linewidth=2)

y2 = list(map(operator.itemgetter(1), y))
ax.plot(x, y2, label='Training error', color='r', linewidth=2)

plt.legend(loc='best')
plt.grid()
plt.show()

Upvotes: 1

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