matplotlib基本操作

Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.

import matplotlib as mpl
import matplotlib.pyplot as plt

# 默认情况下，matplotlib不支持中文显示，我们需要进行一下设置。

# 设置字体为黑体，以支持中文显示。
mpl.rcParams["font.family"] = "SimHei"
# 设置在中文字体时，能够正常的显示负号（-）。
mpl.rcParams["axes.unicode_minus"] = False

# {"Iris-virginica": 0, "Iris-setosa": 1, "Iris-versicolor": 2})
# 设置画布的大小
plt.figure(figsize=(10, 10))
# 绘制训练集数据
plt.scatter(x=t0["SepalLengthCm"][:40], y=t0["PetalLengthCm"][:40], color="r", label="Iris-virginica")
plt.scatter(x=t1["SepalLengthCm"][:40], y=t1["PetalLengthCm"][:40], color="g", label="Iris-setosa")
plt.scatter(x=t2["SepalLengthCm"][:40], y=t2["PetalLengthCm"][:40], color="b", label="Iris-versicolor")
# 绘制测试集数据
right = test_X[result == test_y]
wrong = test_X[result != test_y]
plt.scatter(x=right["SepalLengthCm"], y=right["PetalLengthCm"], color="c", marker="x", label="right")
plt.scatter(x=wrong["SepalLengthCm"], y=wrong["PetalLengthCm"], color="m", marker=">", label="wrong")
plt.xlabel("花萼长度")
plt.ylabel("花瓣长度")
plt.title("KNN分类结果显示")
plt.legend(loc="best")
plt.show()

# ro：红色实线
plt.plot(result, "ro-", label="预测值")
# bo-- ：蓝色虚线
plt.plot(test_y.values, "bo--", label="真实值")