以鸢尾花散点图为例，plot如何自动添加图例legend信息？

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

data_url = "http://download.tensorflow.org/data/iris_training.csv"
column_names = ["萼长", "萼宽", "瓣长", "瓣宽", "种类"]
df_iris = pd.read_csv(data_url, header=0, names=column_names)
data_x = np.array(df_iris["萼长"])
data_y = np.array(df_iris["萼宽"])
data_z = np.array(df_iris["种类"])
fig = plt.figure("鸢尾花散点图示例", figsize=(15, 15))
plt.rcParams["font.sans-serif"] = ["SimHei"]
plt.rcParams["axes.unicode_minus"] = False
plt.suptitle("鸢尾花数据集\n蓝色->setosa|红色->versicolor|绿色->virginica")
plt.xlabel(column_names[0])
plt.ylabel(column_names[1])
plt.title(column_names[0] + "、" + column_names[1] + "数据关联散点图")

# 看这里 ###########################################################
p1 = plt.scatter(data_x, data_y, c=data_z, cmap="brg")
plt.legend(handles=p1.legend_elements()[0], labels=["山鸢尾", "变色鸢尾", "维吉尼亚鸢尾"], loc='best', shadow=True, fontsize=16)
# 看这里 ###########################################################

plt.savefig("scatter.png")
plt.show()

q1 = plt.scatter(data_x, data_y, c=data_z, cmap="brg")
plt.legend(handles=q1.legend_elements()[0], labels=["山鸢尾", "变色鸢尾", "维吉尼亚鸢尾"], loc='best', shadow=True, fontsize=16)

([<matplotlib.lines.Line2D object at 0x0000016BD453B0B8>, <matplotlib.lines.Line2D object at 0x0000016BD453B208>, <matplotlib.lines.Line2D object at 0x0000016BD453B2B0>], ['$\\mathdefault{0}$', '$\\mathdefault{1}$', '$\\mathdefault{2}$'])

matplotlib.lines.Line2D object