1.將數據寫入csv文件，應該可以python代碼直接實現數據集的寫入，但我對文件讀取這塊不太熟練，等我成功了再加上，這裏我直接手寫將數據集寫入Excel

2.然後把後綴改成.csv就可以了，利用pandas讀取

import matplotlib.pyplot as plt
file = ‘bp_test.csv‘
import pandas as pd
df = pd.read_csv(file, header=None)
x = df.iloc[:,].values
print(x)

讀取結果

[[-1.     -0.9602]
 [-0.9    -0.577 ]
 [-0.8    -0.0729]
 [-0.7     0.3771]
 [-0.6     0.6405]
 [-0.5     0.66  ]
 [-0.4     0.4609]
 [-0.3     0.1336]
 [-0.2    -0.2013]
 [-0.1    -0.4344]
 [ 0.     -0.5   ]
 [ 0.1    -0.393 ]
 [ 0.2    -0.1647]
 [ 0.3     0.0988]
 [ 0.4     0.3072]
 [ 0.5     0.396 ]
 [ 0.6     0.3449]
 [ 0.7     0.1816]
 [ 0.8    -0.0312]
 [ 0.9    -0.2189]
 [ 1.     -0.3201]]
 

3.將21個數據可視化

plt.scatter(x[:,0], x[:,1], color=‘red‘, marker=‘x‘, label=‘mark‘)
plt.xlabel(‘x‘)
plt.ylabel(‘y‘)
plt.legend(loc=‘upper left‘)
plt.show()

運行結果

python構建bp單層神經網絡__1.可視化數據