技術標籤：python機器學習資料分析debug

用支援向量機做鳶尾花分類預測時
敲程式碼有個關於KeyError的報錯，如下：
KeyError: “None of [Int64Index([0, 1, 2, 3], dtype=‘int64’)] are in the [columns]”
原始程式碼如下

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn import svm
from sklearn.metrics import accuracy_score
import
 
 numpy as np
data = pd.read_csv(r"G:\實驗6/iris.csv")  
x, y = data[range(4)], data[4]  
y = pd.Categorical(y).codes  
x = x[[0,1,2,3]]
x_train, x_test, y_train, y_test = train_test_split(x, y, random_state=1, train_size=0.6)
clf=svm.SVC(C=0.4,kernel='rbf',gamma=20,decision_function_shape='ovr')
clf.
 
fit(x_train, y_train.ravel())
print('訓練集準確率：', accuracy_score(y_train, clf.predict(x_train))) 
print('測試集準確率：', accuracy_score(y_test, clf.predict(x_test)))  

一開始看了很多博文
以為是資料型別的錯誤，或者是pandas包版本的問題，跟著他們的博文改，發現還是報錯。
然後探索發現並不是，檢視鳶尾花資料發現

鳶尾花資料集中沒有索引行，詳解見如下連結
https://www.cnblogs.com/komean/p/10629311.html

修改後程式碼不再報錯

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn import svm
from sklearn.metrics import accuracy_score
import numpy as np
data = pd.read_csv(r"G:\實驗6/iris.csv",header=None)  
x, y = data[range(4)], data[4]  
y = pd.Categorical(y).codes  
x = x[[0,1,2,3]]
x_train, x_test, y_train, y_test = train_test_split(x, y, random_state=1, train_size=0.6)
clf=svm.SVC(C=0.4,kernel='rbf',gamma=20,decision_function_shape='ovr')
clf.fit(x_train, y_train.ravel())
print('訓練集準確率：', accuracy_score(y_train, clf.predict(x_train))) 
print('測試集準確率：', accuracy_score(y_test, clf.predict(x_test)))  

不再報錯，執行成功