如何防止python中的KeyErrors？

Question

我在机器学习项目中使用 MinMaxScaler 时遇到 KeyError 问题。这是我的相关代码：

df = pd.read_csv(io.BytesIO(uploaded['Root_Work_Sample.csv']))
print(df.shape)
print(df.columns)
display(df.head(5))
print(df.dtypes)
train_cols = ["feature1, feature2, feature3, feature4, feature5, feature6, feature7, feature8, feature9, feature10, feature11, feature12, feature13, feature14, y"]
df_train, df_test = train_test_split(df, train_size=1000, test_size=876, shuffle=False)
print("Train--Test size", len(df_train), len(df_test))
print(df_train)
print(df_test)
 
# scale the feature MinMax, build array
x = df_train.loc[:,train_cols].values  #THE ERROR IS ON THIS LINE
min_max_scaler = MinMaxScaler()
x_train = min_max_scaler.fit_transform(x)
x_test = min_max_scaler.transform(df_test.loc[:,train_cols])

这是我得到的错误：

KeyError: "None of [Index(['feature1, feature2, feature3, feature4, feature5, feature6, feature7, feature8, feature9, feature10, feature11, feature12, feature13, feature14, y'], dtype='object')] are in the [columns]"

对于如何解决这个问题以及像我这样的新手如何避免此类错误的一般做法有什么建议吗？

Answer 1

df_train 不是数据框，它是一个 2D numpy 数组，所以你不能在上面使用loc 方法。 我猜你以错误的方式使用train_test_split 函数。 而且您还错误地指定了train_cols，您应该将每个功能用引号括起来，如下所示：

train_cols = ["feature", "feature2",....]

试试这个：

X, y = df[train_cols], df["y"]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=876, shuffle=False)

scaler = MinMaxScaler()
X_train_scaled = scaler.fit_transform(X_train)
X_test_scaled = scaler.transform(X_test)