我正在尝试根据我在github here中发现的内容创建一个SVM模型,但是它一直在返回此错误。
Traceback (most recent call last):
File "C:\Users\Me\Documents\#e\projects\Sign-Language-Glove-master\modeling.py", line 22, in <module>
train_features = train[['F1','F2','F3','F4','F5','X','Y','Z','C1','C2']]
File "C:\Python27\lib\site-packages\pandas\core\frame.py", line 2934, in __getitem__
raise_missing=True)
File "C:\Python27\lib\site-packages\pandas\core\indexing.py", line 1354, in _convert_to_indexer
return self._get_listlike_indexer(obj, axis, **kwargs)[1]
File "C:\Python27\lib\site-packages\pandas\core\indexing.py", line 1161, in _get_listlike_indexer
raise_missing=raise_missing)
File "C:\Python27\lib\site-packages\pandas\core\indexing.py", line 1246, in _validate_read_indexer
key=key, axis=self.obj._get_axis_name(axis)))
KeyError: u"None of [Index([u'F1', u'F2', u'F3', u'F4', u'F5', u'X', u'Y', u'Z', u'C1', u'C2'], dtype='object')] are in the [columns]"
这是我的代码。
import pandas as pd
dataframe= pd.read_csv("lettera.csv", delimiter=',')
df=pd.DataFrame(dataframe)
from sklearn.model_selection import train_test_split
train, test = train_test_split(df, test_size = 0.2)
train_features = train[['F1','F2','F3','F4','F5','X','Y','Z','C1','C2']]
这些是csv文件的内容。
LABEL, F1, F2, F3, F4, F5, X, Y, Z, C1, C2
1, 631, 761, 739, 751, 743, 14120, -5320, 7404, 0, 0
1, 632, 759, 740, 751, 744, 14108, -5276, 7444, 0, 0
1, 630, 761, 740, 752, 743, 14228, -5104, 7680, 0, 0
1, 630, 761, 738, 750, 743, 14256, -5148, 7672, 0, 0
1, 632, 759, 740, 751, 744, 14172, -5256, 7376, 0, 0
1, 632, 759, 742, 751, 746, 14288, -5512, 7412, 0, 0
1, 632, 759, 742, 751, 744, 14188, -5200, 7416, 0, 0
1, 634, 759, 738, 751, 743, 14252, -5096, 7524, 0, 0
1, 630, 759, 739, 751, 743, 14364, -5124, 7612, 0, 0
1, 630, 759, 740, 751, 744, 14192, -5316, 7424, 0, 0
1, 631, 760, 739, 752, 743, 14292, -5100, 7404, 0, 0
1, 634, 759, 738, 751, 742, 14232, -5188, 7468, 0, 0
1, 632, 759, 740, 751, 744, 14288, -5416, 7552, 0, 0
1, 630, 760, 739, 752, 743, 14344, -5072, 7816, 0, 0
1, 631, 760, 739, 752, 743, 14320, -4992, 7444, 0, 0
1, 630, 762, 739, 751, 746, 14220, -5172, 7544, 0, 0
1, 630, 759, 739, 751, 742, 14280, -5176, 7416, 0, 0
1, 630, 760, 738, 752, 740, 14360, -5028, 7468, 0, 0
1, 632, 759, 738, 752, 741, 14384, -5108, 7364, 0, 0
1, 629, 757, 737, 751, 741, 14224, -5108, 7536, 0, 0
1, 629, 758, 740, 751, 744, 14412, -5136, 7956, 0, 0
1, 629, 761, 740, 750, 744, 14468, -4868, 7100, 0, 0
1, 629, 760, 738, 752, 741, 14504, -4964, 6600, 0, 0
1, 629, 758, 738, 749, 741, 14440, -5112, 6828, 0, 0
1, 629, 760, 738, 752, 741, 14484, -5016, 7556, 0, 0
谢谢。
答案 0 :(得分:2)
问题是您的列名中有个空格;这是保存数据并按完成方式加载数据框后得到的结果:
df.columns
# result:
Index(['LABEL', ' F1', ' F2', ' F3', ' F4', ' F5', ' X', ' Y', ' Z', ' C1',
' C2'],
dtype='object')
因此,将这些空格放回列名称中可消除错误:
train_features = train[[' F1',' F2',' F3',' F4',' F5',' X',' Y',' Z',' C1',' C2']] # works OK
但是可以说,在列名中使用空格不是一种好习惯(您看到了会发生什么!);因此最好在加载过程中消除它们。这是执行此操作的端到端代码(还消除了不必要的第二个数据帧):
import pandas as pd
df= pd.read_csv("lettera.csv", delimiter=',', header=None, skiprows=1, names=['LABEL','F1','F2','F3','F4','F5','X','Y','Z','C1','C2'])
from sklearn.model_selection import train_test_split
train, test = train_test_split(df, test_size = 0.2)
train_features = train[['F1','F2','F3','F4','F5','X','Y','Z','C1','C2']] # works OK
答案 1 :(得分:0)
还尝试将您的csv加载为制表符分隔的数据框:
{{1}}
答案 2 :(得分:0)
尝试
import pandas as pd
dataframe= pd.read_csv("lettera.csv", delimiter=','sep=r', ')
我在", ;, ", -
上遇到了同样的问题,并且在您的数据中看到了这个(", ")
。
如果您可以在数据集中看到单独的符号,则可以使用sep =
。
答案 3 :(得分:0)
就我而言,这是因为我的数据框中的列名有空格。我通过用 _
替换空格来重命名我的 df 中的列名。
# remove special character
df.columns = df.columns.str.replace(' ', '')
答案 4 :(得分:0)
我尝试在 apply()
结果之外的数据框中创建新列时遇到了同样的错误:
>>> df[["foo","bar"]] = df.apply(lambda r: ["foobar","baz"], axis=1)
"None of [Index(['foo', 'bar'], dtype='object')] are in the [columns]"
解决方案只是使用 result_type="expand"
参数作为 apply()
:
df[["foo","bar"]] = df.apply(lambda r: ["foobar","baz"], axis=1, result_type="expand")
我找到了这个解决方案 on this answer,值得点赞。