Question

我有大约190个CSV。每个都有相同的列名。下面共享的一个示例csv：

从每个 csv中，我仅需选择Item，Predicted_BelRd(D2)，Predicted_Ulsoor(D2)，Predicted_ChrchStrt(D2) ，Predicted_BlrClub(D2)，Predicted_Indrangr(D1)，Predicted_Krmngl(D1)，Predicted_KrmnglBkry(D1)，Predicted_HSR(D1)的列，仅 >第一行，并且需要将所有这些行存储到单独的CSV中。因此，最终的CSV应为190行。

为此，我编写了一个代码：

path = '/home/hp/products1'
all_files = glob.glob(path + "/*.csv")
#print(all_files)

columns = ['Item', 'Predicted_BelRd(D2)', 'Predicted_Ulsoor(D2)', 'Predicted_ChrchStrt(D2)', 'Predicted_BlrClub(D2)', 'Predicted_Indrangr(D1)', 'Predicted_Krmngl(D1)', 'Predicted_KrmnglBkry(D1)', 'Predicted_HSR(D1)']
#columns = []
#df.iloc[:, np.r_[1:10, 15, 17, 50:100]]
rows_list = []
for filename in all_files:
    origin_data = pd.read_csv(filename)
    my_data = origin_data[columns]
    rows_list.append(my_data.head(1))

output = pd.DataFrame(rows_list)
#output.to_csv(file_name, sep='\t', encoding='utf-8')
output.to_csv('smallys_final.csv', encoding='utf-8', index=False)

它出现以下错误：

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-7-229c30dd03e1> in <module>()
      9 for filename in all_files:
     10     origin_data = pd.read_csv(filename)
---> 11     my_data = origin_data[columns]
     12     rows_list.append(my_data.head(1))
     13 

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/pandas/core/frame.py in __getitem__(self, key)
   2131         if isinstance(key, (Series, np.ndarray, Index, list)):
   2132             # either boolean or fancy integer index
-> 2133             return self._getitem_array(key)
   2134         elif isinstance(key, DataFrame):
   2135             return self._getitem_frame(key)

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/pandas/core/frame.py in _getitem_array(self, key)
   2175             return self._take(indexer, axis=0, convert=False)
   2176         else:
-> 2177             indexer = self.loc._convert_to_indexer(key, axis=1)
   2178             return self._take(indexer, axis=1, convert=True)
   2179 

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/pandas/core/indexing.py in _convert_to_indexer(self, obj, axis, is_setter)
   1267                 if mask.any():
   1268                     raise KeyError('{mask} not in index'
-> 1269                                    .format(mask=objarr[mask]))
   1270 
   1271                 return _values_from_object(indexer)

KeyError: "['Predicted_BelRd(D2)' 'Predicted_Ulsoor(D2)' 'Predicted_ChrchStrt(D2)'\n 'Predicted_BlrClub(D2)' 'Predicted_Indrangr(D1)' 'Predicted_Krmngl(D1)'\n 'Predicted_KrmnglBkry(D1)' 'Predicted_HSR(D1)'] not in index"

其中一个数据框的内容：

prod = pd.read_csv('/home/hp/products1/' + 'prod[' + str(0) + '].csv', engine='python')
print(prod)

输出：

      Category                         Item  UOM  BelRd(D2)  Ulsoor(D2)  \
0  Food/Bakery  BAKING POWDER SPARSH (1KGS)  PKT          0           0   
1  Food/Bakery  BAKING POWDER SPARSH (1KGS)  PKT          0           0   
2  Food/Bakery  BAKING POWDER SPARSH (1KGS)  PKT          0           0   
3  Food/Bakery  BAKING POWDER SPARSH (1KGS)  PKT          0           0   
4  Food/Bakery  BAKING POWDER SPARSH (1KGS)  PKT          0           0   

   ChrchStrt(D2)  BlrClub(D2)  Indrangr(D1)  Krmngl(D1)  KrmnglBkry(D1)  \
0              0            0             0           0               1   
1              0            0             0           0               0   
2              0            0             0           0               0   
3              0            0             0           0               0   
4              0            0             0           0               1   

   HSR(D1)         date  Predicted_BelRd(D2)  Predicted_Ulsoor(D2)  \
0        0    10 FEB 19                  0.0                   0.0   
1        0    17 FEB 19                  NaN                   NaN   
2        0    24 FEB 19                  NaN                   NaN   
3        0   4 MARCH 19                  NaN                   NaN   
4        0  11 MARCH 19                  NaN                   NaN   

   Predicted_ChrchStrt(D2)  Predicted_BlrClub(D2)  Predicted_Indrangr(D1)  \
0                      0.0                    0.0                     0.0   
1                      NaN                    NaN                     NaN   
2                      NaN                    NaN                     NaN   
3                      NaN                    NaN                     NaN   
4                      NaN                    NaN                     NaN   

   Predicted_Krmngl(D1)  Predicted_KrmnglBkry(D1)  Predicted_HSR(D1)  
0                   0.0                       0.0                0.0  
1                   NaN                       NaN                NaN  
2                   NaN                       NaN                NaN  
3                   NaN                       NaN                NaN  
4                   NaN                       NaN                NaN

编辑：

prod = pd.read_csv('/home/hp/products1/' + 'prod[' + str(0) + '].csv', engine='python')
print(list(prod))

输出：

['Category', 'Item', 'UOM', 'BelRd(D2)', 'Ulsoor(D2)', 'ChrchStrt(D2)', 'BlrClub(D2)', 'Indrangr(D1)', 'Krmngl(D1)', 'KrmnglBkry(D1)', 'HSR(D1)', 'date', 'Predicted_BelRd(D2)', 'Predicted_Ulsoor(D2)', 'Predicted_ChrchStrt(D2)', 'Predicted_BlrClub(D2)', 'Predicted_Indrangr(D1)', 'Predicted_Krmngl(D1)', 'Predicted_KrmnglBkry(D1)', 'Predicted_HSR(D1)']

Answer 1

我认为您需要删除制表符空格并重新执行代码。它可能工作正常。我认为由于多余的制表符空间，数据框无法区分实际值和输出“ KeyError”。

Python +熊猫+数据框：Keyerror

1 个答案: