Python之将数据帧保存到 CSV "too many indices for array"错误

我正在尝试将数据帧保存为 CSV 并收到“数组索引太多”错误。用于保存的代码是-

df.to_csv('CCS_Matrix.csv') 

数据框看起来像这样

  Var10  Var100   Var101     
0   0       1       1 
1   0       0       1 
2   0       1       0 

数据集中有 250 列和大约 1000 万行。

数据框的数据类型是

Var10     int64 
Var100    int64 
Var101    int64 
etc. 

250 列的所有数据类型都相同。

这里是错误信息的完整输出

--------------------------------------------------------------------------- 
IndexError                                Traceback (most recent call last) 
<ipython-input-16-37cbe55e6c0d> in <module>() 
----> 1 df.to_csv('CCS_Matrix.csv', encoding='utf-8') 
 
~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py in to_csv(self, path_or_buf, sep, na_rep, float_format, columns, header, index, index_label, mode, encoding, compression, quoting, quotechar, line_terminator, chunksize, tupleize_cols, date_format, doublequote, escapechar, decimal) 
   1401                                      doublequote=doublequote, 
   1402                                      escapechar=escapechar, decimal=decimal) 
-> 1403         formatter.save() 
   1404  
   1405         if path_or_buf is None: 
 
~/anaconda3/lib/python3.6/site-packages/pandas/io/formats/format.py in save(self) 
   1590                 self.writer = csv.writer(f, **writer_kwargs) 
   1591  
-> 1592             self._save() 
   1593  
   1594         finally: 
 
~/anaconda3/lib/python3.6/site-packages/pandas/io/formats/format.py in _save(self) 
   1691                 break 
   1692  
-> 1693             self._save_chunk(start_i, end_i) 
   1694  
   1695     def _save_chunk(self, start_i, end_i): 
 
~/anaconda3/lib/python3.6/site-packages/pandas/io/formats/format.py in _save_chunk(self, start_i, end_i) 
   1705                                   decimal=self.decimal, 
   1706                                   date_format=self.date_format, 
-> 1707                                   quoting=self.quoting) 
   1708  
   1709             for col_loc, col in zip(b.mgr_locs, d): 
 
~/anaconda3/lib/python3.6/site-packages/pandas/core/internals.py in to_native_types(self, slicer, na_rep, quoting, **kwargs) 
    611         values = self.values 
    612         if slicer is not None: 
--> 613             values = values[:, slicer] 
    614         mask = isnull(values) 
    615  
 
~/anaconda3/lib/python3.6/site-packages/pandas/core/sparse/array.py in __getitem__(self, key) 
    417             return self._get_val_at(key) 
    418         elif isinstance(key, tuple): 
--> 419             data_slice = self.values[key] 
    420         else: 
    421             if isinstance(key, SparseArray): 
 
IndexError: too many indices for array 

请您参考如下方法:

你能打印出 type(df) 吗？ 我在 SparseDataFrames here 中注意到了这个问题.

我能够通过在 SparseDataFrame 上调用 .to_dense() 来解决问题，生成一个传统的 DataFrame。之后工作正常。显然，出于内存原因，这并不理想，但至少它在短期内有效。

pandas团队已经回应，确实是bug。