大Pandas数据帧上的外部合并导致内存错误——如何将“大数据”与Pandas合并？

Question

我有两个pandas数据帧df1和df2，格式相当标准：

   one  two  three   feature
A    1    2      3   feature1
B    4    5      6   feature2  
C    7    8      9   feature3   
D    10   11     12  feature4
E    13   14     15  feature5 
F    16   17     18  feature6 
...

和df2的相同格式。这些数据帧的大小约为175MB和140MB。

merged_df = pd.merge(df1, df2, on='feature', how='outer', suffixes=('','_features'))

我得到了以下纪念品：

File "/nfs/sw/python/python-3.5.1/lib/python3.5/site-packages/pandas/tools/merge.py", line 39, in merge
    return op.get_result()
File "/nfs/sw/python/python-3.5.1/lib/python3.5/site-packages/pandas/tools/merge.py", line 217, in get_result
    join_index, left_indexer, right_indexer = self._get_join_info()
File "/nfs/sw/python/python-3.5.1/lib/python3.5/site-packages/pandas/tools/merge.py", line 353, in _get_join_info
    sort=self.sort, how=self.how) 
File "/nfs/sw/python/python-3.5.1/lib/python3.5/site-packages/pandas/tools/merge.py", line 559, in _get_join_indexers
    return join_func(lkey, rkey, count, **kwargs)
File "pandas/src/join.pyx", line 187, in pandas.algos.full_outer_join (pandas/algos.c:61680)
  File "pandas/src/join.pyx", line 196, in pandas.algos._get_result_indexer (pandas/algos.c:61978)
MemoryError

合并时熊猫数据帧是否有“大小限制”？我很惊讶这不起作用。也许这是熊猫的某个版本的虫子？

编辑：如注释中所述，合并列中的许多重复项很容易导致RAM问题。见：Python Pandas Merge Causing Memory Overflow

现在的问题是，我们如何进行合并？似乎最好的方法是以某种方式对数据帧进行分区。

Answer 1

尝试为数值列指定数据类型以减小现有数据帧的大小，例如：

df[['one','two', 'three']] = df[['one','two', 'three']].astype(np.int32)

这将显著减少内存，并有望让您执行合并。