python - 从无法放入内存的巨 Pandas 数据框中删除索引

Question

我有一个包含 5000 万条记录的文件，我有一个需要从文件中删除的索引列表。如果我想使用 pandas dataframe 来读取文件——我可能会遇到内存问题(如果我的内存有限)。假设我这样做:

df = pd.read_csv('input_file')
df = df.drop(df.index[example_ix_list])
df.to_csv('input_file', index=False)

我可能会遇到内存问题:

  File "/home/ec2-user/CloudMatcher/cloudmatcher/core/execution/user_interaction.py", line 768, in process
    new_unlabel_df = unlabel_df.drop(unlabel_df.index[list_ix])
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/generic.py", line 2162, in drop
    dropped = self.reindex(**{axis_name: new_axis})
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/frame.py", line 2733, in reindex
    **kwargs)
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/generic.py", line 2515, in reindex
    fill_value, copy).__finalize__(self)
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/frame.py", line 2679, in _reindex_axes
    fill_value, limit, tolerance)
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/frame.py", line 2690, in _reindex_index
    allow_dups=False)
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/generic.py", line 2627, in _reindex_with_indexers
    copy=copy)
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/internals.py", line 3897, in reindex_indexer
    for blk in self.blocks]
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/internals.py", line 1046, in take_nd
    allow_fill=True, fill_value=fill_value)
  File "/home/ec2-user/anaconda2/envs/cloudmatch/lib/python2.7/site-packages/pandas/core/algorithms.py", line 1467, in take_nd
    out = np.empty(out_shape, dtype=dtype)
MemoryError

问:我可以使用 pandas dataframe 分块读取文件并使用列表删除索引吗？如果是这样怎么办？或者我错过了一些更好的方法。

非常感谢。

Answer 1

试试这个:

pd.read_csv('input_file', skiprows=example_ix_list).to_csv('input_file', index=False)

如果仍然出现 MemoryError，可以使用 chunksize 参数:

example_ix_list = pd.Index(example_ix_list)

for df in pd.read_csv('input_file', chunksize=10**5):
    df.loc[df.index.difference(example_ix_list)] \
      .to_csv('new_file_name', index=False, header=None, mode='a')