出現的情況 user_log = pd.read_csv(’一個1.8G的文件‘) # 已證明8G內存的電腦不行，在jupyter種操作的時候結果如下： --------------------------------------------------------------------------- MemoryError Traceback (most recent call last) <ipython-input-26-126c6dffbe38> in <module>() ----> 1 user_log = pd.read_csv(path6) 2 user_log.sample(5) E:\miniconda\envs\course_py35\lib\site-packages\pandas\io\parsers.py in parser_f(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision) 653 skip_blank_lines=skip_blank_lines) 654 --> 655 return _read(filepath_or_buffer, kwds) 656 657 parser_f.__name__ = name E:\miniconda\envs\course_py35\lib\site-packages\pandas\io\parsers.py in _read(filepath_or_buffer, kwds) 409 410 try: --> 411 data = parser.read(nrows) 412 finally: 413 parser.close() E:\miniconda\envs\course_py35\lib\site-packages\pandas\io\parsers.py in read(self, nrows) 1021 new_rows = len(index) 1022 -> 1023 df = DataFrame(col_dict, columns=columns, index=index) 1024 1025 self._currow += new_rows E:\miniconda\envs\course_py35\lib\site-packages\pandas\core\frame.py in __init__(self, data, index, columns, dtype, copy) 273 dtype=dtype, copy=copy) 274 elif isinstance(data, dict): --> 275 mgr = self._init_dict(data, index, columns, dtype=dtype) 276 elif isinstance(data, ma.MaskedArray): 277 import numpy.ma.mrecords as mrecords E:\miniconda\envs\course_py35\lib\site-packages\pandas\core\frame.py in _init_dict(self, data, index, columns, dtype) 409 arrays = [data[k] for k in keys] 410 --> 411 return _arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype) 412 413 def _init_ndarray(self, values, index, columns, dtype=None, copy=False): E:\miniconda\envs\course_py35\lib\site-packages\pandas\core\frame.py in _arrays_to_mgr(arrays, arr_names, index, columns, dtype) 5504 axes = [_ensure_index(columns), _ensure_index(index)] 5505 -> 5506 return create_block_manager_from_arrays(arrays, arr_names, axes) 5507 5508 E:\miniconda\envs\course_py35\lib\site-packages\pandas\core\internals.py in create_block_manager_from_arrays(arrays, names, axes) 4307 4308 try: -> 4309 blocks = form_blocks(arrays, names, axes) 4310 mgr = BlockManager(blocks, axes) 4311 mgr._consolidate_inplace() E:\miniconda\envs\course_py35\lib\site-packages\pandas\core\internals.py in form_blocks(arrays, names, axes) 4379 4380 if len(int_items): -> 4381 int_blocks = _multi_blockify(int_items) 4382 blocks.extend(int_blocks) 4383 E:\miniconda\envs\course_py35\lib\site-packages\pandas\core\internals.py in _multi_blockify(tuples, dtype) 4448 for dtype, tup_block in grouper: 4449 -> 4450 values, placement = _stack_arrays(list(tup_block), dtype) 4451 4452 block = make_block(values, placement=placement) E:\miniconda\envs\course_py35\lib\site-packages\pandas\core\internals.py in _stack_arrays(tuples, dtype) 4491 shape = (len(arrays),) + _shape_compat(first) 4492 -> 4493 stacked = np.empty(shape, dtype=dtype) 4494 for i, arr in enumerate(arrays): 4495 stacked[i] = _asarray_compat(arr) MemoryError: 目的 查看任務管理器，內存使用量達到了90%以上，如何在不shutdown當前文件的情況下回收讀取這個文件時占用的內存？