使用熊貓讀取和處理數據是很普遍的，但存在一些內存問題。我可以讀取一個大文件：import pandas as pddf = pd.read_csv('mydata.csv.gz', sep=';')但是，在使用Dask進行相同操作時，出現錯誤：import dask.dataframe as dddf_base = dd.read_csv('CoilsSampleFiltered.csv.gz', sep=';')追溯：---------------------------------------------------------------------------UnicodeDecodeError                        Traceback (most recent call last)<ipython-input-7-abc513f2a657> in <module>()----> 1 df_base = dd.read_csv('CoilsSampleFiltered.csv.gz', sep=';')~\AppData\Local\Continuum\Anaconda3\lib\site-packages\dask\dataframe\io\csv.py in read(urlpath, blocksize, collection, lineterminator, compression, sample, enforce, assume_missing, storage_options, **kwargs)    424                            enforce=enforce, assume_missing=assume_missing,    425                            storage_options=storage_options,--> 426                            **kwargs)    427     read.__doc__ = READ_DOC_TEMPLATE.format(reader=reader_name,    428                                             file_type=file_type)~\AppData\Local\Continuum\Anaconda3\lib\site-packages\dask\dataframe\io\csv.py in read_pandas(reader, urlpath, blocksize, collection, lineterminator, compression, sample, enforce, assume_missing, storage_options, **kwargs)    324     325     # Use sample to infer dtypes--> 326     head = reader(BytesIO(b_sample), **kwargs)    327     328     specified_dtypes = kwargs.get('dtype', {})我正在嘗試找出問題所在。該文件由R編寫，R默認情況下使用utf-8。