我有以下格式的 「CSV」 數據文件(當然,這是相當一個TSV):如何讀取製表符分隔的CSV格式?
event pdg x y z t px py pz ekin 3383 11 -161.515 5.01938e-05 -0.000187112 0.195413 0.664065 0.126078 -0.736968 0.00723234 1694 11 -161.515 -0.000355633 0.000263174 0.195413 0.511853 -0.523429 0.681196 0.00472714 4228 11 -161.535 6.59631e-06 -3.32796e-05 0.194947 -0.713983 -0.0265468 -0.69966 0.0108681 4233 11 -161.515 -0.000524488 6.5069e-05 0.195413 0.942642 0.331324 0.0406377 0.017594
這個文件解釋爲,是在pandas
:
from pandas import read_csv, read_table
data = read_csv("test.csv", sep="\t", index_col=False) # Works
data = read_table("test.csv", index_col=False) # Works
然而,當我嘗試在blaze
讀它(聲明使用熊貓的關鍵字參數),拋出一個異常:這些
from blaze import Data
Data("test.csv") # Attempt 1
Data("test.csv", sep="\t") # Attempt 2
Data("test.csv", sep="\t", index_col=False) # Attempt 3
無工程和熊貓根本不使用。試圖推斷列名稱和類型的「嗅探器」僅從標準庫調用csv.Sniffer.sniff()
(失敗)。
有沒有辦法如何正確閱讀這個文件(因爲它的「小兄弟」有幾百MB,我想用blaze的順序處理能力)?
感謝您的任何想法。
編輯:我想可能是里程/ CSV的問題,並提交了問題:https://github.com/blaze/odo/issues/327
EDIT2: 完整的錯誤:
Error Traceback (most recent call last) in() ----> 1 bz.Data("test.csv", sep="\t", index_col=False) /home/[username-hidden]/anaconda3/lib/python3.4/site-packages/blaze/interactive.py in Data(data, dshape, name, fields, columns, schema, **kwargs) 54 if isinstance(data, _strtypes): 55 data = resource(data, schema=schema, dshape=dshape, columns=columns, ---> 56 **kwargs) 57 if (isinstance(data, Iterator) and 58 not isinstance(data, tuple(not_an_iterator))): /home/[username-hidden]/anaconda3/lib/python3.4/site-packages/odo/regex.py in __call__(self, s, *args, **kwargs) 62 63 def __call__(self, s, *args, **kwargs): ---> 64 return self.dispatch(s)(s, *args, **kwargs) 65 66 @property /home/[username-hidden]/anaconda3/lib/python3.4/site-packages/odo/backends/csv.py in resource_csv(uri, **kwargs) 276 @resource.register('.+\.(csv|tsv|ssv|data|dat)(\.gz|\.bz2?)?') 277 def resource_csv(uri, **kwargs): --> 278 return CSV(uri, **kwargs) 279 280 /home/[username-hidden]/anaconda3/lib/python3.4/site-packages/odo/backends/csv.py in __init__(self, path, has_header, encoding, sniff_nbytes, **kwargs) 102 if has_header is None: 103 self.has_header = (not os.path.exists(path) or --> 104 infer_header(path, sniff_nbytes)) 105 else: 106 self.has_header = has_header /home/[username-hidden]/anaconda3/lib/python3.4/site-packages/odo/backends/csv.py in infer_header(path, nbytes, encoding, **kwargs) 58 with open_file(path, 'rb') as f: 59 raw = f.read(nbytes) ---> 60 return csv.Sniffer().has_header(raw if PY2 else raw.decode(encoding)) 61 62 /home/[username-hidden]/anaconda3/lib/python3.4/csv.py in has_header(self, sample) 392 # subtracting from the likelihood of the first row being a header. 393 --> 394 rdr = reader(StringIO(sample), self.sniff(sample)) 395 396 header = next(rdr) # assume first row is header /home/[username-hidden]/anaconda3/lib/python3.4/csv.py in sniff(self, sample, delimiters) 187 188 if not delimiter: --> 189 raise Error("Could not determine delimiter") 190 191 class dialect(Dialect): Error: Could not determine delimiter
嗨,那裏。我相信這對我的系統有效。你得到的錯誤是什麼? – wgwz
似乎像安裝dask改變了錯誤被報告給別的東西。我有點困惑。我現在就離開它,只用熊貓解析數據 - 我需要在幾個小時內完成分析。我稍後再回來。謝謝。 –
查看我對帖子的編輯。您的列在純粹的熊貓分析中沒有正確解析。 – wgwz