我在DataFrame中有两列(serverTs,FTs),它们是Unix Time格式的时间戳。 在我的代码中,我需要从另一个中减去一个。当我这样做时,我收到一个错误,说我不能减去字符串。所以我将serverTs和FTs的类型添加为整数。
file = r'S:\Работа с клиентами\Клиенты\BigTV Rating\fts_check.csv'
col_names = ["Day", "vcId", "FTs", "serverTs", "locHost", "tnsTmsec", "Hits", "Uniqs"]
df_empty = pd.DataFrame()
with open(file) as fl:
chunk_iter = pd.read_csv(fl, sep='\t', names=col_names, dtype={'serverTs': np.int32, 'FTs': np.int32}, chunksize = 100000)
for chunk in chunk_iter:
chunk['diff'] = np.array(chunk['serverTs'])-np.array(chunk['FTs'])
chunk = chunk[chunk['diff'] > 180]
df_empty = pd.concat([df_empty,chunk])
但程序给了我一个错误:
TypeError Traceback(最近一次调用 最后)pandas / _libs / parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()
TypeError:无法将数组从dtype('O')转换为dtype('int32') 根据规则'安全'
在处理上述异常期间,发生了另一个异常:
ValueError Traceback(最近一次调用 最后)in() 6 #dtype = {'serverTs':np.int32,'FTs':np.int32}, 7 #chunk_iter = chunk_iter.astype({'serverTs':np.int32,'FTs':np.int32}) ----> 8为chunk_iter中的块: 9 #print(chunk [chunk ['FTs'] =='NaN']) 10 #chunk [['serverTs','FTs']] = chunk [['serverTs','FTs']]。astype('int32')
C:\ ProgramData \ Anaconda3 \ lib \ site-packages \ pandas \ io \ parsers.py in 下一个(个体经营)1040 def 下一个(个体经营):1041尝试: - > 1042返回self.get_chunk()1043,除了StopIteration:1044 self.close()
C:\ ProgramData \ Anaconda3 \ lib \ site-packages \ pandas \ io \ parsers.py in get_chunk(self,size)1104提高StopIteration
1105 size = min(size,self.nrows - self._currow) - > 1106 return self.read(nrows = size)1107 1108C:\ ProgramData \ Anaconda3 \ lib \ site-packages \ pandas \ io \ parsers.py in read(self,nrows)1067引发ValueError('skipfooter 不支持迭代')1068 - > 1069 ret = self._engine.read(nrows)1070 1071 if self.options.get('as_recarray'):
C:\ ProgramData \ Anaconda3 \ lib \ site-packages \ pandas \ io \ parsers.py in 读(self,nrows)1837 def read(self,nrows = None):1838
尝试: - > 1839 data = self._reader.read(nrows)1840除StopIteration:1841 if self._first_chunk:pandas._libs.parsers.TextReader.read()中的pandas / _libs / parsers.pyx
pandas / _libs / parsers.pyx in pandas._libs.parsers.TextReader._read_low_memory()
pandas / _libs / parsers.pyx in pandas._libs.parsers.TextReader._read_rows()
pandas / _libs / parsers.pyx in pandas._libs.parsers.TextReader._convert_column_data()
pandas / _libs / parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()
ValueError:基数为10的int()的无效文字:'FTs'
我正在使用SQL查询从Hadoop获取数据,因此我检查了带字母的任何符号,但只有数字。此外,如果FT有任何不是数字的字符,它就不能出现在数据库中。 可能是什么问题?
答案 0 :(得分:1)
这里的问题是你传递names
和dtypes
参数。这会导致header
充当None
。所以考虑一下:
In [1]: import pandas as pd, numpy as np
In [2]: dt={'serverTs': np.int32, 'FTs': np.int32}
In [3]: import io
In [4]: s = """FTs,serverTs
...: 0,1
...: 1,2
...: """
In [5]: pd.read_csv(io.StringIO(s))
Out[5]:
FTs serverTs
0 0 1
1 1 2
In [6]: pd.read_csv(io.StringIO(s), dtype=dt)
Out[6]:
FTs serverTs
0 0 1
1 1 2
工作正常。但是,如果我通过names
:
In [8]: names = 'FTs','serverTs'
In [9]: pd.read_csv(io.StringIO(s), dtype=dt, names=names)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()
TypeError: Cannot cast array from dtype('O') to dtype('int32') according to the rule 'safe'
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-9-18dcd5477b7e> in <module>()
----> 1 pd.read_csv(io.StringIO(s), dtype=dt, names=names)
/Users/juan/anaconda3/lib/python3.5/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)
707 skip_blank_lines=skip_blank_lines)
708
--> 709 return _read(filepath_or_buffer, kwds)
710
711 parser_f.__name__ = name
/Users/juan/anaconda3/lib/python3.5/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds)
453
454 try:
--> 455 data = parser.read(nrows)
456 finally:
457 parser.close()
/Users/juan/anaconda3/lib/python3.5/site-packages/pandas/io/parsers.py in read(self, nrows)
1067 raise ValueError('skipfooter not supported for iteration')
1068
-> 1069 ret = self._engine.read(nrows)
1070
1071 if self.options.get('as_recarray'):
/Users/juan/anaconda3/lib/python3.5/site-packages/pandas/io/parsers.py in read(self, nrows)
1837 def read(self, nrows=None):
1838 try:
-> 1839 data = self._reader.read(nrows)
1840 except StopIteration:
1841 if self._first_chunk:
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader.read()
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._read_low_memory()
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._read_rows()
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._convert_column_data()
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()
ValueError: invalid literal for int() with base 10: 'FTs'
In [10]:
因此,一种解决方案是传递正确的标头索引:
In [10]: pd.read_csv(io.StringIO(s), dtype=dt, names=names, header=0)
Out[10]:
FTs serverTs
0 0 1
1 1 2
或者更好的是,根本不会通过names
,pandas
无论如何会为你推断:
In [11]: pd.read_csv(io.StringIO(s), dtype=dt)
Out[11]:
FTs serverTs
0 0 1
1 1 2