我查看了python文档，到目前为止这段代码没有任何问题。但是，当我在Rodeo IDE上运行此代码时，它会将此标记为错误，有人可以指导我找到正确的方向或发布解决此问题的答案。
我的代码：
#%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
#pd.set_option("display.max_rows", 16)
#LARGE_FIGSIZE = (12, 8)
#C:\\Users\\User\\Documents\\dataScience\\pandas_tutorial\\climate_timeseries\\data\\temperatures\\xxxx.txt"
#https://github.com/jonathanrocher/pandas_tutorial/blob/master/climate_timeseries/data/temperatures/GLB.Ts+dSST.txt
giss_temp = pd.read_table("C:\\Users\\User\\Documents\\dataScience\\pandas_tutorial\\climate_timeseries\\data\\temperatures\\xxxx.txt",sep="\s+",skiprows=7,skipfooter=7,engine="python")
print(giss_temp)
我的错误讯息：
ValueError: Expected 2 fields in line 160, saw 87
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-31-02b52eb96870> in <module>()
11 #C:\\Users\\User\\Documents\\dataScience\\pandas_tutorial\\climate_timeseries\\data\\temperatures\\xxxx.txt"
12 #https://github.com/jonathanrocher/pandas_tutorial/blob/master/climate_timeseries/data/temperatures/GLB.Ts+dSST.txt
---> 13 giss_temp = pd.read_table("https://github.com/jonathanrocher/pandas_tutorial/blob/master/climate_timeseries/data/temperatures/GLB.Ts+dSST.txt",sep="\s+",skiprows=7,skipfooter=7,engine="python")
14 print(giss_temp)
C:\Users\User\AppData\Local\rodeo\app-2.5.2\resources\conda\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)
643 skip_blank_lines=skip_blank_lines)
644
--> 645 return _read(filepath_or_buffer, kwds)
646
647 parser_f.__name__ = name
C:\Users\User\AppData\Local\rodeo\app-2.5.2\resources\conda\lib\site-packages\pandas\io\parsers.py in _read(filepath_or_buffer, kwds)
398 return parser
399
--> 400 data = parser.read()
401 parser.close()
402 return data
C:\Users\User\AppData\Local\rodeo\app-2.5.2\resources\conda\lib\site-packages\pandas\io\parsers.py in read(self, nrows)
936 raise ValueError('skipfooter not supported for iteration')
937
--> 938 ret = self._engine.read(nrows)
939
940 if self.options.get('as_recarray'):
C:\Users\User\AppData\Local\rodeo\app-2.5.2\resources\conda\lib\site-packages\pandas\io\parsers.py in read(self, rows)
1990 content = content[1:]
1991
-> 1992 alldata = self._rows_to_cols(content)
1993 data = self._exclude_implicit_index(alldata)
1994
C:\Users\User\AppData\Local\rodeo\app-2.5.2\resources\conda\lib\site-packages\pandas\io\parsers.py in _rows_to_cols(self, content)
2505 msg = ('Expected %d fields in line %d, saw %d' %
2506 (col_len, row_num + 1, zip_len))
-> 2507 raise ValueError(msg)
2508
2509 if self.usecols:
ValueError: Expected 2 fields in line 160, saw 87
>>>
ClearInterruptRestart
答案 0 :(得分：1)
您应该使用原始文件网址：
In [390]: pd.options.display.max_rows = 10
In [391]: url = 'https://raw.githubusercontent.com/jonathanrocher/pandas_tutorial/master/climate_timeseries/data/temperatures/GLB.Ts%2BdSST.txt'
In [392]: pd.read_csv(url, skiprows=7, delim_whitespace=True, skipfooter=12, error_bad_lines=False, engine='python')
Out[392]:
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec J-D D-N DJF MAM JJA SON Year.1
0 1880 -34 -27 -22 -30 -16 -24 -19 -12 -20 -19 -16 -21 -22 *** **** -23 -18 -18 1880
1 1881 -13 -16 -2 -3 -3 -27 -12 -8 -18 -23 -28 -18 -14 -14 -17 -3 -15 -23 1881
2 1882 3 4 -2 -24 -20 -32 -27 -11 -11 -25 -25 -37 -17 -16 -4 -15 -23 -20 1882
3 1883 -38 -38 -12 -20 -20 -8 -3 -13 -19 -19 -28 -21 -20 -21 -38 -18 -8 -22 1883
4 1884 -20 -14 -31 -36 -33 -36 -31 -24 -29 -25 -29 -25 -28 -28 -18 -33 -31 -28 1884
.. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
137 2011 45 44 57 60 47 54 70 69 52 60 50 48 55 55 45 55 64 54 2011
138 2012 38 43 52 62 71 59 50 56 68 73 69 46 57 57 43 62 55 70 2012
139 2013 62 52 60 48 56 61 53 61 73 61 75 61 60 59 53 55 58 70 2013
140 2014 68 44 71 72 79 62 50 74 81 78 64 74 68 67 58 74 62 74 2014
141 2015 75 80 84 71 **** **** **** **** **** **** **** **** **** *** 76 **** **** **** 2015
[142 rows x 20 columns]