0

我的数据：

a,b,c,d,e,f
1.5,4.8,,6.3
1.60,5.2,6.5,7.2
1.70,5.5,6.6,8.3,5.7
1.80,6.1,6.7,9.7,6.2
1.90,7.1,6.8,11.1,6.7
2,,6.8,12.5,7.3
2.08,,,,7.8
2.1,,7.2
2.2,,8.0
2.3,,8.7
2.4,,9.2,8.2

from pandas import read_csv
ds = read_csv ('lin-nan.dat', index_col=0, sep=',')

Traceback (most recent call last):
  File "read_lin.py", line 7, in <module>
    ds = read_csv ('lin-nan.dat', index_col=0, sep=',')
  File "/home/nbecker/.local/lib/python2.7/site-packages/pandas/io/parsers.py", line 253, in read_csv
    return _read(TextParser, filepath_or_buffer, kdict)
  File "/home/nbecker/.local/lib/python2.7/site-packages/pandas/io/parsers.py", line 202, in _read
    return parser.get_chunk()
  File "/home/nbecker/.local/lib/python2.7/site-packages/pandas/io/parsers.py", line 844, in get_chunk
    alldata = self._rows_to_cols(content)
  File "/home/nbecker/.local/lib/python2.7/site-packages/pandas/io/parsers.py", line 809, in _rows_to_cols
    raise ValueError(msg)
ValueError: Expecting 6 columns, got 5 in row 1
4

2 回答 2

1

您可以使用该功能的error_bad_lines=False选项read_csv。它会自动跳过格式错误的行并打印它们。

于 2013-03-21T01:31:08.847 回答
0

问题是您没有任何长度为 6 的列（最长为 5），我认为没有关键字 inread_csv可以克服这一点。

一种解决方案是更明确：

In [1]: df = pd.read_csv('lin-nan.dat', names=list('abcde'), index_col=0, skiprows=1)

In [2]: df['f'] = np.nan

In [3]: df
Out[3]: 
        b    c     d    e   f
a                            
1.50  4.8  NaN   6.3  NaN NaN
1.60  5.2  6.5   7.2  NaN NaN
1.70  5.5  6.6   8.3  5.7 NaN
1.80  6.1  6.7   9.7  6.2 NaN
1.90  7.1  6.8  11.1  6.7 NaN
2.00  NaN  6.8  12.5  7.3 NaN
2.08  NaN  NaN   NaN  7.8 NaN
2.10  NaN  7.2   NaN  NaN NaN
2.20  NaN  8.0   NaN  NaN NaN
2.30  NaN  8.7   NaN  NaN NaN
2.40  NaN  9.2   8.2  NaN NaN
于 2012-11-19T13:50:47.473 回答