熊猫误读文件中的行[副本]

我正在尝试使用Python3.6用Pandas读取以下文件:

$ cat tmp2.txt
somename     nan                                0       0     1     0     0       1       11    0.909091  0       0     1     0     0     7     1     1     0     0     0       0     2       
somename     nan                                0       0     1     0     0       1       36    0.972222  0       0     7     0     5     22    0     6     1     0     0       0     2       
somename UgzVrvH-ahjgfT9-NfN4AaABAg.8e3_FgQnopN8e4FLHwai7v0       0     1     0     0             0       25    0.920000  0       0     0     0     2     22    0     1     0     0     0       0           0   
somename     UgxyXxibolL_qOhMsyZ4AaABAg.8eApKy29u5J8eAxINbTH2m0       0     1     0     0       0       13    1.000000  0       0     0     0     1     10    0     2     0     0     0       0     0       
somename     nan                                0       0     0     0     0       2       56    0.839286  0       0     0     0     11    14    5     7     3     0     3       1     10

当我试着和熊猫一起读的时候:

>>> import pandas as pd
>>> df  = pd.read_csv(header=None, filepath_or_buffer="tmp2.txt", delim_whitespace=True, index_col=0)
>>> df.values[2,:]
array(['UgzVrvH-ahjgfT9-NfN4AaABAg.8e3_FgQnopN8e4FLHwai7v0', 0, 1, 0, 0,
       0, 25, 0.92, 0.0, 0, 0, 0, 2, 22, 0, 1, 0, 0, 0, 0, 0, nan],
      dtype=object)
>>> df.values[3,:]
array(['UgxyXxibolL_qOhMsyZ4AaABAg.8eApKy29u5J8eAxINbTH2m0', 0, 1, 0, 0,
       0, 13, 1.0, 0.0, 0, 0, 0, 1, 10, 0, 2, 0, 0, 0, 0, 0, nan],
      dtype=object)
>>> df.values[4,:]
array([nan, 0, 0, 0, 0, 0, 2, 56.0, 0.8392860000000001, 0, 0, 0, 0, 11,
       14, 5, 7, 3, 0, 3, 1, 10.0], dtype=object)

当我打印时可以看到 df.values[2,:] 和 df.values[3,:] 我得到额外的东西 nan 最后。这似乎是一个问题,每行有最多的字符数,但是对于 pandas.read_csv 没有任何提及。

问题:是什么原因造成的,如何让pandas.read_csv正确读取此文件?