以下是我的代码
import pandas as pd
pd.set_option('display.max_rows',50) #Extending the amout of viewable rows
pd.set_option('display.max_colwidth',100) #extending the amount of viewable column width
col = ["bytes",'N',"type","root","time","algbw","busbw","delta"]
df = pd.read_table('test-pairs.txt',header=None,error_bad_lines = False,
comment = '#')#,skiprows=Skip) #, squeeze=False )
print df
以下是我的结果
0
0 0 - 1
1 2000000000 2000000000 char 0 88.307 22.65 22.65 0e+00
2 2000000000 2000000000 char 1 87.351 22.90 22.90 0e+00
3 0 - 2
4 2000000000 2000000000 char 0 88.328 22.64 22.64 0e+00
5 2000000000 2000000000 char 1 87.343 22.90 22.90 0e+00
6 0 - 3
7 2000000000 2000000000 char 0 78.093 25.61 25.61 0e+00
8 2000000000 2000000000 char 1 78.203 25.57 25.57 0e+00
9 0 - 4
10 2000000000 2000000000 char 0 78.042 25.63 25.63 0e+00
11 2000000000 2000000000 char 1 76.976 25.98 25.98 0e+00
12 0 - 5
13 2000000000 2000000000 char 0 220.868 9.06 9.06 0e+00
14 2000000000 2000000000 char 1 205.188 9.75 9.75 0e+00
15 0 - 6
16 2000000000 2000000000 char 0 217.028 9.22 9.22 0e+00
17 2000000000 2000000000 char 1 214.294 9.33 9.33 0e+00
18 0 - 7
19 2000000000 2000000000 char 0 217.843 9.18 9.18 0e+00
20 2000000000 2000000000 char 1 205.845 9.72 9.72 0e+00
21 1 - 2
22 2000000000 2000000000 char 0 87.428 22.88 22.88 0e+00
23 2000000000 2000000000 char 1 78.064 25.62 25.62 0e+00
24 1 - 3
.. ...
59 2000000000 2000000000 char 1 208.865 9.58 9.58 0e+00
60 3 - 6
61 2000000000 2000000000 char 0 214.659 9.32 9.32 0e+00
62 2000000000 2000000000 char 1 214.902 9.31 9.31 0e+00
63 3 - 7
64 2000000000 2000000000 char 0 87.359 22.89 22.89 0e+00
65 2000000000 2000000000 char 1 87.346 22.90 22.90 0e+00
66 4 - 5
67 2000000000 2000000000 char 0 87.767 22.79 22.79 0e+00
68 2000000000 2000000000 char 1 87.355 22.90 22.90 0e+00
69 4 - 6
70 2000000000 2000000000 char 0 87.803 22.78 22.78 0e+00
71 2000000000 2000000000 char 1 87.343 22.90 22.90 0e+00
72 4 - 7
73 2000000000 2000000000 char 0 76.989 25.98 25.98 0e+00
74 2000000000 2000000000 char 1 77.033 25.96 25.96 0e+00
75 5 - 6
76 2000000000 2000000000 char 0 88.580 22.58 22.58 0e+00
77 2000000000 2000000000 char 1 77.140 25.93 25.93 0e+00
78 5 - 7
79 2000000000 2000000000 char 0 87.508 22.86 22.86 0e+00
80 2000000000 2000000000 char 1 87.375 22.89 22.89 0e+00
81 6 - 7
82 2000000000 2000000000 char 0 87.305 22.91 22.91 0e+00
83 2000000000 2000000000 char 1 76.999 25.97 25.97 0e+00
您好，我正在将Pandas与Python配合使用。我试图解析列，并尝试从代码列表中将列命名为“ col”。我尝试使用sep =“”和sep =“ \ s +”，但是这些对我不起作用。我想将诸如0-1,0-2,0-3 ... 6-7之类的索引保留为列表。有什么办法去做吗？任何帮助，将不胜感激。如果此信息相关，则为Idk，但在编译代码时显示[84行x 1列]。
答案 0 :(得分：0)
test-pairs.txt 文件中的列如何分隔？从问题陈述中，我假设它们由制表符或空格分隔。尝试以下方法，
df = pd.read_table('test-pairs.txt', header=None, names=col, sep='\s+')
要对行进行索引的方式真的很难理解。您能否通过一些示例详细说明一下输入是什么以及期望输出是什么？