Python Pandas：读取文件时如何跳过列？
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Python Pandas : How to skip columns when reading a file?
提问by jrjc
I have table formatted as follow :
我的表格格式如下：
foo - bar - 10 2e-5 0.0 some information
quz - baz - 4 1e-2 1 some other description in here
When I open it with pandas doing :
当我用熊猫打开它时：
a = pd.read_table("file", header=None, sep=" ")
It tells me :
它告诉我：
CParserError: Error tokenizing data. C error: Expected 9 fields in line 2, saw 12
What I'd basically like to have is something similar to the skiprows option which would allow me to do something like :
我基本上想要的是类似于 skiprows 选项的东西，它可以让我做类似的事情：
a = pd.read_table("file", header=None, sep=" ", skipcolumns=[8:])
I'm aware that I could re-format this table with awk, but I'd like to known whether a Pandas solution exists or not.
我知道我可以用 重新格式化这个表awk，但我想知道 Pandas 解决方案是否存在。
Thanks.
谢谢。
回答by otus
The usecolsparameter allows you to select which columns to use:
该usecols参数允许您选择要使用的列：
a = pd.read_table("file", header=None, sep=" ", usecols=range(8))
However, to accept irregular column counts you need to also use engine='python'.
但是，要接受不规则的列计数，您还需要使用engine='python'.
回答by Martin Konecny
If you are using Linux/OS X/Windows Cygwin, you should be able to prepare the file as follows:
如果您使用的是 Linux/OS X/Windows Cygwin，您应该能够按如下方式准备文件：
cat your_file | cut -d' ' -f1,2,3,4,5,6,7 > out.file
Then in Python:
然后在 Python 中：
a = pd.read_table("out.file", header=None, sep=" ")
Example:
例子：
Input:
输入：
foo - bar - 10 2e-5 0.0 some information
quz - baz - 4 1e-2 1 some other description in here
Output:
输出：
foo - bar - 10 2e-5 0.0
quz - baz - 4 1e-2 1
You can run this command manually on the command-line, or simply call it from within Python using the subprocessmodule.
您可以在命令行上手动运行此命令，也可以使用subprocess模块从 Python 内部调用它。
