Python Pandas:读取文件时如何跳过列? [英] Python Pandas : How to skip columns when reading a file?

问题描述

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

当我用熊猫打开它时:

a = pd.read_table("file", header=None, sep=" ")

它告诉我:

CParserError: Error tokenizing data. C error: Expected 9 fields in line 2, saw 12

我基本上想要拥有的是与skiprows选项类似的东西，它将允许我做类似的事情:

What I'd basically like to have is something similar to the skiprows option which would allow me to do something like :

a = pd.read_table("file", header=None, sep=" ", skipcolumns=[8:])

我知道我可以使用awk重新设置该表格的格式，但是我想知道是否存在Pandas解决方案.

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.

谢谢.

推荐答案

usecols参数允许您选择要使用的列:

The usecols parameter allows you to select which columns to use:

a = pd.read_table("file", header=None, sep=" ", usecols=range(8))

但是，要接受不规则的列数，还需要使用engine='python'.

However, to accept irregular column counts you need to also use engine='python'.

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