pandas 读取excel框架时跳过特定的列集 - 熊猫
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Skip specific set of columns when reading excel frame - pandas
提问by Juan David
I know beforehand what columns I don't need from an excel file and I'd like to avoid them when reading the file to improve the performance. Something like this:
我事先知道excel文件中不需要哪些列，并且在读取文件以提高性能时我想避免使用它们。像这样的东西：
import pandas as pd
df = pd.read_excel('large_excel_file.xlsx', skip_cols=['col_a', 'col_b',...,'col_zz'])
There is nothing related to this in the documentation. is there any workaround for this?
文档中没有与此相关的任何内容。有什么解决方法吗？
采纳答案by MaxU
You can use the following technique:
您可以使用以下技术：
In [7]: cols2skip = [2,5,8]
In [8]: cols = [i for i in range(10) if i not in cols2skip]
In [9]: cols
Out[9]: [0, 1, 3, 4, 6, 7, 9]
and then
进而
df = pd.read_excel(filename, usecols=cols)
回答by MarMat
If your version of pandas allows (check first if you can pass a function to usecols), I would try something like:
如果您的 Pandas 版本允许（首先检查您是否可以将函数传递给 usecols），我会尝试以下操作：
import pandas as pd
df = pd.read_excel('large_excel_file.xlsx', usecols=lambda x: 'Unnamed' not in x,)
This should skip all columns without header names. You could substitute 'Unnamed' with a list of column names you do not want.
这应该跳过所有没有标题名称的列。您可以将“未命名”替换为您不需要的列名列表。
