Python 在 Pandas DataFrame 中选择多个范围的列
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Select multiple ranges of columns in Pandas DataFrame
提问by Alex
I have to read several files some in Excel format and some in CSV format. Some of the files have hundreds of columns.
我必须阅读几个文件，一些是 Excel 格式，一些是 CSV 格式。一些文件有数百列。
Is there a way to select several ranges of columns without specifying all the column names or positions? For example something like selecting columns 1 -10, 15, 17 and 50-100:
有没有办法在不指定所有列名或位置的情况下选择多个列范围？例如，选择第 1 -10、15、17 和 50-100 列：
df = df.ix[1:10, 15, 17, 50:100]
I need to know how to do this both when creating dataframe from Excel files and CSV files and after the data framers created.
我需要知道在从 Excel 文件和 CSV 文件创建数据框时以及在创建数据框之后如何执行此操作。
回答by piRSquared
use np.r_
用 np.r_
np.r_[1:10, 15, 17, 50:100]
array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 17, 50, 51, 52, 53, 54, 55,
56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,
73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
90, 91, 92, 93, 94, 95, 96, 97, 98, 99])
so you can do
所以你可以做
df.iloc[:, np.r_[1:10, 15, 17, 50:100]]
