选择/排除 pandas 中的列集 [英] Selecting/excluding sets of columns in pandas

问题描述

我想根据列选择从现有数据框中创建视图或数据框.

I would like to create views or dataframes from an existing dataframe based on column selections.

例如，我想从一个数据框df1创建一个数据框df2，该数据框保存其中的所有列，除了其中的两列.我尝试执行以下操作，但没有成功:

For example, I would like to create a dataframe df2 from a dataframe df1 that holds all columns from it except two of them. I tried doing the following, but it didn't work:

import numpy as np
import pandas as pd

# Create a dataframe with columns A,B,C and D
df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD'))

# Try to create a second dataframe df2 from df with all columns except 'B' and D
my_cols = set(df.columns)
my_cols.remove('B').remove('D')

# This returns an error ("unhashable type: set")
df2 = df[my_cols]

我做错了什么?也许更笼统地说，大熊猫必须采用什么机制来支持从数据框中挑选和排除排除任意列?

What am I doing wrong? Perhaps more generally, what mechanisms does pandas have to support the picking and exclusions of arbitrary sets of columns from a dataframe?

推荐答案

您可以删除不需要的列，也可以选择所需的列

You can either Drop the columns you do not need OR Select the ones you need

# Using DataFrame.drop
df.drop(df.columns[[1, 2]], axis=1, inplace=True)

# drop by Name
df1 = df1.drop(['B', 'C'], axis=1)

# Select the ones you want
df1 = df[['a','d']]

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