如何在 pandas 数据框列中选择一系列值?

问题描述

import pandas as pd
import numpy as np
data = 'filename.csv'
df = pd.DataFrame(data)
df 

        one       two     three  four   five
a  0.469112 -0.282863 -1.509059  bar   True
b  0.932424  1.224234  7.823421  bar  False
c -1.135632  1.212112 -0.173215  bar  False
d  0.232424  2.342112  0.982342  unbar True
e  0.119209 -1.044236 -0.861849  bar   True
f -2.104569 -0.494929  1.071804  bar  False

我想为某一列选择一个范围，比如列 two.我想选择 -0.5 和 +0.5 之间的所有值.如何做到这一点?

I would like to select a range for a certain column, let's say column two. I would like to select all values between -0.5 and +0.5. How does one do this?

我希望使用

-0.5 < df["two"] < 0.5

但这(自然)给出了一个ValueError:

But this (naturally) gives a ValueError:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

我试过了

-0.5 (< df["two"] < 0.5)

但这会输出所有 True.

正确的输出应该是

0    True
1    False
2    False
3    False
4    False
5    True

在 pandas 数据框列中查找一系列值的正确方法是什么?

What is the correct way to find a range of values in a pandas dataframe column?

问题

使用 .between() 和

df['two'].between(-0.5, 0.5, inclusive=False)

会有区别

 -0.5 < df['two'] < 0.5

和像

 -0.5 =< df['two'] < 0.5

?

推荐答案

使用 between 与 inclusive=False 表示严格不等式:

Use between with inclusive=False for strict inequalities:

df['two'].between(-0.5, 0.5, inclusive=False)

inclusive 参数决定是否包含端点(True: <=, False: <).这适用于两个标志.如果您想要混合不等式，则需要明确编码:

The inclusive parameter determines if the endpoints are included or not (True: <=, False: <). This applies to both signs. If you want mixed inequalities, you'll need to code them explicitly:

(df['two'] >= -0.5) & (df['two'] < 0.5)

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