How to select a range of values in a pandas dataframe column?

Question

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

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?

I expected to use

-0.5 < df["two"] < 0.5

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().

I tried

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

But this outputs all True.

The correct output should be

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

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

EDIT: Question

Using .between() with

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

would would be the difference between

 -0.5 < df['two'] < 0.5

and inequalities like

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

?

Answer 1

Use between with inclusive=False for strict inequalities:

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

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)

Answer 2

.between is a good solution, but if you want finer control use this:

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

The operator & is different from and. The other operators are | for or, ~ for not. See this discussion for more info.

Your statement was the same as this:

(0.5 <= df['two']) and (df['two'] < 0.5)

Hence it raised the error.