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

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 

?

2 Answers

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) 

.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.