ShanZhengYang ShanZhengYang - 3 months ago 21
Python Question

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


?

Answer

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)
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