JAG2024
JAG2024

Reputation: 4317

Remove rows in python less than a certain value

I feel like this question must have been answered by someone before, but I can't find an answer on stack overflow!

I have a dataframe result that looks like this and I want to remove all the values less than or equal to 10

>>> result
                       Name              Value      Date
189                   Sall                19.0  11/14/15
191                     Sam               10.0  11/14/15
192                 Richard               21.0  11/14/15
193                  Ingrid                4.0  11/14/15 

This command works and removes all the values that are 10:

df2 = result[result['Value'] != 10]

But when I try to add the <= qualifier I get the error message SyntaxError: invalid syntax

df3 = result[result['Value'] ! <= 10]  

I feel like there is probably a really simple solution.

Upvotes: 47

Views: 150324

Answers (4)

Ashish Tripathi
Ashish Tripathi

Reputation: 311

I have another suggestion, which could help

df3 = result.drop(result[result['Value'] < 10].index)

Upvotes: 9

Janosh
Janosh

Reputation: 4652

There's also df.query():

result.query('Value > 10')
                       Name              Value      Date
189                   Sall                19.0  11/14/15
191                     Sam               10.0  11/14/15
192                 Richard               21.0  11/14/15

Upvotes: 1

Jay Parikh
Jay Parikh

Reputation: 2489

Instead of this

df3 = result[result['Value'] ! <= 10]  

Use

df3 = result[~(result['Value'] <= 10)]  

It will work. OR simply use

df3 = result[result['Value'] > 10]  

Upvotes: 68

piRSquared
piRSquared

Reputation: 294258

python doesn't use ! to negate. It uses not. See this answer
In this particular example != is a two character string that means not equal. It is not the negation of ==.

option 1
This should work unless you have NaN

result[result['Value'] > 10]

option 2
use the unary operator ~ to negate a boolean series

result[~(result['Value'] <= 10)]

Upvotes: 14

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