Greater/less than in if statement

Question

Still looking for an answer, help is very much appreciated!

I am working on a dataset containing different types of data about cars I want to add a value to the horsepower_score column, if the value of the horsepower column is greater than x but less than y.

I want to add the value:

1 if horsepower is less than or equal to 50

2 if horsepower is greater than 50 but less than or equal to 100

3 if horsepower is greater than 100 but less than or equal to 200

4 if horsepower is greater than 200 but less than or equal to 250

5 if horsepower is greater than 250 but less than or equal to 300

I have tried several different codes, but I can't make any of them work.

import pandas as pd
data=[[150,0],[275,0],[30,0],[90,0],[220,0]]
df=pd.DataFrame(data,columns=['horsepower','horsepower_score'])

if df['horsepower']<=50:
    df['horsepower_score']=1

if df['horsepower']>50 & <=100:
    df['horsepower_score']=2

if df['horsepower']>100 & <=200:
    df['horsepower_score']=2

if df['horsepower']>200 & <=250:
    df['horsepower_score']=4

if df['horsepower']>250 & <=300:
    df['horsepower_score']=5

So my desired result would look like this:

horsepower	horsepower_score
150	3
275	5
30	1
90	2
220	4

Update: Im still looking for a solution. The only answer that worked partially is the one from @Andreas, but that suggestion keeps on adding the number to the column when the code is run several times, and i simply want to assign the number once.

How do i add a value to a new column when the value in some column is greater than 100 and less than 200? — lindstroem, May 19 '21 at 20:57
@quamrana, i have tried your suggestion, but get the following error: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). — lindstroem, May 19 '21 at 20:59
Can you post a working example including initialization of a sample dataframe? — tdelaney, May 19 '21 at 21:02
There is `between`: `df['horsepower'].between(100, 200, inclusive=False)`, but that wont solve the warning you're going to get for the truth value of a Series being ambiguous... — ALollz, May 19 '21 at 21:07
@ALollz My goal is to create a second column called "horsepower_score" that ranges from 1-5. So if a car has number of horsepower less than 200 and larger than 100, i want to add "3" to the column "horsepower_score". Can i adjust your suggested code so that this will happen? — lindstroem, May 19 '21 at 21:16
There are multiple ways to solve this problem but burden is on OP to post a working example so that we can demonstrate that the answer works. — tdelaney, May 19 '21 at 21:17
Something like `df["horsepower_score"] = df["horsepower"] // 100 + 1` could do the trick, depending on exactly where you want the score demarcations to be. — tdelaney, May 19 '21 at 21:21
@tdelaney your above suggestion solves the issues to a limited degree, but thanks. I have added what i assume is meant by a working example, maybe that will make it easier to answer :D — lindstroem, May 19 '21 at 21:35
Welcome to Stack Overflow! Please include your __expected__ output for the __provided__ data. See [MRE - Minimal, Reproducible, Example](https://stackoverflow.com/help/minimal-reproducible-example), and [How to make good reproducible pandas examples](https://stackoverflow.com/q/20109391/15497888). — Henry Ecker, May 19 '21 at 22:06
Yes i actually want those too, just thought it was easier to explain and understand if 3 and 5 was given as examples. — lindstroem, May 19 '21 at 22:19
Actually, this problem is probably easier solved all together. — Henry Ecker, May 19 '21 at 22:21
Okay Last question you have score 1 strictly less than 50 and score 2 strictly greater than 50 which means 50 belongs to no category is this your intention ? This is also true for 100, 200, and 250 — Henry Ecker, May 19 '21 at 22:43

score 2 · Answer 1 · answered May 19 '21 at 20:58

2

In python you can chain these conditions, which makes pretty nice to read.

if 100 < df['horsepower'] < 200:
    df['horsepower_score']=3

Or you use the more traditional way:

if df['horsepower'] > 100 & df['horsepower'] < 200:
    df['horsepower_score']=3

answered May 19 '21 at 20:58

schilli

1,700
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2

This is a dataframe so `df['hosepower_score'] = 3` assigns 3 to the entire column. I don't think `100 < df['horsepower'] < 200` will even work with a dataframe. – tdelaney May 19 '21 at 21:15
Gives the error message: "ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()." – lindstroem May 26 '21 at 15:16

score 1 · Answer 2 · answered May 19 '21 at 20:57

1

You have to break it into two separate comparisons. Those comparisons form a boolean index you can use to slice df.

ix = df['horsepower']>100 & df['horsepower']<200
df.loc[ix, 'horsepower_score'] = 3

answered May 19 '21 at 20:57

James

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4
47
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score 1 · Answer 3 · answered May 19 '21 at 21:04

You wrote

I want to add a value to horsepower_score

Therefore I assume there are already values in horsepower_score, and you want to add 3 to the existing number. If that is the case, you can use this:

df['horsepower_score'] += (df['horsepower'].ge(100) & df['horsepower'].le(200)) * 3

Greater/less than in if statement

3 Answers3