grouping values in pandas column

Question

I have a pandas dataframe that contain score such as

score
0.1
0.15
0.2
0.3
0.35
0.4
0.5

etc

I want to group these value into the gorups of 0.2 so if score is between 0.1 or 0.2 the value for this row in sore will be 0.2 if score is between 0.2 and 0.4 then the value for score will be 0.4

so for example if max score is 1, I will have 5 buckets of score, 0.2 0.4 0.6 0.8 1

desired output:

score
0.2
0.2
0.2
0.4
0.4
0.4
0.6

last sentence: "max score is 10", should this be 1? – T C Molenaar Sep 26 '22 at 09:45 — T C Molenaar, Sep 26 '22 at 09:45
what is your desired output? – T C Molenaar Sep 26 '22 at 09:46 — T C Molenaar, Sep 26 '22 at 09:46

score 1 · Accepted Answer · answered Sep 26 '22 at 10:01

You can first define a function that does the rounding for you:

import numpy as np
def custom_round(x, base):
    return base * np.ceil(x / base)

Then use .apply() to apply the function to your column:

df.score.apply(lambda x: custom_round(x, base=.2))

Output:

0    0.2
1    0.2
2    0.2
3    0.4
4    0.4
5    0.4
6    0.6
Name: score, dtype: float64

score 1 · Answer 2 · answered Sep 26 '22 at 10:02

Try np.ceil:

import pandas as pd
import numpy as np

data = {'score': {0: 0.1, 1: 0.15, 2: 0.2, 3: 0.3, 4: 0.35, 5: 0.4, 6: 0.5}}
df = pd.DataFrame(data)

base = 0.2
df['score'] = base * np.ceil(df.score/base)

print(df)

   score
0    0.2
1    0.2
2    0.2
3    0.4
4    0.4
5    0.4
6    0.6

grouping values in pandas column

2 Answers2