replacing a range of values with one value

Question

I have a list that I'm adding to a pandas data frame it contains a range of decimal values. I want to divide it into 3 ranges each range represents one value

sents=[]
for sent in sentis:
if sent > 0:
    if sent < 0.40:
        sents.append('negative')
    if (sent >= 0.40 and sent <= 0.60):
        sents.append('neutral')
    if sent > 0.60
        sents.append('positive')

my question is if there is a more efficient way in pandas to do this as i'm trying to implement this on a bigger list and

Thanks in advance.

piRSquared · Accepted Answer · 2017-05-09 00:05:27Z

2

You can use pd.cut to produce the results that are of type categorical and have the appropriate labels.

In order to fix the inclusion of .4 and .6 for the neutral category, I add and subtract the smallest float epsilon

sentis = np.linspace(0, 1, 11)
eps = np.finfo(float).eps

pd.DataFrame(dict(
        Value=sentis,
        Sentiment=pd.cut(
            sentis, [-np.inf, .4 - eps, .6 + eps, np.inf],
            labels=['negative', 'neutral', 'positive']
        ),
    ))

   Sentiment  Value
0   negative    0.0
1   negative    0.1
2   negative    0.2
3   negative    0.3
4    neutral    0.4
5    neutral    0.5
6    neutral    0.6
7   positive    0.7
8   positive    0.8
9   positive    0.9
10  positive    1.0

answered May 9, 2017 at 0:05

piRSquared

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1 Comment

Muhammed Eltabakh Over a year ago

Thanks a lot exactly what i'm looking for

Scott Hunter · Accepted Answer · 2017-05-08 23:59:54Z

0

List comprehension:

['negative' if x < 0.4 else 'positive' if x > 0.6 else 'neutral' for x in sentis]

answered May 8, 2017 at 23:59

Scott Hunter

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