Quick way to check if the pandas series contains a negative value

Question

What is the quickest way to check if the given pandas series contains a negative value.

For example, for the series s below the answer is True.

s = pd.Series([1,5,3,-1,7])

0    1
1    5
2    3
3   -1
4    7
dtype: int64

Macrography

(s<0).sum()>0 ? – Brigittebriley

Even shorter - (s<0).any() – Brigittebriley

Even shorter - any(s<0) – Rajasthan

Answer 1

Use any

>>> s = pd.Series([1,5,3,-1,7])
>>> any(s<0)
True

Willumsen

Of all the answers, this is the fastest. – Rajasthan

@MohitMotwani that depends on the size of the series and the index of the item less than zero. – Japhetic

@VanPeer In that case, is there a universal fastest answer to this? – Rajasthan

Plus where would this method be slower compared to the other methods mentioned? – Rajasthan

nice one. For those who are curious: have checked the runtime; %timeit s.lt(0).any() results in 72.8 µs ± 2.24 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each); and %timeit any(s<0) results in 50.4 µs ± 1.65 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each). (This may be faster on more modern systems, but only as an indication) – Shulman

Answer 2

You can use Series.lt :

s = pd.Series([1,5,3,-1,7])
s.lt(0).any()

Output:

True

Shylashylock

lt stands for 'less than' – Drye

Answer 3

Use any function:

>>>s = pd.Series([1,5,3,-1,7])
>>>any(x < 0 for x in s)
True
>>>s = pd.Series([1,5,3,0,7])
>>>any(x < 0 for x in s)
False

Alula