Check if a pandas Series has at least one item greater than a value

Question

The following code will print True because the Series contains at least one element that is greater than 1. However, it seems a bit un-Pythonic. Is there a more Pythonic way to return True if a Series contains a number that is greater than a particular value?

import pandas as pd

s = pd.Series([0.5, 2])
print True in (s > 1)          # True

Not only is the above answer un-Pythonic, it will sometimes return an incorrect result for some reason. For example:

s = pd.Series([0.5])
print True in (s < 1)          # False

Hero

Answer 1

You could use any method to check if that condition is True at least for the one value:

In [36]: (s > 1).any()
Out[36]: True

Inculcate

How do you extend that operation to a set of columns so that it returns if there is at least one value greater than zero among all values? – Judijudicable

@FedericoGentile do you mean something like any(axis=1).any()? First, it'll be checked across all rows in your subset and will produce the Pandas Series. Second, you'll check series for any True values. If not you could provide an example in the comment or maybe better to ask a new question with all details. – Inculcate

I meant if I have a dataframe with 3 columns (A, B, C) and I want to check if there is at least a value grater than 0 in column A and B... one possible solution is to do this: (df.A > 1).any() and (df.B > 1).any(). Is there a nicer and elegant way to do it? – Judijudicable

@FedericoGentile you could use something like (df[['A', 'B', 'C']] > 1).any(axis=1) – Inculcate

Answer 2

in operator a.k.a __contains__() method checks if a specific value exists as an index in a Series.

s = pd.Series([0.5], index=['a'])

'a' in (s > 1)          # True
'b' in s                # False

As a side note, in operator used on dataframes checks if a value exists as a column label.

df = pd.DataFrame([[1]], columns=['a'])
'a' in df               # True
'b' in df               # False

In other words, the fact that the in operator returns True or False has nothing to do with whether (s > 1) has any True values in it or not. In order to make the membership test work, the values must be accessed.

True in (s < 1).values  # True

Reducing the values into a single boolean value (as suggested by @Anton Protopopov) is the canonical way to this task. Python's built-in any() function may be called as well.

any(s > 1)              # False
s.gt(1).any()           # False

(s < 1).any()           # True
s.lt(1).any()           # True

Montague