Is there an equivalent of the python built in function `all` in pandas?

Question

I'm quyering a pandas dataframe df like this.

df = df[
    (df.value1 >= threshold1) &
    (df.value2 >= threshold2) &
    (df.value3.isin(list3))
    ]

Python has the built in function all , which allows this syntax:

if all([
    value1 > threshold1,
    value2 > threshold2,
    value3 in list3,
    ]):

Instead of this:

if (
    value1 > threshold1 and
    value2 > threshold2 and
    value3 in list3,
    ):

Does Pandas have something similar to all in Python? Thanks.

Also, is this the fastest way of subsetting a Pandas dataframe based on multiple conditions?

Answer 1

@juanpa.arrivillaga already gave you a very good explanation about boolean indexing in Pandas.

I'd like to give you a bit nicer alternative - DataFrame.query() method:

df.query("value1 > @threshold1 and value2 > @threshold2 and value3 in @list3")

Demo:

In [138]: df = pd.DataFrame(np.random.randint(1, 10, (10, 3)),
                            columns=['value1','value2','value3'])

In [139]: df
Out[139]:
   value1  value2  value3
0       7       9       1
1       4       1       3
2       3       8       8
3       2       8       9
4       9       2       7
5       5       8       9
6       4       2       9
7       7       2       5
8       6       3       5
9       9       1       5

In [140]: threshold1 = 2

In [141]: threshold2 = 4

In [142]: list3 = [1,9]

In [143]: df.query("value1 > @threshold1 and value2 > @threshold2 and value3 in @list3")
Out[143]:
   value1  value2  value3
0       7       9       1
5       5       8       9