Python if statement getting: 'The truth value of a Series is ambiguous'

Condition worked independently, but adding as part of an if, is getting truth ambiguous:

import pandas as pd
import numpy as np
df1 = pd.DataFrame(np.random.randn(10,5), columns=list('ABCDE'))
df1
# df1.loc[(df1.D > 1.25) | (df1.D < -0.25)] # work
# df1.loc[:,'D'] > 0.1 # work
if df1.loc[:,'D'] > 0.1:
    print(df1['A'] * df1['B'])

reference:
https://stackoverflow.com/questions/36921951/truth-value-of-a-series-is-ambiguous-use-a-empty-a-bool-a-item-a-any-o

df.loc[:,'D'] > 0.1 gives you a vector of true and false values:

Out[1]: 
0    False
1    False
2    False
3    False
4     True
5     True
6    False
7    False
8    False
9    False
Name: D, dtype: bool

It's not sure how to convert a vector of true and false into a single value. You could assume all: if (df1.loc[:,'D'] > 0.1).all():, any: if (df1.loc[:,'D'] > 0.1).any():, or iterate through:

for item in (df1.loc[:,'D'] > 0.1):
    if item:
        print('something')

Without knowing more about what you're trying to do python and I are just guessing.

So looking at your edit, I think you're trying to multiply A and B and take the values when D > 0.1, which is easy:

(df1['A'] * df1['B'])[(df1.loc[:,'D'] > 0.1)]

1   -0.590544
3   -0.371079
8   -0.704530
dtype: float64