df = pd.DataFrame({'A': ['foo', 'bar', 'baz', 'foo'], 
                   'B': ['qux', 'quux', 'quuz', 'xyz']})
df

df['col2'] = (df['A'] == 'foo') & (df['B'] == 'qux' )

df = df.assign(col3 = lambda x: (df['A'] == 'foo') & (df['B'] == 'qux' ))

def test(df):
    if (  (df['A'] == 'foo') & (df['B'] == 'qux' ) ).any():
        x = True
    else:
        x = False
    return x 

df = df.assign(col4 = lambda x: test(df))
# df['col5'] = df.apply(test, axis=1)
df['col6'] = df.apply(lambda x: test(df), axis=1)

def test(df):
    x =  (df['A'] == 'foo') & (df['B'] == 'qux' ) 
    return x 

def test5(df):
    if  (df['A'] == 'foo') & (df['B'] == 'qux' ):
        x = 'peak'
    elif (df['A'] == 'bar') & (df['B'] == 'quux' ):
        x = 'off'
    else:
        x = 'false'
    return x    

# this works - have to use apply not assign.
df['col10'] = df.apply(lambda x: test5(x), axis=1)

# this fails "truth value of series...." error; assign doesn't work.
df = df.assign(col11 = lambda x: test5(x))

def test6(df):
    if ( (df['A'] == 'foo').any() & (df['B'] == 'qux' ).any() ):
        x = 'peak'
    elif ( (df['A'] == 'bar').any() & (df['B'] == 'quux' ).any() ):
        x = 'off'
    else:
        x = 'false'
    return x 

# this "works" - code doesn't fail, but has the wrong answer

df = df.assign(col12 = lambda x: test6(x))

def cook1(recipe):
    if "salt" in recipe:
        print("Add salt.")
        return False
    else:
        return True


def cook2(recipe):
    if "salt" in recipe:
        print("Add salt.")
        return False
    else:
        return True


recipe = ["salt", "flour", "water"]

print("Bitwise AND:")
if cook1(recipe) & cook2(recipe):
    print("Voila!")

print("\nLogical AND:")
if cook1(recipe) and cook2(recipe):
    print("Voila!")