Find index of last true value in pandas Series or DataFrame

You can use idxmax what is the same as argmax of Andy Hayden answer:

print s[::-1].idxmax()

Comparing:

These timings are going to be very dependent on the size of s as well as the number (and position) of Trues - thanks.

In [2]: %timeit s.index[s][-1]
The slowest run took 6.92 times longer than the fastest. This could mean that an intermediate result is being cached 
10000 loops, best of 3: 35 µs per loop

In [3]: %timeit s[::-1].argmax()
The slowest run took 6.67 times longer than the fastest. This could mean that an intermediate result is being cached 
10000 loops, best of 3: 126 µs per loop

In [4]: %timeit s[::-1].idxmax()
The slowest run took 6.55 times longer than the fastest. This could mean that an intermediate result is being cached 
10000 loops, best of 3: 127 µs per loop

In [5]: %timeit s[s==True].last_valid_index()
The slowest run took 8.10 times longer than the fastest. This could mean that an intermediate result is being cached 
1000 loops, best of 3: 261 µs per loop

In [6]: %timeit (s[s==True].index.tolist()[-1])
The slowest run took 6.11 times longer than the fastest. This could mean that an intermediate result is being cached 
1000 loops, best of 3: 239 µs per loop

In [7]: %timeit (s[s==True].index[-1])
The slowest run took 5.75 times longer than the fastest. This could mean that an intermediate result is being cached 
1000 loops, best of 3: 227 µs per loop

EDIT:

Next solution:

print s[s==True].index[-1]

EDIT1: Solution

(s[s==True].index.tolist()[-1])

was in deleted answer.

Use last_valid_index:

In [9]:
s.tail(10)

Out[9]:
h    False
w     True
h    False
r     True
q    False
b    False
p    False
e    False
q    False
d    False
dtype: bool

In [8]:
s[s==True].last_valid_index()

Out[8]:
'r'

argmax gets the first True. Use argmax on the reversed Series:

In [11]: s[::-1].argmax()
Out[11]: 'e'

Here:

In [12]: s.tail()
Out[12]:
n     True
e     True
k    False
d    False
l    False
dtype: bool