How to apply a function in pandas time series

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Python

dataset

hi
Stdev = Sample Standard Deviation
Ln = Natural Logarithm
Sqrt = Square Root

volatility Index = Stdev(Ln(P1/P0), Ln(P2/P1), ..., Ln(P30/P29)) *Sqrt(365)

i want to write this code on a data frame like this

	Date	Twap
0	2013-10-01	123.8187
1	2013-10-02	124.62557999999999
2	2013-10-03	110.758455
3	2013-10-04	113.2481625
4	2013-10-05	119.98882750000001
5	2013-10-06	121.10016250000001
6	2013-10-07	121.218495
7	2013-10-08	122.454705
8	2013-10-09	123.61454
9	2013-10-10	125.46166249999999
10	2013-10-11	125.4478275
11	2013-10-12	125.09333
12	2013-10-13	126.1209575
13	2013-10-14	130.7805775
14	2013-10-15	133.6325575
15	2013-10-16	138.130205
16	2013-10-17	140.57558
17	2013-10-18	140.68141250000002
18	2013-10-19	147.66287
19	2013-10-20	158.1210375
20	2013-10-21	162.220495
21	2013-10-22	170.8828675
22	2013-10-23	182.96707750000002
23	2013-10-24	194.289745
24	2013-10-25	185.277995
25	2013-10-26	175.5104125
26	2013-10-27	176.9478725
27	2013-10-28	182.0395825
28	2013-10-29	189.65937
29	2013-10-30	195.04937
30	2013-10-31	196.262995
31	2013-11-01	196.918245
32	2013-11-02	197.89224750000002
33	2013-11-03	199.8566625
34	2013-11-04	205.5794575
35	2013-11-05	217.89729
36	2013-11-06	235.860705
37	2013-11-07	254.05082749999997
38	2013-11-08	277.9382
39	2013-11-09	315.68937
40	2013-11-10	312.36775
41	2013-11-11	293.71074500000003
42	2013-11-12	321.64056
43	2013-11-13	347.718685
44	2013-11-14	380.0384975
45	2013-11-15	402.89374999999995
46	2013-11-16	410.94737250000003
47	2013-11-17	427.670185
48	2013-11-18	474.050745
49	2013-11-19	619.415935
50	2013-11-20	584.2309325
51	2013-11-21	528.8384325
52	2013-11-22	633.0808724999999
53	2013-11-23	720.7646225
54	2013-11-24	758.8703725
55	2013-11-25	752.5100575
56	2013-11-26	772.9409975
57	2013-11-27	843.5803125
58	2013-11-28	915.7935625
59	2013-11-29	1000.1489
60	2013-11-30	1102.253675
61	2013-12-01	1127.42
62	2013-12-02	1000.675655
63	2013-12-03	1007.0671624999999
64	2013-12-04	1053.5350274999998
65	2013-12-05	1107.1964725
66	2013-12-06	1039.6750299999999
67	2013-12-07	864.8679325
68	2013-12-08	708.4128499999999
69	2013-12-09	765.0535
70	2013-12-10	879.3037400000001
71	2013-12-11	947.4553675
72	2013-12-12	910.3923375
73	2013-12-13	885.056975
74	2013-12-14	898.4179125
75	2013-12-15	871.095485
76	2013-12-16	855.9061925
77	2013-12-17	758.7809275
78	2013-12-18	678.12831
79	2013-12-19	571.078495
80	2013-12-20	625.6539124999999
81	2013-12-21	668.4366125
82	2013-12-22	619.480035
83	2013-12-23	627.3999
84	2013-12-24	659.2937299999999
85	2013-12-25	663.205455
86	2013-12-26	683.3997850000001
87	2013-12-27	734.7544125
88	2013-12-28	747.228785
89	2013-12-29	727.71843
90	2013-12-30	736.0334125
91	2013-12-31	751.1306775
92	2014-01-01	754.6834125
93	2014-01-02	765.5737025000001
94	2014-01-03	791.9052525000001
95	2014-01-04	813.8303324999999
96	2014-01-05	841.7824925
97	2014-01-06	918.7571275
98	2014-01-07	967.7621549999999
99	2014-01-08	894.2876549999999
100	2014-01-09	856.2382775
101	2014-01-10	850.7965899999999
102	2014-01-11	869.8508075
103	2014-01-12	906.5073674999999
104	2014-01-13	892.106
105	2014-01-14	857.8113925000001
106	2014-01-15	856.7985974999999
107	2014-01-16	867.3681675
108	2014-01-17	859.29376
109	2014-01-18	835.4024975
110	2014-01-19	839.4864524999999
111	2014-01-20	860.06041
112	2014-01-21	873.8656225
113	2014-01-22	871.3352
114	2014-01-23	866.7214099999999
115	2014-01-24	851.0422475
116	2014-01-25	830.4061375
117	2014-01-26	850.66715
118	2014-01-27	874.0466025000001

What I have tried:

<pre>p = data[['Date','Twap']] 

a=np.array([])

def volatility(x):
    for i in range(30-1):
        np.append(a,np.log(x['Twap'][i+1]/x['Twap'][i]))

p.rolling(window = 30).apply(volatility)

but I get an error what should I do to be able to continue my calculations sorry if my question is naive I'm not a programmer