The Virtual DataFrame¶

The Virtual DataFrame is the main object and star of the library and acts as the perfect transition between small and Big Data. The principle is quite simple: As Vertica is a powerful columnar massive parallel processing (MPP) database with many built-in functions, we want it to do as much of the computation work as possible.

Indeed, columnar orientation allows for high compression, and its structure inherently avoids unncessary parsing when retrieving data. MPP allows to parallelize our computations accross the different nodes.

The best way to take advantage of your data is by simply keeping it in your Vertica database, rather than within the limitations of working memory. VerticaPy pushes all computation to your Vertica database before aggregating the final result, so you can get the best of both worlds: Vertica's power and Python's flexibility.

With Python, it's easy to add abstractions, and the vDataFrame acts as the primary abstraction layer. Simple but powerful, it'll help any user through the data science life cycle.

Creating the vDataFrame¶

There are two main ways to create a vDataFrame.

The first is to create one directly using an existing relation.

In [1]:

from verticapy.datasets import load_titanic
load_titanic() # Loading the titanic dataset in Vertica

import verticapy as vp
vp.vDataFrame("public.titanic")

Out[1]:

	123 pclass Int	123 survived Int	Abc Varchar(164)	Abc sex Varchar(20)	123 age Numeric(6,3)	123 sibsp Int	123 parch Int	Abc ticket Varchar(36)	123 fare Numeric(10,5)	Abc cabin Varchar(30)	Abc embarked Varchar(20)	Abc boat Varchar(100)	123 body Int	Abc home.dest Varchar(100)
1	1	0		female	2.0	1	2	113781	151.55	C22 C26	S	[null]	[null]	Montreal, PQ / Chesterville, ON
2	1	0		male	30.0	1	2	113781	151.55	C22 C26	S	[null]	135	Montreal, PQ / Chesterville, ON
3	1	0		female	25.0	1	2	113781	151.55	C22 C26	S	[null]	[null]	Montreal, PQ / Chesterville, ON
4	1	0		male	39.0	0	0	112050	0.0	A36	S	[null]	[null]	Belfast, NI
5	1	0		male	71.0	0	0	PC 17609	49.5042	[null]	C	[null]	22	Montevideo, Uruguay
6	1	0		male	47.0	1	0	PC 17757	227.525	C62 C64	C	[null]	124	New York, NY
7	1	0		male	[null]	0	0	PC 17318	25.925	[null]	S	[null]	[null]	New York, NY
8	1	0		male	24.0	0	1	PC 17558	247.5208	B58 B60	C	[null]	[null]	Montreal, PQ
9	1	0		male	36.0	0	0	13050	75.2417	C6	C	A	[null]	Winnipeg, MN
10	1	0		male	25.0	0	0	13905	26.0	[null]	C	[null]	148	San Francisco, CA
11	1	0		male	45.0	0	0	113784	35.5	T	S	[null]	[null]	Trenton, NJ
12	1	0		male	42.0	0	0	110489	26.55	D22	S	[null]	[null]	London / Winnipeg, MB
13	1	0		male	41.0	0	0	113054	30.5	A21	S	[null]	[null]	Pomeroy, WA
14	1	0		male	48.0	0	0	PC 17591	50.4958	B10	C	[null]	208	Omaha, NE
15	1	0		male	[null]	0	0	112379	39.6	[null]	C	[null]	[null]	Philadelphia, PA
16	1	0		male	45.0	0	0	113050	26.55	B38	S	[null]	[null]	Washington, DC
17	1	0		male	[null]	0	0	113798	31.0	[null]	S	[null]	[null]	[null]
18	1	0		male	33.0	0	0	695	5.0	B51 B53 B55	S	[null]	[null]	New York, NY
19	1	0		male	28.0	0	0	113059	47.1	[null]	S	[null]	[null]	Montevideo, Uruguay
20	1	0		male	17.0	0	0	113059	47.1	[null]	S	[null]	[null]	Montevideo, Uruguay
21	1	0		male	49.0	0	0	19924	26.0	[null]	S	[null]	[null]	Ascot, Berkshire / Rochester, NY
22	1	0		male	36.0	1	0	19877	78.85	C46	S	[null]	172	Little Onn Hall, Staffs
23	1	0		male	46.0	1	0	W.E.P. 5734	61.175	E31	S	[null]	[null]	Amenia, ND
24	1	0		male	[null]	0	0	112051	0.0	[null]	S	[null]	[null]	Liverpool, England / Belfast
25	1	0		male	27.0	1	0	13508	136.7792	C89	C	[null]	[null]	Los Angeles, CA
26	1	0		male	[null]	0	0	110465	52.0	A14	S	[null]	[null]	Stoughton, MA
27	1	0		male	47.0	0	0	5727	25.5875	E58	S	[null]	[null]	Victoria, BC
28	1	0		male	37.0	1	1	PC 17756	83.1583	E52	C	[null]	[null]	Lakewood, NJ
29	1	0		male	[null]	0	0	113791	26.55	[null]	S	[null]	[null]	Roachdale, IN
30	1	0		male	70.0	1	1	WE/P 5735	71.0	B22	S	[null]	269	Milwaukee, WI
31	1	0		male	39.0	1	0	PC 17599	71.2833	C85	C	[null]	[null]	New York, NY
32	1	0		male	31.0	1	0	F.C. 12750	52.0	B71	S	[null]	[null]	Montreal, PQ
33	1	0		male	50.0	1	0	PC 17761	106.425	C86	C	[null]	62	Deephaven, MN / Cedar Rapids, IA
34	1	0		male	39.0	0	0	PC 17580	29.7	A18	C	[null]	133	Philadelphia, PA
35	1	0		female	36.0	0	0	PC 17531	31.6792	A29	C	[null]	[null]	New York, NY
36	1	0		male	[null]	0	0	PC 17483	221.7792	C95	S	[null]	[null]	[null]
37	1	0		male	30.0	0	0	113051	27.75	C111	C	[null]	[null]	New York, NY
38	1	0		male	19.0	3	2	19950	263.0	C23 C25 C27	S	[null]	[null]	Winnipeg, MB
39	1	0		male	64.0	1	4	19950	263.0	C23 C25 C27	S	[null]	[null]	Winnipeg, MB
40	1	0		male	[null]	0	0	113778	26.55	D34	S	[null]	[null]	Westcliff-on-Sea, Essex
41	1	0		male	[null]	0	0	112058	0.0	B102	S	[null]	[null]	[null]
42	1	0		male	37.0	1	0	113803	53.1	C123	S	[null]	[null]	Scituate, MA
43	1	0		male	47.0	0	0	111320	38.5	E63	S	[null]	275	St Anne's-on-Sea, Lancashire
44	1	0		male	24.0	0	0	PC 17593	79.2	B86	C	[null]	[null]	[null]
45	1	0		male	71.0	0	0	PC 17754	34.6542	A5	C	[null]	[null]	New York, NY
46	1	0		male	38.0	0	1	PC 17582	153.4625	C91	S	[null]	147	Winnipeg, MB
47	1	0		male	46.0	0	0	PC 17593	79.2	B82 B84	C	[null]	[null]	New York, NY
48	1	0		male	[null]	0	0	113796	42.4	[null]	S	[null]	[null]	[null]
49	1	0		male	45.0	1	0	36973	83.475	C83	S	[null]	[null]	New York, NY
50	1	0		male	40.0	0	0	112059	0.0	B94	S	[null]	110	[null]
51	1	0		male	55.0	1	1	12749	93.5	B69	S	[null]	307	Montreal, PQ
52	1	0		male	42.0	0	0	113038	42.5	B11	S	[null]	[null]	London / Middlesex
53	1	0		male	[null]	0	0	17463	51.8625	E46	S	[null]	[null]	Brighton, MA
54	1	0		male	55.0	0	0	680	50.0	C39	S	[null]	[null]	London / Birmingham
55	1	0		male	42.0	1	0	113789	52.0	[null]	S	[null]	38	New York, NY
56	1	0		male	[null]	0	0	PC 17600	30.6958	[null]	C	14	[null]	New York, NY
57	1	0		female	50.0	0	0	PC 17595	28.7125	C49	C	[null]	[null]	Paris, France New York, NY
58	1	0		male	46.0	0	0	694	26.0	[null]	S	[null]	80	Bennington, VT
59	1	0		male	50.0	0	0	113044	26.0	E60	S	[null]	[null]	London
60	1	0		male	32.5	0	0	113503	211.5	C132	C	[null]	45	[null]
61	1	0		male	58.0	0	0	11771	29.7	B37	C	[null]	258	Buffalo, NY
62	1	0		male	41.0	1	0	17464	51.8625	D21	S	[null]	[null]	Southington / Noank, CT
63	1	0		male	[null]	0	0	113028	26.55	C124	S	[null]	[null]	Portland, OR
64	1	0		male	[null]	0	0	PC 17612	27.7208	[null]	C	[null]	[null]	Chicago, IL
65	1	0		male	29.0	0	0	113501	30.0	D6	S	[null]	126	Springfield, MA
66	1	0		male	30.0	0	0	113801	45.5	[null]	S	[null]	[null]	London / New York, NY
67	1	0		male	30.0	0	0	110469	26.0	C106	S	[null]	[null]	Brockton, MA
68	1	0		male	19.0	1	0	113773	53.1	D30	S	[null]	[null]	New York, NY
69	1	0		male	46.0	0	0	13050	75.2417	C6	C	[null]	292	Vancouver, BC
70	1	0		male	54.0	0	0	17463	51.8625	E46	S	[null]	175	Dorchester, MA
71	1	0		male	28.0	1	0	PC 17604	82.1708	[null]	C	[null]	[null]	New York, NY
72	1	0		male	65.0	0	0	13509	26.55	E38	S	[null]	249	East Bridgewater, MA
73	1	0		male	44.0	2	0	19928	90.0	C78	Q	[null]	230	Fond du Lac, WI
74	1	0		male	55.0	0	0	113787	30.5	C30	S	[null]	[null]	Montreal, PQ
75	1	0		male	47.0	0	0	113796	42.4	[null]	S	[null]	[null]	Washington, DC
76	1	0		male	37.0	0	1	PC 17596	29.7	C118	C	[null]	[null]	Brooklyn, NY
77	1	0		male	58.0	0	2	35273	113.275	D48	C	[null]	122	Lexington, MA
78	1	0		male	64.0	0	0	693	26.0	[null]	S	[null]	263	Isle of Wight, England
79	1	0		male	65.0	0	1	113509	61.9792	B30	C	[null]	234	Providence, RI
80	1	0		male	28.5	0	0	PC 17562	27.7208	D43	C	[null]	189	?Havana, Cuba
81	1	0		male	[null]	0	0	112052	0.0	[null]	S	[null]	[null]	Belfast
82	1	0		male	45.5	0	0	113043	28.5	C124	S	[null]	166	Surbiton Hill, Surrey
83	1	0		male	23.0	0	0	12749	93.5	B24	S	[null]	[null]	Montreal, PQ
84	1	0		male	29.0	1	0	113776	66.6	C2	S	[null]	[null]	Isleworth, England
85	1	0		male	18.0	1	0	PC 17758	108.9	C65	C	[null]	[null]	Madrid, Spain
86	1	0		male	47.0	0	0	110465	52.0	C110	S	[null]	207	Worcester, MA
87	1	0		male	38.0	0	0	19972	0.0	[null]	S	[null]	[null]	Rotterdam, Netherlands
88	1	0		male	22.0	0	0	PC 17760	135.6333	[null]	C	[null]	232	[null]
89	1	0		male	[null]	0	0	PC 17757	227.525	[null]	C	[null]	[null]	[null]
90	1	0		male	31.0	0	0	PC 17590	50.4958	A24	S	[null]	[null]	Trenton, NJ
91	1	0		male	[null]	0	0	113767	50.0	A32	S	[null]	[null]	Seattle, WA
92	1	0		male	36.0	0	0	13049	40.125	A10	C	[null]	[null]	Winnipeg, MB
93	1	0		male	55.0	1	0	PC 17603	59.4	[null]	C	[null]	[null]	New York, NY
94	1	0		male	33.0	0	0	113790	26.55	[null]	S	[null]	109	London
95	1	0		male	61.0	1	3	PC 17608	262.375	B57 B59 B63 B66	C	[null]	[null]	Haverford, PA / Cooperstown, NY
96	1	0		male	50.0	1	0	13507	55.9	E44	S	[null]	[null]	Duluth, MN
97	1	0		male	56.0	0	0	113792	26.55	[null]	S	[null]	[null]	New York, NY
98	1	0		male	56.0	0	0	17764	30.6958	A7	C	[null]	[null]	St James, Long Island, NY
99	1	0		male	24.0	1	0	13695	60.0	C31	S	[null]	[null]	Huntington, WV
100	1	0		male	[null]	0	0	113056	26.0	A19	S	[null]	[null]	Streatham, Surrey

Rows: 1-100 | Columns: 14

We can also create one using a customized relation.

In [2]:

vp.vDataFrame(sql = "SELECT pclass, AVG(survived) AS survived FROM titanic GROUP BY 1")

Out[2]:

	123 pclass Integer	123 survived Float
1	1	0.612179487179487
2	2	0.416988416988417
3	3	0.227752639517345

Rows: 1-3 | Columns: 2

In-memory vs. In-database Loading and Processing¶

First, let's load the expedia dataset in Vertica.

In [4]:

vp.read_csv("data/expedia.csv", schema = "public", parse_nrows = 2000)

Out[4]:

	📅 date_time Timestamp	123 site_name Int	123 posa_continent Int	123 user_location_country Int	123 user_location_region Int	123 user_location_city Int	123 orig_destination_distance Numeric(11,5)	123 user_id Int	123 is_mobile Int	123 is_package Int	123 channel Int	📅 srch_ci Date	📅 srch_co Date	123 srch_adults_cnt Int	123 srch_children_cnt Int	123 srch_rm_cnt Int	123 srch_destination_id Int	123 srch_destination_type_id Int	123 is_booking Int	123 cnt Int	123 hotel_continent Int	123 hotel_country Int	123 hotel_market Int	123 hotel_cluster Int
1	2013-01-07 00:00:02	24	2	3	50	5703	[null]	461899	0	0	9	2013-03-14	2013-03-15	2	1	1	669	3	0	1	2	50	212	41
2	2013-01-07 00:00:06	2	3	66	174	21177	5713.6206	13796	0	0	9	2013-01-19	2013-01-26	1	0	1	8821	1	0	3	6	17	30	58
3	2013-01-07 00:00:06	11	3	205	155	14703	795.7298	1128575	0	0	9	2013-01-19	2013-01-22	1	0	1	25064	6	0	1	2	50	1230	91
4	2013-01-07 00:00:09	37	1	69	761	41949	[null]	1080476	0	1	9	2013-05-29	2013-06-05	2	0	1	7635	3	0	1	2	50	675	10
5	2013-01-07 00:00:17	37	1	69	761	41949	[null]	1018895	0	0	0	2013-09-08	2013-09-10	2	0	1	27215	6	0	2	2	50	645	59
6	2013-01-07 00:00:17	37	1	69	761	41949	[null]	1080476	0	1	9	2013-05-29	2013-06-05	2	0	1	7635	3	0	1	2	50	675	10
7	2013-01-07 00:00:18	2	3	66	462	18767	2696.5003	783725	1	0	9	2013-07-29	2013-08-04	3	3	1	8855	1	0	2	2	50	213	48
8	2013-01-07 00:00:23	37	1	69	761	41949	[null]	1080476	0	1	9	2013-05-29	2013-06-05	2	0	1	7635	3	0	1	2	50	675	10
9	2013-01-07 00:00:28	2	3	66	294	7976	511.012	1197968	0	0	9	2013-01-16	2013-01-18	1	0	1	5811	3	0	2	2	50	350	51
10	2013-01-07 00:00:28	2	3	66	356	4779	4948.1861	593375	0	0	9	2013-05-09	2013-05-10	4	0	2	2763	3	0	2	6	70	1901	2
11	2013-01-07 00:00:29	24	2	3	49	19105	[null]	1174819	0	0	9	2013-04-25	2013-04-28	2	0	1	14908	1	0	1	3	88	1032	75
12	2013-01-07 00:00:33	24	2	3	50	53819	[null]	233534	0	0	1	2013-01-08	2013-01-09	1	1	1	26729	6	0	1	6	105	12	48
13	2013-01-07 00:00:39	2	3	119	0	27731	[null]	519086	0	0	9	2013-01-09	2013-01-11	1	0	1	1510	3	0	3	3	99	1043	82
14	2013-01-07 00:00:42	2	3	163	12	13476	[null]	176709	0	0	9	2013-01-19	2013-01-20	2	0	1	23507	6	0	2	6	70	19	59
15	2013-01-07 00:00:48	24	2	3	49	19105	[null]	1174819	0	0	9	2013-04-25	2013-04-28	2	0	1	14908	1	0	3	3	88	1032	96
16	2013-01-07 00:00:50	2	3	66	442	19744	5315.4141	1173504	0	0	9	2013-01-20	2013-01-26	1	1	1	8739	1	1	1	6	144	4	2
17	2013-01-07 00:00:51	24	2	3	50	53819	[null]	233534	0	0	1	2013-01-08	2013-01-09	1	1	1	26729	6	0	2	6	105	12	61
18	2013-01-07 00:00:55	2	3	66	459	43805	1768.161	836947	0	1	9	2013-04-13	2013-04-18	3	2	1	12257	6	0	2	4	51	1509	5
19	2013-01-07 00:00:59	2	3	23	48	4924	[null]	1046558	0	0	9	2013-02-15	2013-02-17	1	0	1	8244	1	0	4	2	50	643	68
20	2013-01-07 00:00:59	2	3	66	174	16634	382.6203	886436	0	0	1	2013-02-15	2013-02-20	2	0	1	8250	1	0	1	2	50	628	45
21	2013-01-07 00:01:10	24	2	3	50	5703	[null]	207769	0	0	1	2013-04-29	2013-05-01	2	0	1	18569	1	0	2	3	182	83	26
22	2013-01-07 00:01:18	2	3	215	646	51733	149.1411	901573	1	0	9	2013-01-17	2013-01-20	2	0	1	22119	6	0	2	4	8	128	58
23	2013-01-07 00:01:34	2	3	66	356	4779	4948.1861	593375	0	0	9	2013-05-09	2013-05-10	2	0	1	2763	3	0	3	6	70	1901	2
24	2013-01-07 00:01:36	2	3	66	174	6735	2404.0244	1103572	0	0	3	2013-02-11	2013-02-13	2	1	1	25169	6	0	2	2	50	674	4
25	2013-01-07 00:01:45	2	3	66	294	7976	509.4848	1197968	0	0	9	2013-01-16	2013-01-18	1	0	1	5811	3	0	4	2	50	350	76
26	2013-01-07 00:01:53	24	2	3	49	19105	[null]	1174819	0	0	9	2013-04-25	2013-04-28	2	0	1	14908	1	0	3	3	88	1032	5
27	2013-01-07 00:02:02	2	3	66	462	14703	2605.0971	614322	0	0	1	2013-01-08	2013-01-15	2	0	1	13094	3	0	1	2	50	212	41
28	2013-01-07 00:02:02	34	3	205	155	41977	155.835	725753	0	0	5	2013-01-11	2013-01-12	2	0	1	8288	1	1	1	2	198	399	10
29	2013-01-07 00:02:20	2	3	215	646	51733	149.2343	901573	1	0	9	2013-01-17	2013-01-20	2	0	1	22119	6	0	1	4	8	128	36
30	2013-01-07 00:02:21	34	3	205	135	13892	118.0871	799663	0	0	5	2013-01-08	2013-01-10	3	1	1	25946	6	1	1	2	198	370	73
31	2013-01-07 00:02:24	11	3	205	155	14703	796.3281	1128575	0	0	9	2013-01-19	2013-01-22	1	0	1	25064	6	0	1	2	50	1230	4
32	2013-01-07 00:02:28	13	1	46	347	1810	5555.7996	970396	0	0	9	2013-10-09	2013-10-16	2	0	1	8279	1	0	2	2	50	1230	70
33	2013-01-07 00:02:33	11	3	205	155	12291	54.3112	756870	0	0	0	2013-01-08	2013-01-09	2	1	1	26385	6	0	1	2	198	1131	7
34	2013-01-07 00:02:36	2	3	66	348	47997	1692.3911	856762	0	1	2	2013-03-24	2013-04-01	6	0	3	11634	1	0	1	4	35	1616	40
35	2013-01-07 00:02:43	2	3	66	462	14703	2605.4093	614322	0	0	1	2013-01-08	2013-01-15	2	0	1	13094	3	0	1	2	50	212	40
36	2013-01-07 00:02:43	24	2	66	346	31371	384.0182	1162059	1	0	2	2013-01-11	2013-01-14	3	1	1	14985	1	0	1	2	50	1241	99
37	2013-01-07 00:02:45	2	3	66	356	22202	145.5446	1150496	0	0	3	2013-01-18	2013-01-20	2	0	1	12271	6	0	1	2	50	663	91
38	2013-01-07 00:02:46	24	2	3	50	5703	[null]	5061	0	0	3	2013-01-21	2013-01-22	1	1	1	8746	1	0	1	6	105	29	10
39	2013-01-07 00:02:59	24	2	66	346	31371	386.4055	1162059	1	0	2	2013-01-11	2013-01-14	3	1	1	14985	1	0	1	2	50	1241	91
40	2013-01-07 00:03:09	2	3	66	174	42881	379.3402	80737	0	0	9	2013-03-20	2013-03-23	2	0	1	47429	3	0	1	2	50	1230	18
41	2013-01-07 00:03:19	2	3	163	12	13476	[null]	176709	0	0	9	2013-01-19	2013-01-20	2	0	1	23507	6	0	1	6	70	19	49
42	2013-01-07 00:03:23	24	2	3	50	5703	[null]	486357	0	0	0	[null]	[null]	2	0	1	8043	3	0	1	2	50	676	83
43	2013-01-07 00:03:27	17	1	133	25	1503	[null]	228687	0	1	9	2013-02-18	2013-02-23	2	2	2	8821	1	0	1	6	17	30	82
44	2013-01-07 00:03:33	2	3	215	646	51733	149.2495	901573	1	0	9	2013-01-17	2013-01-20	2	0	1	22119	6	0	1	4	8	128	67
45	2013-01-07 00:03:35	2	3	70	47	14566	[null]	598076	0	0	9	2013-01-12	2013-01-13	6	1	3	8220	1	0	2	3	182	46	46
46	2013-01-07 00:03:37	24	2	66	346	31371	383.6014	1162059	1	0	2	2013-01-11	2013-01-14	3	1	1	14985	1	0	1	2	50	1241	94
47	2013-01-07 00:03:41	2	3	66	174	21177	5713.6394	13796	0	0	9	2013-01-19	2013-01-26	1	0	1	8821	1	0	1	6	17	30	67
48	2013-01-07 00:03:52	11	3	205	155	12291	54.216	756870	0	0	0	2013-01-08	2013-01-09	2	1	1	1811	1	0	1	2	198	1131	89
49	2013-01-07 00:03:59	11	3	205	155	14703	796.3082	1128575	0	0	9	2013-01-19	2013-01-22	1	0	1	25064	6	0	2	2	50	1230	5
50	2013-01-07 00:04:02	2	3	66	356	4779	4948.1861	593375	0	0	9	2013-05-09	2013-05-10	2	0	1	2763	3	1	2	6	70	1901	2
51	2013-01-07 00:04:14	2	3	66	348	48862	1093.7218	368084	0	0	3	2013-03-04	2013-03-08	4	0	1	44045	3	0	2	2	50	701	98
52	2013-01-07 00:04:17	24	2	3	50	5703	[null]	486357	0	0	0	2013-01-24	2013-01-28	1	0	1	8043	3	0	4	2	50	676	83
53	2013-01-07 00:04:24	23	1	1	167	14716	[null]	1002737	0	1	9	2013-01-17	2013-01-22	2	0	1	468	1	0	1	3	48	153	64
54	2013-01-07 00:04:25	13	1	46	347	1810	5557.073	970396	0	0	9	2013-10-09	2013-10-16	2	0	1	8279	1	0	1	2	50	1230	68
55	2013-01-07 00:04:29	2	3	66	174	42881	379.3402	80737	0	0	9	2013-03-20	2013-03-23	4	0	2	47429	3	0	1	2	50	1230	18
56	2013-01-07 00:04:31	2	3	66	348	48862	1093.7218	368084	0	0	3	2013-03-01	2013-03-05	4	0	1	44045	3	0	1	2	50	701	98
57	2013-01-07 00:04:32	11	3	205	155	53078	989.6525	564664	0	1	9	2013-03-17	2013-03-21	4	2	1	8250	1	0	5	2	50	628	45
58	2013-01-07 00:04:33	2	3	3	50	31800	[null]	192004	0	0	9	2013-02-24	2013-02-28	1	1	1	22238	6	0	2	6	77	2	6
59	2013-01-07 00:04:33	2	3	103	45	38784	[null]	753394	1	1	9	2013-02-09	2013-02-17	2	3	1	8268	1	0	1	2	50	682	31
60	2013-01-07 00:04:37	2	3	66	467	16159	1510.8714	103449	0	1	9	2013-03-01	2013-03-05	2	0	1	8791	1	1	1	4	8	110	65
61	2013-01-07 00:04:40	24	2	66	346	31371	390.7326	1162059	1	0	2	2013-01-11	2013-01-14	3	1	1	14985	1	0	1	2	50	1241	40
62	2013-01-07 00:04:42	2	3	66	348	48862	1093.7218	368084	0	0	3	2013-03-02	2013-03-06	4	0	1	44045	3	0	1	2	50	701	98
63	2013-01-07 00:04:44	34	3	205	155	14703	995.1954	332853	1	0	9	2013-03-24	2013-03-28	2	2	1	12206	6	0	3	2	50	628	79
64	2013-01-07 00:04:51	2	3	66	462	18767	2688.2625	783725	1	0	9	2013-07-29	2013-08-04	3	3	1	8855	1	0	1	2	50	213	6
65	2013-01-07 00:04:55	37	1	69	761	41949	[null]	976118	0	1	3	2013-02-15	2013-02-15	2	1	1	1014	1	0	1	3	92	168	92
66	2013-01-07 00:04:58	2	3	66	348	48862	1093.7218	368084	0	0	3	2013-03-04	2013-03-06	4	0	1	44045	3	0	3	2	50	701	98
67	2013-01-07 00:05:04	2	3	3	50	31800	[null]	192004	0	0	9	2013-02-24	2013-02-28	2	1	1	22238	6	0	1	6	77	2	6
68	2013-01-07 00:05:06	37	1	69	761	41949	[null]	1080476	0	1	9	2013-05-29	2013-06-05	2	0	1	7635	3	0	1	2	50	675	83
69	2013-01-07 00:05:13	37	1	69	761	41949	[null]	1080476	0	1	9	2013-05-29	2013-06-05	2	0	1	7635	3	0	1	2	50	675	55
70	2013-01-07 00:05:31	17	1	133	20	46168	[null]	124561	0	0	3	2013-03-09	2013-03-13	4	2	1	8253	1	0	2	6	70	19	48
71	2013-01-07 00:05:32	2	3	198	208	54488	[null]	425340	0	0	9	2013-02-10	2013-02-11	1	1	1	468	1	0	1	3	48	153	64
72	2013-01-07 00:05:34	24	2	3	50	22013	[null]	487265	0	0	0	2013-05-23	2013-05-27	4	1	1	669	3	0	1	2	50	212	96
73	2013-01-07 00:05:39	37	1	69	761	41949	[null]	1018895	0	0	0	2013-09-08	2013-09-10	2	0	1	27215	6	0	3	2	50	645	91
74	2013-01-07 00:05:42	2	3	66	348	48862	1093.7218	368084	0	0	3	2013-03-04	2013-03-07	4	0	1	44045	3	0	5	2	50	701	98