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vDataFrame[].iv_woe¶
In [ ]:
vDataFrame[].iv_woe(y: str,
nbins: int = 10)
Computes the Information Value (IV) / Weight Of Evidence (WOE) Table. It tells the predictive power of an independent variable in relation to the dependent variable.
Parameters¶
Name | Type | Optional | Description |
---|---|---|---|
y | str | ❌ | Response vcolumn. |
nbins | int | ✓ | Maximum number of bins used for the discretization (must be > 1). |
Returns¶
tablesample : An object containing the result. For more information, see utilities.tablesample.
Example¶
In [18]:
from verticapy.datasets import load_titanic
titanic = load_titanic()
display(titanic)
123 pclassInt | 123 survivedInt | Abc Varchar(164) | Abc sexVarchar(20) | 123 ageNumeric(6,3) | 123 sibspInt | 123 parchInt | Abc ticketVarchar(36) | 123 fareNumeric(10,5) | Abc cabinVarchar(30) | Abc embarkedVarchar(20) | Abc boatVarchar(100) | 123 bodyInt | Abc home.destVarchar(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
In [19]:
titanic["age"].iv_woe(y = "survived",
nbins = 20)
Out[19]:
123 non_eventsInteger | 123 eventsInteger | 123 pt_non_eventsNumeric(36,18) | 123 pt_eventsNumeric(36,18) | 123 woeFloat | 123 ivFloat | |
[null] | 178 | 59 | 0.22704081632653061 | 0.13111111111111112 | 0.238464441757655 | 0.0228758236021714 |
[0.00;4.02] | 18 | 30 | 0.02295918367346939 | 0.06666666666666667 | -0.462952298525451 | 0.0202344797144627 |
[4.02;8.04] | 8 | 11 | 0.01020408163265306 | 0.024444444444444446 | -0.379406247075376 | 0.00540288261141352 |
[8.04;12.06] | 13 | 6 | 0.016581632653061226 | 0.013333333333333332 | 0.0946885530140983 | 0.000307576762341714 |
[12.06;16.08] | 20 | 15 | 0.025510204081632654 | 0.03333333333333333 | -0.116164812300795 | 0.000908772341128667 |
[16.08;20.10] | 72 | 35 | 0.09183673469387756 | 0.07777777777777778 | 0.0721609031718981 | 0.00101450702872056 |
[20.10;24.12] | 91 | 59 | 0.11607142857142858 | 0.13111111111111112 | -0.0529141682301453 | 0.000795812292032741 |
[24.12;28.14] | 85 | 40 | 0.10841836734693877 | 0.08888888888888889 | 0.0862553854772356 | 0.00168452269256846 |
[28.14;32.16] | 71 | 49 | 0.09056122448979592 | 0.10888888888888888 | -0.0800412802185331 | 0.00146696972191903 |
[32.16;36.18] | 54 | 39 | 0.06887755102040816 | 0.08666666666666667 | -0.0997743961126255 | 0.0017748982709831 |
[36.18;40.20] | 39 | 22 | 0.04974489795918367 | 0.04888888888888889 | 0.00753837729519824 | 6.45291933999395e-06 |
[40.20;44.22] | 36 | 14 | 0.04591836734693878 | 0.03111111111111111 | 0.169070916179955 | 0.00250347637790273 |
[44.22;48.24] | 29 | 23 | 0.036989795918367346 | 0.051111111111111114 | -0.140433387027732 | 0.00198310412180317 |
[48.24;52.26] | 21 | 16 | 0.026785714285714288 | 0.035555555555555556 | -0.1230042368311 | 0.00107872763252671 |
[52.26;56.28] | 12 | 15 | 0.015306122448979591 | 0.03333333333333333 | -0.338013561917151 | 0.00609344176245204 |
[56.28;60.30] | 12 | 9 | 0.015306122448979591 | 0.02 | -0.116164812300795 | 0.0005452634046772 |
[60.30;64.32] | 14 | 6 | 0.017857142857142856 | 0.013333333333333332 | 0.1268732363855 | 0.00057395035507726 |
[64.32;68.34] | 5 | 0 | 0.006377551020408163 | 0.0 | 0.0 | 0.0 |
[68.34;72.36] | 5 | 0 | 0.006377551020408163 | 0.0 | 0.0 | 0.0 |
[72.36;76.38] | 1 | 1 | 0.001275510204081633 | 0.002222222222222222 | -0.241103548909095 | 0.000228255627368587 |
[76.38;80.40] | 0 | 1 | 0.0 | 0.002222222222222222 | 0.0 | 0.0 |
total | 784 | 450 | 0.06947891723888959 |
Rows: 1-22 | Columns: 7
See Also¶
vDataFrame.iv_woe | Computes the Information Value (IV) Table. |
(c) Copyright [2020-2022] Vertica