From 07dc0c3b75c916cd9cd5a1c0f7a901c96b3883aa Mon Sep 17 00:00:00 2001
From: ibidyouadu <angel.d.umana@gmail.com>
Date: Sun, 25 Oct 2020 02:03:47 -0400
Subject: [PATCH] Revised data, experimented with multicollinearity, tested
 some models

---
 fl_irma_maxwind.csv |  16 -------
 irma.csv            | 100 ++++++++++++++++++++++----------------------
 irma_modeling.ipynb |   2 +-
 3 files changed, 51 insertions(+), 67 deletions(-)
 delete mode 100644 fl_irma_maxwind.csv

diff --git a/fl_irma_maxwind.csv b/fl_irma_maxwind.csv
deleted file mode 100644
index 8dd9848..0000000
--- a/fl_irma_maxwind.csv
+++ /dev/null
@@ -1,16 +0,0 @@
-date,Alachua County,Baker County,Bay County,Bradford County,Brevard County,Broward County,Calhoun County,Charlotte County,Citrus County,Clay County,Collier County,Columbia County,DeSoto County,Dixie County,Duval County,Escambia County,Flagler County,Franklin County,Gadsden County,Gilchrist County,Glades County,Gulf County,Hamilton County,Hardee County,Hendry County,Hernando County,Highlands County,Hillsborough County,Holmes County,Indian River County,Jackson County,Jefferson County,Lafayette County,Lake County,Lee County,Leon County,Levy County,Liberty County,Madison County,Manatee County,Marion County,Martin County,Miami-Dade County,Monroe County,Nassau County,Okaloosa County,Okeechobee County,Orange County,Osceola County,Palm Beach County,Pasco County,Pinellas County,Polk County,Putnam County,St. Johns County,St. Lucie County,Santa Rosa County,Sarasota County,Seminole County,Sumter County,Suwannee County,Taylor County,Union County,Volusia County,Wakulla County,Walton County,Washington County
-2017-09-03,4.1,4.1,8.9,4.1,8.0,9.9,15.9,9.9,9.9,4.1,14.0,4.1,9.9,9.9,9.9,17.1,6.0,11.1,11.1,9.9,8.9,7.0,7.0,18.1,14.0,9.9,18.1,5.1,,7.0,,11.1,7.0,6.0,7.0,11.1,9.9,11.1,7.0,8.9,5.1,7.0,9.9,9.9,8.0,11.1,8.9,7.0,9.9,15.9,9.9,7.0,11.1,8.9,8.9,7.0,8.0,8.9,6.0,6.0,7.0,7.0,4.1,7.0,11.1,8.9,
-2017-09-04,7.0,6.0,9.9,7.0,8.0,11.1,8.0,13.0,15.9,6.0,8.0,7.0,13.0,9.9,12.0,9.9,8.9,8.0,13.0,9.9,15.9,6.0,8.9,12.0,8.0,15.9,12.0,8.0,,9.9,,13.0,8.9,11.1,14.0,13.0,9.9,8.0,8.9,8.9,8.9,8.0,13.0,13.0,9.9,7.0,15.9,11.1,8.9,9.9,15.9,9.9,15.9,8.9,8.9,9.9,11.1,8.9,12.0,11.1,8.9,8.9,7.0,15.0,13.0,9.9,
-2017-09-05,7.0,6.0,9.9,7.0,9.9,13.0,9.9,20.0,7.0,6.0,19.0,7.0,20.0,9.9,9.9,11.1,9.9,8.0,9.9,9.9,8.9,8.9,8.9,19.0,19.0,7.0,19.0,4.1,,8.0,,9.9,8.9,8.0,18.1,9.9,9.9,8.0,8.9,8.9,4.1,6.0,13.0,13.0,8.0,6.0,8.9,15.0,20.0,11.1,7.0,9.9,6.0,11.1,11.1,8.0,6.0,8.9,12.0,8.0,8.9,8.9,7.0,9.9,9.9,9.9,
-2017-09-06,11.1,7.0,11.1,11.1,9.9,14.0,22.0,8.9,9.9,7.0,13.0,11.1,8.9,8.0,8.9,12.0,8.9,8.0,13.0,8.0,7.0,14.0,12.0,11.1,13.0,9.9,11.1,7.0,,14.0,,13.0,12.0,13.0,11.1,13.0,8.0,8.0,12.0,9.9,9.9,14.0,14.0,14.0,9.9,8.9,7.0,8.0,15.0,12.0,9.9,9.9,14.0,9.9,9.9,14.0,12.0,9.9,12.0,13.0,12.0,12.0,11.1,7.0,13.0,11.1,
-2017-09-07,8.9,9.9,12.0,8.9,9.9,13.0,11.1,20.0,9.9,9.9,20.0,8.9,20.0,11.1,12.0,8.9,13.0,8.9,8.0,11.1,11.1,13.0,8.9,17.1,20.0,9.9,17.1,9.9,5.1,9.9,5.1,8.0,8.9,13.0,13.0,8.0,11.1,8.9,8.9,8.9,8.9,14.0,12.0,12.0,11.1,8.0,11.1,13.0,17.1,11.1,9.9,9.9,13.0,12.0,12.0,9.9,9.9,8.9,12.0,13.0,8.9,8.9,8.9,9.9,8.0,11.1,5.1
-2017-09-08,14.0,15.0,9.9,14.0,14.0,17.1,8.0,22.0,17.1,15.0,25.1,14.0,22.0,12.0,17.1,9.9,22.0,11.1,11.1,12.0,12.0,11.1,11.1,14.0,25.1,17.1,14.0,13.0,5.1,14.0,5.1,11.1,11.1,19.0,17.1,11.1,12.0,11.1,11.1,20.0,13.0,12.0,15.0,15.0,15.9,8.0,12.0,15.9,13.0,17.1,17.1,20.0,13.0,18.1,18.1,14.0,8.9,20.0,18.1,19.0,11.1,11.1,14.0,13.0,11.1,9.9,5.1
-2017-09-09,15.9,13.0,17.1,15.9,20.0,24.1,12.0,22.9,20.0,13.0,20.0,15.9,22.9,19.0,22.9,11.1,21.0,13.0,15.0,19.0,20.0,15.9,14.0,20.0,20.0,20.0,20.0,17.1,,15.9,,15.0,14.0,19.0,20.0,15.0,19.0,13.0,14.0,18.1,14.0,17.1,29.9,29.9,21.0,12.0,20.0,19.0,20.0,22.9,20.0,18.1,15.0,22.9,22.9,15.9,15.0,18.1,18.1,19.0,14.0,14.0,15.9,25.1,15.0,15.0,
-2017-09-10,20.0,14.0,22.9,20.0,28.9,49.0,18.1,44.1,22.0,14.0,63.9,20.0,44.1,25.1,28.9,15.9,35.0,17.1,17.1,25.1,28.9,22.9,18.1,45.1,63.9,22.0,45.1,19.0,20.0,49.9,20.0,17.1,18.1,28.0,49.9,17.1,25.1,17.1,18.1,40.0,18.1,22.0,42.9,42.9,25.1,15.9,28.9,36.9,49.9,51.1,22.0,33.0,33.0,44.1,44.1,49.9,25.1,40.0,42.0,28.0,18.1,18.1,20.0,25.1,17.1,24.1,20.0
-2017-09-11,35.0,24.1,24.1,35.0,41.0,17.1,28.9,40.0,33.0,24.1,39.0,35.0,40.0,35.9,42.9,21.0,44.1,22.9,29.9,35.9,40.0,27.0,20.0,54.0,39.0,33.0,54.0,27.0,18.1,48.0,18.1,29.9,20.0,36.9,19.0,29.9,35.9,22.9,20.0,42.0,32.1,19.0,21.0,21.0,42.9,21.0,40.0,44.1,49.0,42.0,33.0,42.9,36.9,45.1,45.1,48.0,20.0,42.0,44.1,36.9,20.0,20.0,35.0,35.0,29.9,24.1,18.1
-2017-09-12,14.0,12.0,18.1,14.0,12.0,8.0,18.1,11.1,18.1,12.0,11.1,14.0,11.1,13.0,20.0,15.0,11.1,12.0,14.0,13.0,11.1,9.9,,8.9,11.1,18.1,8.9,6.0,8.0,8.9,8.0,14.0,,11.1,9.9,14.0,13.0,12.0,,15.0,13.0,12.0,9.9,9.9,15.9,15.0,11.1,13.0,14.0,9.9,18.1,12.0,,14.0,14.0,8.9,12.0,15.0,15.9,11.1,,,14.0,,14.0,17.1,8.0
-2017-09-13,8.0,7.0,8.9,8.0,8.9,12.0,11.1,7.0,8.0,7.0,8.9,8.0,7.0,11.1,9.9,14.0,8.0,6.0,11.1,11.1,6.0,8.9,,6.0,8.9,8.0,6.0,8.9,,14.0,,11.1,,4.1,8.9,11.1,11.1,6.0,,8.9,5.1,9.9,9.9,9.9,8.9,11.1,6.0,9.9,8.9,14.0,8.0,8.0,,9.9,9.9,14.0,8.9,8.9,8.0,4.1,,,8.0,,11.1,12.0,
-2017-09-14,8.9,4.1,8.9,8.9,12.0,12.0,6.0,15.0,8.0,4.1,11.1,8.9,15.0,8.0,8.0,11.1,8.9,8.9,6.0,8.0,8.0,4.1,,9.9,11.1,8.0,9.9,7.0,,9.9,,6.0,,5.1,9.9,6.0,8.0,8.9,,9.9,,12.0,9.9,9.9,8.9,7.0,8.0,15.9,13.0,13.0,8.0,14.0,,9.9,9.9,9.9,12.0,9.9,9.9,5.1,,,8.9,,6.0,9.9,
-2017-09-15,15.0,12.0,8.9,15.0,11.1,13.0,7.0,8.0,8.9,12.0,8.9,15.0,8.0,9.9,11.1,12.0,9.9,7.0,9.9,9.9,8.9,8.9,7.0,13.0,8.9,8.9,13.0,6.0,,8.9,,9.9,7.0,9.9,8.0,9.9,9.9,7.0,7.0,13.0,7.0,8.9,12.0,12.0,13.0,7.0,8.9,11.1,19.0,13.0,8.9,13.0,,12.0,12.0,8.9,13.0,13.0,12.0,9.9,7.0,7.0,15.0,,9.9,9.9,
-2017-09-16,8.0,8.9,17.1,8.0,14.0,12.0,8.0,12.0,17.1,8.9,11.1,8.0,12.0,7.0,8.9,8.0,15.0,7.0,9.9,7.0,13.0,7.0,8.0,12.0,11.1,17.1,12.0,7.0,,11.1,,9.9,8.0,11.1,11.1,9.9,7.0,7.0,8.0,9.9,8.9,13.0,15.0,15.0,8.9,8.9,13.0,12.0,15.0,15.0,17.1,11.1,,12.0,12.0,11.1,12.0,9.9,14.0,11.1,8.0,8.0,8.0,,9.9,8.9,
-2017-09-17,9.9,9.9,9.9,9.9,15.9,9.9,8.9,11.1,9.9,9.9,9.9,9.9,11.1,11.1,12.0,8.9,17.1,6.0,8.9,11.1,11.1,7.0,8.9,12.0,9.9,9.9,12.0,7.0,,11.1,,8.9,8.9,11.1,11.1,8.9,11.1,6.0,8.9,12.0,8.0,14.0,11.1,11.1,11.1,14.0,11.1,13.0,13.0,15.0,9.9,13.0,,15.9,15.9,11.1,8.9,12.0,15.0,11.1,8.9,8.9,9.9,,8.9,8.0,
diff --git a/irma.csv b/irma.csv
index 6db5256..9a5ba47 100644
--- a/irma.csv
+++ b/irma.csv
@@ -1,50 +1,50 @@
-county,wind_total,wind_peak,gust_total,gust_peak,maxwind_total,maxwind_peak,precip_total,precip_peak,poverty_pop,poverty_rate,mhi,gdp,population,twt_total,twt_peak,dmg
-Alachua County,87.19999999999996,21.4,173.0,53.0,186.8,35.0,18.250000000000004,11.39,53816,21.2,45230,11912080,269956,182,39,9306765.0
-Baker County,81.00000000000001,18.6,152.0,38.1,153.0,24.1,9.21,7.06,3900,15.3,51856,472948,28355,1,1,1360525.84
-Bradford County,87.19999999999996,21.4,173.0,53.0,186.8,35.0,18.250000000000004,11.39,4533,19.1,44997,532487,27732,4,1,3246248.07
-Brevard County,130.9,28.7,240.3,69.9,223.5,41.0,4.69,2.25,72303,12.4,52596,20453753,596849,354,71,31928910.59
-Broward County,128.2,31.7,216.9,73.0,235.2,49.0,10.44,4.11,252288,13.1,56702,96591919,1951260,2036,382,132955108.79
-Charlotte County,112.1,24.9,305.2,63.9,265.0,44.1,1.69,0.76,19300,10.8,51583,3966314,184998,72,20,6625988.329999999
-Citrus County,103.3,28.8,186.8,55.9,214.7,33.0,13.18,5.97,20654,14.4,43147,3335110,147929,67,13,5568338.59
-Clay County,81.00000000000001,18.6,152.0,38.1,153.0,24.1,9.21,7.06,20889,9.9,65375,3976007,216072,53,8,12195897.65
-Collier County,41.5,12.1,296.0,76.9,283.0,63.9,5.12,4.2,43075,11.7,66709,16124953,378488,231,63,61941331.1
-Columbia County,87.19999999999996,21.4,173.0,53.0,186.8,35.0,18.250000000000004,11.39,10720,16.5,42097,1826541,70503,14,4,3225476.29
-DeSoto County,112.1,24.9,305.2,63.9,265.0,44.1,1.69,0.76,8766,26.1,37342,735286,37489,5,2,4049290.29
-Dixie County,96.2,26.8,226.5,53.0,200.9,35.9,4.3900000000000015,2.38,3627,24.4,38355,178261,16700,7,5,907905.74
-Duval County,143.00000000000003,29.3,179.9,62.0,234.4,42.9,9.21,7.06,138069,15.1,52105,60146765,950181,772,137,47409375.6
-Flagler County,116.3,23.5,226.3,59.1,238.8,44.1,8.659999999999998,4.66,13137,12.0,52713,1809151,112067,63,16,7243310.27
-Gilchrist County,96.2,26.8,226.5,53.0,200.9,35.9,4.3900000000000015,2.38,2675,16.1,42880,254260,18256,3,1,641836.8
-Glades County,77.10000000000002,22.1,239.2,62.0,210.8,40.0,9.96,7.09,2312,18.9,42865,171573,13724,4,2,1684916.42
-Hamilton County,57.7,17.0,135.9,32.1,132.8,20.0,4.3900000000000015,2.38,2791,24.0,35262,377309,14310,5,3,779650.4900000001
-Hardee County,100.2,25.9,372.1,75.0,272.2,54.0,2.6300000000000003,1.36,6026,23.3,40056,893349,27245,8,3,6791780.699999997
-Hendry County,115.1,27.8,296.0,76.9,283.0,63.9,12.61,8.84,9525,23.9,38361,1241872,41556,2,1,4864094.83
-Hernando County,103.3,28.8,186.8,55.9,214.7,33.0,13.18,5.97,25773,14.0,44710,3031267,190865,43,12,6987438.839999999
-Highlands County,100.2,25.9,372.1,75.0,272.2,54.0,2.6300000000000003,1.36,20051,19.8,37445,2088782,105424,46,16,11041809.99
-Hillsborough County,42.30000000000001,13.5,134.8,48.0,152.10000000000005,27.0,5.43,4.5,214442,15.5,54741,77093796,1436888,990,234,41393416.09
-Indian River County,107.0,24.0,251.2,76.9,240.5,49.9,10.86,8.11,16249,10.6,51797,5001702,157413,79,23,5417250.77
-Lafayette County,57.7,17.0,135.9,32.1,132.8,20.0,4.3900000000000015,2.38,1579,22.7,41549,160614,8732,2,1,438725.36
-Lake County,101.7,25.4,248.1,60.0,206.4,36.9,10.51,8.05,43020,12.6,51429,7452383,356495,151,47,14187385.8
-Lee County,101.2,22.7,214.7,73.0,228.1,49.9,6.079999999999999,1.89,85844,11.8,54198,23806704,754610,380,63,62696698.67
-Levy County,96.2,26.8,226.5,53.0,200.9,35.9,4.3900000000000015,2.38,8329,20.8,37272,636701,40770,7,2,1823097.65
-Manatee County,116.2,25.2,240.8,55.9,234.3,42.0,7.079999999999999,5.71,41057,10.8,55189,11968028,394855,170,33,13692987.63
-Marion County,60.50000000000001,22.0,186.1,47.0,156.1,32.1,0.4400000000000001,0.23,55880,16.2,43772,7956019,359977,121,30,19342692.11
-Martin County,101.2,13.7,183.1,34.0,188.9,22.0,16.319999999999997,9.43,17002,10.9,58344,6533103,160912,85,22,2936390.78
-Miami-Dade County,129.6,28.7,269.0,62.9,238.5,42.9,9.33,5.18,452649,16.7,49758,141734334,2761581,4063,730,241746424.33
-Monroe County,129.6,28.7,269.0,62.9,238.5,42.9,9.33,5.18,8963,11.8,63009,4097511,75027,158,31,106189963.06
-Nassau County,115.8,28.5,203.0,75.0,218.5,42.9,10.05,9.01,7484,9.1,70590,1886261,85832,49,16,4184525.26
-Okeechobee County,77.10000000000002,22.1,239.2,62.0,210.8,40.0,2.6300000000000003,1.36,8415,21.8,42524,1021477,41537,7,2,2920370.44
-Orange County,107.1,25.5,216.3,66.0,244.9,44.1,10.36,7.48,201528,15.3,54021,89817807,1380645,1794,346,52163799.68
-Osceola County,115.5,29.9,268.0,69.0,285.7000000000001,49.9,13.429999999999998,7.02,48892,14.0,49284,9207981,367990,205,50,12440584.46
-Palm Beach County,144.99999999999997,31.0,335.2,76.0,273.0,51.1,3.96,1.92,170868,11.8,60059,76866505,1485941,904,167,83072778.53999999
-Pasco County,103.3,28.8,186.8,55.9,214.7,33.0,13.18,5.97,67635,13.0,51247,9330553,539630,206,58,18248964.51
-Pinellas County,113.5,24.6,242.0,63.9,231.7,42.9,5.85,4.32,115990,12.2,51488,44125945,975280,730,159,56327903.18
-Polk County,77.5,33.5,165.8,55.9,157.9,36.9,8.06,6.21,107844,16.1,48328,20779632,708009,524,116,43510879.41
-Putnam County,159.99999999999997,35.5,205.8,62.0,254.7,45.1,18.250000000000004,11.39,18954,26.3,34390,1925314,74163,16,4,11106167.89
-Sarasota County,159.99999999999997,35.5,205.8,62.0,254.7,45.1,9.21,7.06,20118,8.3,77022,7313073,254261,243,68,13065488.090000002
-Seminole County,107.0,24.0,251.2,76.9,240.5,49.9,16.319999999999997,9.43,39839,12.8,49995,7030683,321128,331,81,21730578.29
-St. Johns County,116.2,25.2,240.8,55.9,234.3,42.0,7.079999999999999,5.71,38065,9.2,58423,15773229,426718,154,34,18622275.3
-St. Lucie County,107.79999999999998,25.9,219.3,61.0,251.1,44.1,11.28,9.24,51321,11.2,63865,17902542,467832,112,32,23506428.65
-Sumter County,101.7,25.4,248.1,60.0,206.4,36.9,10.51,8.05,10672,9.1,57931,2312425,128754,21,7,3424526.2299999995
-Suwannee County,57.7,17.0,135.9,32.1,132.8,20.0,4.3900000000000015,2.38,8299,20.3,44144,851332,44191,12,4,2045322.54
-Union County,87.19999999999996,21.4,173.0,53.0,186.8,35.0,18.250000000000004,11.39,2291,22.2,47373,341763,14940,3,3,577498.4500000001
-Volusia County,62.6,21.6,148.1,55.0,147.0,35.0,8.659999999999998,4.66,79877,15.2,46911,14864234,547538,266,51,37825717.1
+county,maxwind_mean,maxwind_peak,precip_total,precip_peak,mhi,poverty_rate,poverty_pop,population,gdp,twt_total,twt_peak,dmg
+Alachua County,12.453333333333335,35.0,18.250000000000004,11.39,45230,21.2,53816,269956,11912080,182,39,9306765.0
+Baker County,10.2,24.1,9.21,7.06,51856,15.3,3900,28355,472948,1,1,1360525.84
+Bradford County,12.453333333333335,35.0,18.250000000000004,11.39,44997,19.1,4533,27732,532487,4,1,3246248.07
+Brevard County,14.9,41.0,4.69,2.25,52596,12.4,72303,596849,20453753,354,71,31928910.59
+Broward County,15.68,49.0,10.44,4.11,56702,13.1,252288,1951260,96591919,2036,382,132955108.79
+Charlotte County,17.666666666666668,44.1,1.69,0.76,51583,10.8,19300,184998,3966314,72,20,6625988.329999999
+Citrus County,14.313333333333333,33.0,13.18,5.97,43147,14.4,20654,147929,3335110,67,13,5568338.59
+Clay County,10.2,24.1,9.21,7.06,65375,9.9,20889,216072,3976007,53,8,12195897.65
+Collier County,18.866666666666667,63.9,5.12,4.2,66709,11.7,43075,378488,16124953,231,63,61941331.1
+Columbia County,12.453333333333335,35.0,18.250000000000004,11.39,42097,16.5,10720,70503,1826541,14,4,3225476.29
+DeSoto County,17.666666666666668,44.1,1.69,0.76,37342,26.1,8766,37489,735286,5,2,4049290.29
+Dixie County,13.393333333333334,35.9,4.3900000000000015,2.38,38355,24.4,3627,16700,178261,7,5,907905.74
+Duval County,15.626666666666667,42.9,9.21,7.06,52105,15.1,138069,950181,60146765,772,137,47409375.6
+Flagler County,15.92,44.1,8.659999999999998,4.66,52713,12.0,13137,112067,1809151,63,16,7243310.27
+Gilchrist County,13.393333333333334,35.9,4.3900000000000015,2.38,42880,16.1,2675,18256,254260,3,1,641836.8
+Glades County,14.053333333333333,40.0,9.96,7.09,42865,18.9,2312,13724,171573,4,2,1684916.42
+Hamilton County,11.066666666666668,20.0,4.3900000000000015,2.38,35262,24.0,2791,14310,377309,5,3,779650.4900000001
+Hardee County,18.146666666666665,54.0,2.6300000000000003,1.36,40056,23.3,6026,27245,893349,8,3,6791780.699999997
+Hendry County,18.866666666666667,63.9,12.61,8.84,38361,23.9,9525,41556,1241872,2,1,4864094.83
+Hernando County,14.313333333333333,33.0,13.18,5.97,44710,14.0,25773,190865,3031267,43,12,6987438.839999999
+Highlands County,18.146666666666665,54.0,2.6300000000000003,1.36,37445,19.8,20051,105424,2088782,46,16,11041809.99
+Hillsborough County,10.140000000000002,27.0,5.43,4.5,54741,15.5,214442,1436888,77093796,990,234,41393416.09
+Indian River County,16.033333333333335,49.9,10.86,8.11,51797,10.6,16249,157413,5001702,79,23,5417250.77
+Lafayette County,11.066666666666668,20.0,4.3900000000000015,2.38,41549,22.7,1579,8732,160614,2,1,438725.36
+Lake County,13.759999999999998,36.9,10.51,8.05,51429,12.6,43020,356495,7452383,151,47,14187385.8
+Lee County,15.206666666666667,49.9,6.079999999999999,1.89,54198,11.8,85844,754610,23806704,380,63,62696698.67
+Levy County,13.393333333333334,35.9,4.3900000000000015,2.38,37272,20.8,8329,40770,636701,7,2,1823097.65
+Manatee County,15.620000000000001,42.0,7.079999999999999,5.71,55189,10.8,41057,394855,11968028,170,33,13692987.63
+Marion County,11.15,32.1,0.4400000000000001,0.23,43772,16.2,55880,359977,7956019,121,30,19342692.11
+Martin County,12.593333333333334,22.0,16.319999999999997,9.43,58344,10.9,17002,160912,6533103,85,22,2936390.78
+Miami-Dade County,15.9,42.9,9.33,5.18,49758,16.7,452649,2761581,141734334,4063,730,241746424.33
+Monroe County,15.9,42.9,9.33,5.18,63009,11.8,8963,75027,4097511,158,31,106189963.06
+Nassau County,14.566666666666666,42.9,10.05,9.01,70590,9.1,7484,85832,1886261,49,16,4184525.26
+Okeechobee County,14.053333333333333,40.0,2.6300000000000003,1.36,42524,21.8,8415,41537,1021477,7,2,2920370.44
+Orange County,16.326666666666668,44.1,10.36,7.48,54021,15.3,201528,1380645,89817807,1794,346,52163799.68
+Osceola County,19.04666666666667,49.9,13.429999999999998,7.02,49284,14.0,48892,367990,9207981,205,50,12440584.46
+Palm Beach County,18.2,51.1,3.96,1.92,60059,11.8,170868,1485941,76866505,904,167,83072778.53999999
+Pasco County,14.313333333333333,33.0,13.18,5.97,51247,13.0,67635,539630,9330553,206,58,18248964.51
+Pinellas County,15.446666666666665,42.9,5.85,4.32,51488,12.2,115990,975280,44125945,730,159,56327903.18
+Polk County,17.544444444444444,36.9,8.06,6.21,48328,16.1,107844,708009,20779632,524,116,43510879.41
+Putnam County,16.98,45.1,18.250000000000004,11.39,34390,26.3,18954,74163,1925314,16,4,11106167.89
+Sarasota County,15.620000000000001,45.1,9.21,7.06,77022,8.3,20118,254261,7313073,243,68,13065488.090000002
+Seminole County,16.74,49.9,16.319999999999997,9.43,49995,12.8,39839,321128,7030683,331,81,21730578.29
+St. Johns County,16.98,42.0,7.079999999999999,5.71,58423,9.2,38065,426718,15773229,154,34,18622275.3
+St. Lucie County,16.033333333333335,44.1,11.28,9.24,63865,11.2,51321,467832,17902542,112,32,23506428.65
+Sumter County,13.759999999999998,36.9,10.51,8.05,57931,9.1,10672,128754,2312425,21,7,3424526.2299999995
+Suwannee County,11.066666666666668,20.0,4.3900000000000015,2.38,44144,20.3,8299,44191,851332,12,4,2045322.54
+Union County,12.453333333333335,35.0,18.250000000000004,11.39,47373,22.2,2291,14940,341763,3,3,577498.4500000001
+Volusia County,16.333333333333332,35.0,8.659999999999998,4.66,46911,15.2,79877,547538,14864234,266,51,37825717.1
diff --git a/irma_modeling.ipynb b/irma_modeling.ipynb
index 911637c..c0d5d96 100644
--- a/irma_modeling.ipynb
+++ b/irma_modeling.ipynb
@@ -1 +1 @@
-{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"irma_modeling.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true,"mount_file_id":"1Q4J-Du4O02VX-aMhBgnqA8CcQVFolx1x","authorship_tag":"ABX9TyMB9PeN6zk1xqvplmHHBIWs"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"dpQIA2trCnVq"},"source":["# Hurricane Irma Damage Assessment Modeling\n","\n","In this notebook we develop a multilinear and decision tree model to assess damages from hurricane Irma.\n","\n","Our dataset consists of weather, socioeconomic, and Twitter parameters from 49 counties in Florida during Irma. The dependent variable is the amount of federal aid from FEMA that a county received, `dmg`."]},{"cell_type":"code","metadata":{"id":"ShFs31gOCjKO","executionInfo":{"status":"ok","timestamp":1603527192161,"user_tz":240,"elapsed":824,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"d7702916-fac1-4bd4-bff8-5962969cda08","colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["%cd '/content/drive/My Drive/Colab Notebooks/disaster_assessment/irma_modeling'\n","\n","import pandas as pd\n","import numpy as np\n","from matplotlib import pyplot as plt\n","import seaborn as sns; sns.set()\n","\n","df = pd.read_csv('irma.csv')\n","df.set_index(keys='county',inplace=True)\n","df"],"execution_count":1,"outputs":[{"output_type":"stream","text":["/content/drive/My Drive/Colab Notebooks/disaster_assessment/irma_modeling\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>wind_total</th>\n","      <th>wind_peak</th>\n","      <th>gust_total</th>\n","      <th>gust_peak</th>\n","      <th>maxwind_total</th>\n","      <th>maxwind_peak</th>\n","      <th>precip_total</th>\n","      <th>precip_peak</th>\n","      <th>poverty_pop</th>\n","      <th>poverty_rate</th>\n","      <th>mhi</th>\n","      <th>gdp</th>\n","      <th>population</th>\n","      <th>twt_total</th>\n","      <th>twt_peak</th>\n","      <th>dmg</th>\n","    </tr>\n","    <tr>\n","      <th>county</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Alachua County</th>\n","      <td>87.2</td>\n","      <td>21.4</td>\n","      <td>173.0</td>\n","      <td>53.0</td>\n","      <td>186.8</td>\n","      <td>35.0</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>53816</td>\n","      <td>21.2</td>\n","      <td>45230</td>\n","      <td>11912080</td>\n","      <td>269956</td>\n","      <td>182</td>\n","      <td>39</td>\n","      <td>9.306765e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Baker County</th>\n","      <td>81.0</td>\n","      <td>18.6</td>\n","      <td>152.0</td>\n","      <td>38.1</td>\n","      <td>153.0</td>\n","      <td>24.1</td>\n","      <td>9.21</td>\n","      <td>7.06</td>\n","      <td>3900</td>\n","      <td>15.3</td>\n","      <td>51856</td>\n","      <td>472948</td>\n","      <td>28355</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1.360526e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Bradford County</th>\n","      <td>87.2</td>\n","      <td>21.4</td>\n","      <td>173.0</td>\n","      <td>53.0</td>\n","      <td>186.8</td>\n","      <td>35.0</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>4533</td>\n","      <td>19.1</td>\n","      <td>44997</td>\n","      <td>532487</td>\n","      <td>27732</td>\n","      <td>4</td>\n","      <td>1</td>\n","      <td>3.246248e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Brevard County</th>\n","      <td>130.9</td>\n","      <td>28.7</td>\n","      <td>240.3</td>\n","      <td>69.9</td>\n","      <td>223.5</td>\n","      <td>41.0</td>\n","      <td>4.69</td>\n","      <td>2.25</td>\n","      <td>72303</td>\n","      <td>12.4</td>\n","      <td>52596</td>\n","      <td>20453753</td>\n","      <td>596849</td>\n","      <td>354</td>\n","      <td>71</td>\n","      <td>3.192891e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Broward County</th>\n","      <td>128.2</td>\n","      <td>31.7</td>\n","      <td>216.9</td>\n","      <td>73.0</td>\n","      <td>235.2</td>\n","      <td>49.0</td>\n","      <td>10.44</td>\n","      <td>4.11</td>\n","      <td>252288</td>\n","      <td>13.1</td>\n","      <td>56702</td>\n","      <td>96591919</td>\n","      <td>1951260</td>\n","      <td>2036</td>\n","      <td>382</td>\n","      <td>1.329551e+08</td>\n","    </tr>\n","    <tr>\n","      <th>Charlotte County</th>\n","      <td>112.1</td>\n","      <td>24.9</td>\n","      <td>305.2</td>\n","      <td>63.9</td>\n","      <td>265.0</td>\n","      <td>44.1</td>\n","      <td>1.69</td>\n","      <td>0.76</td>\n","      <td>19300</td>\n","      <td>10.8</td>\n","      <td>51583</td>\n","      <td>3966314</td>\n","      <td>184998</td>\n","      <td>72</td>\n","      <td>20</td>\n","      <td>6.625988e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Citrus County</th>\n","      <td>103.3</td>\n","      <td>28.8</td>\n","      <td>186.8</td>\n","      <td>55.9</td>\n","      <td>214.7</td>\n","      <td>33.0</td>\n","      <td>13.18</td>\n","      <td>5.97</td>\n","      <td>20654</td>\n","      <td>14.4</td>\n","      <td>43147</td>\n","      <td>3335110</td>\n","      <td>147929</td>\n","      <td>67</td>\n","      <td>13</td>\n","      <td>5.568339e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Clay County</th>\n","      <td>81.0</td>\n","      <td>18.6</td>\n","      <td>152.0</td>\n","      <td>38.1</td>\n","      <td>153.0</td>\n","      <td>24.1</td>\n","      <td>9.21</td>\n","      <td>7.06</td>\n","      <td>20889</td>\n","      <td>9.9</td>\n","      <td>65375</td>\n","      <td>3976007</td>\n","      <td>216072</td>\n","      <td>53</td>\n","      <td>8</td>\n","      <td>1.219590e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Collier County</th>\n","      <td>41.5</td>\n","      <td>12.1</td>\n","      <td>296.0</td>\n","      <td>76.9</td>\n","      <td>283.0</td>\n","      <td>63.9</td>\n","      <td>5.12</td>\n","      <td>4.20</td>\n","      <td>43075</td>\n","      <td>11.7</td>\n","      <td>66709</td>\n","      <td>16124953</td>\n","      <td>378488</td>\n","      <td>231</td>\n","      <td>63</td>\n","      <td>6.194133e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Columbia County</th>\n","      <td>87.2</td>\n","      <td>21.4</td>\n","      <td>173.0</td>\n","      <td>53.0</td>\n","      <td>186.8</td>\n","      <td>35.0</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>10720</td>\n","      <td>16.5</td>\n","      <td>42097</td>\n","      <td>1826541</td>\n","      <td>70503</td>\n","      <td>14</td>\n","      <td>4</td>\n","      <td>3.225476e+06</td>\n","    </tr>\n","    <tr>\n","      <th>DeSoto County</th>\n","      <td>112.1</td>\n","      <td>24.9</td>\n","      <td>305.2</td>\n","      <td>63.9</td>\n","      <td>265.0</td>\n","      <td>44.1</td>\n","      <td>1.69</td>\n","      <td>0.76</td>\n","      <td>8766</td>\n","      <td>26.1</td>\n","      <td>37342</td>\n","      <td>735286</td>\n","      <td>37489</td>\n","      <td>5</td>\n","      <td>2</td>\n","      <td>4.049290e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Dixie County</th>\n","      <td>96.2</td>\n","      <td>26.8</td>\n","      <td>226.5</td>\n","      <td>53.0</td>\n","      <td>200.9</td>\n","      <td>35.9</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>3627</td>\n","      <td>24.4</td>\n","      <td>38355</td>\n","      <td>178261</td>\n","      <td>16700</td>\n","      <td>7</td>\n","      <td>5</td>\n","      <td>9.079057e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Duval County</th>\n","      <td>143.0</td>\n","      <td>29.3</td>\n","      <td>179.9</td>\n","      <td>62.0</td>\n","      <td>234.4</td>\n","      <td>42.9</td>\n","      <td>9.21</td>\n","      <td>7.06</td>\n","      <td>138069</td>\n","      <td>15.1</td>\n","      <td>52105</td>\n","      <td>60146765</td>\n","      <td>950181</td>\n","      <td>772</td>\n","      <td>137</td>\n","      <td>4.740938e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Flagler County</th>\n","      <td>116.3</td>\n","      <td>23.5</td>\n","      <td>226.3</td>\n","      <td>59.1</td>\n","      <td>238.8</td>\n","      <td>44.1</td>\n","      <td>8.66</td>\n","      <td>4.66</td>\n","      <td>13137</td>\n","      <td>12.0</td>\n","      <td>52713</td>\n","      <td>1809151</td>\n","      <td>112067</td>\n","      <td>63</td>\n","      <td>16</td>\n","      <td>7.243310e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Gilchrist County</th>\n","      <td>96.2</td>\n","      <td>26.8</td>\n","      <td>226.5</td>\n","      <td>53.0</td>\n","      <td>200.9</td>\n","      <td>35.9</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>2675</td>\n","      <td>16.1</td>\n","      <td>42880</td>\n","      <td>254260</td>\n","      <td>18256</td>\n","      <td>3</td>\n","      <td>1</td>\n","      <td>6.418368e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Glades County</th>\n","      <td>77.1</td>\n","      <td>22.1</td>\n","      <td>239.2</td>\n","      <td>62.0</td>\n","      <td>210.8</td>\n","      <td>40.0</td>\n","      <td>9.96</td>\n","      <td>7.09</td>\n","      <td>2312</td>\n","      <td>18.9</td>\n","      <td>42865</td>\n","      <td>171573</td>\n","      <td>13724</td>\n","      <td>4</td>\n","      <td>2</td>\n","      <td>1.684916e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Hamilton County</th>\n","      <td>57.7</td>\n","      <td>17.0</td>\n","      <td>135.9</td>\n","      <td>32.1</td>\n","      <td>132.8</td>\n","      <td>20.0</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>2791</td>\n","      <td>24.0</td>\n","      <td>35262</td>\n","      <td>377309</td>\n","      <td>14310</td>\n","      <td>5</td>\n","      <td>3</td>\n","      <td>7.796505e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Hardee County</th>\n","      <td>100.2</td>\n","      <td>25.9</td>\n","      <td>372.1</td>\n","      <td>75.0</td>\n","      <td>272.2</td>\n","      <td>54.0</td>\n","      <td>2.63</td>\n","      <td>1.36</td>\n","      <td>6026</td>\n","      <td>23.3</td>\n","      <td>40056</td>\n","      <td>893349</td>\n","      <td>27245</td>\n","      <td>8</td>\n","      <td>3</td>\n","      <td>6.791781e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Hendry County</th>\n","      <td>115.1</td>\n","      <td>27.8</td>\n","      <td>296.0</td>\n","      <td>76.9</td>\n","      <td>283.0</td>\n","      <td>63.9</td>\n","      <td>12.61</td>\n","      <td>8.84</td>\n","      <td>9525</td>\n","      <td>23.9</td>\n","      <td>38361</td>\n","      <td>1241872</td>\n","      <td>41556</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>4.864095e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Hernando County</th>\n","      <td>103.3</td>\n","      <td>28.8</td>\n","      <td>186.8</td>\n","      <td>55.9</td>\n","      <td>214.7</td>\n","      <td>33.0</td>\n","      <td>13.18</td>\n","      <td>5.97</td>\n","      <td>25773</td>\n","      <td>14.0</td>\n","      <td>44710</td>\n","      <td>3031267</td>\n","      <td>190865</td>\n","      <td>43</td>\n","      <td>12</td>\n","      <td>6.987439e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Highlands County</th>\n","      <td>100.2</td>\n","      <td>25.9</td>\n","      <td>372.1</td>\n","      <td>75.0</td>\n","      <td>272.2</td>\n","      <td>54.0</td>\n","      <td>2.63</td>\n","      <td>1.36</td>\n","      <td>20051</td>\n","      <td>19.8</td>\n","      <td>37445</td>\n","      <td>2088782</td>\n","      <td>105424</td>\n","      <td>46</td>\n","      <td>16</td>\n","      <td>1.104181e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Hillsborough County</th>\n","      <td>42.3</td>\n","      <td>13.5</td>\n","      <td>134.8</td>\n","      <td>48.0</td>\n","      <td>152.1</td>\n","      <td>27.0</td>\n","      <td>5.43</td>\n","      <td>4.50</td>\n","      <td>214442</td>\n","      <td>15.5</td>\n","      <td>54741</td>\n","      <td>77093796</td>\n","      <td>1436888</td>\n","      <td>990</td>\n","      <td>234</td>\n","      <td>4.139342e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Indian River County</th>\n","      <td>107.0</td>\n","      <td>24.0</td>\n","      <td>251.2</td>\n","      <td>76.9</td>\n","      <td>240.5</td>\n","      <td>49.9</td>\n","      <td>10.86</td>\n","      <td>8.11</td>\n","      <td>16249</td>\n","      <td>10.6</td>\n","      <td>51797</td>\n","      <td>5001702</td>\n","      <td>157413</td>\n","      <td>79</td>\n","      <td>23</td>\n","      <td>5.417251e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Lafayette County</th>\n","      <td>57.7</td>\n","      <td>17.0</td>\n","      <td>135.9</td>\n","      <td>32.1</td>\n","      <td>132.8</td>\n","      <td>20.0</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>1579</td>\n","      <td>22.7</td>\n","      <td>41549</td>\n","      <td>160614</td>\n","      <td>8732</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>4.387254e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Lake County</th>\n","      <td>101.7</td>\n","      <td>25.4</td>\n","      <td>248.1</td>\n","      <td>60.0</td>\n","      <td>206.4</td>\n","      <td>36.9</td>\n","      <td>10.51</td>\n","      <td>8.05</td>\n","      <td>43020</td>\n","      <td>12.6</td>\n","      <td>51429</td>\n","      <td>7452383</td>\n","      <td>356495</td>\n","      <td>151</td>\n","      <td>47</td>\n","      <td>1.418739e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Lee County</th>\n","      <td>101.2</td>\n","      <td>22.7</td>\n","      <td>214.7</td>\n","      <td>73.0</td>\n","      <td>228.1</td>\n","      <td>49.9</td>\n","      <td>6.08</td>\n","      <td>1.89</td>\n","      <td>85844</td>\n","      <td>11.8</td>\n","      <td>54198</td>\n","      <td>23806704</td>\n","      <td>754610</td>\n","      <td>380</td>\n","      <td>63</td>\n","      <td>6.269670e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Levy County</th>\n","      <td>96.2</td>\n","      <td>26.8</td>\n","      <td>226.5</td>\n","      <td>53.0</td>\n","      <td>200.9</td>\n","      <td>35.9</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>8329</td>\n","      <td>20.8</td>\n","      <td>37272</td>\n","      <td>636701</td>\n","      <td>40770</td>\n","      <td>7</td>\n","      <td>2</td>\n","      <td>1.823098e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Manatee County</th>\n","      <td>116.2</td>\n","      <td>25.2</td>\n","      <td>240.8</td>\n","      <td>55.9</td>\n","      <td>234.3</td>\n","      <td>42.0</td>\n","      <td>7.08</td>\n","      <td>5.71</td>\n","      <td>41057</td>\n","      <td>10.8</td>\n","      <td>55189</td>\n","      <td>11968028</td>\n","      <td>394855</td>\n","      <td>170</td>\n","      <td>33</td>\n","      <td>1.369299e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Marion County</th>\n","      <td>60.5</td>\n","      <td>22.0</td>\n","      <td>186.1</td>\n","      <td>47.0</td>\n","      <td>156.1</td>\n","      <td>32.1</td>\n","      <td>0.44</td>\n","      <td>0.23</td>\n","      <td>55880</td>\n","      <td>16.2</td>\n","      <td>43772</td>\n","      <td>7956019</td>\n","      <td>359977</td>\n","      <td>121</td>\n","      <td>30</td>\n","      <td>1.934269e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Martin County</th>\n","      <td>101.2</td>\n","      <td>13.7</td>\n","      <td>183.1</td>\n","      <td>34.0</td>\n","      <td>188.9</td>\n","      <td>22.0</td>\n","      <td>16.32</td>\n","      <td>9.43</td>\n","      <td>17002</td>\n","      <td>10.9</td>\n","      <td>58344</td>\n","      <td>6533103</td>\n","      <td>160912</td>\n","      <td>85</td>\n","      <td>22</td>\n","      <td>2.936391e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Miami-Dade County</th>\n","      <td>129.6</td>\n","      <td>28.7</td>\n","      <td>269.0</td>\n","      <td>62.9</td>\n","      <td>238.5</td>\n","      <td>42.9</td>\n","      <td>9.33</td>\n","      <td>5.18</td>\n","      <td>452649</td>\n","      <td>16.7</td>\n","      <td>49758</td>\n","      <td>141734334</td>\n","      <td>2761581</td>\n","      <td>4063</td>\n","      <td>730</td>\n","      <td>2.417464e+08</td>\n","    </tr>\n","    <tr>\n","      <th>Monroe County</th>\n","      <td>129.6</td>\n","      <td>28.7</td>\n","      <td>269.0</td>\n","      <td>62.9</td>\n","      <td>238.5</td>\n","      <td>42.9</td>\n","      <td>9.33</td>\n","      <td>5.18</td>\n","      <td>8963</td>\n","      <td>11.8</td>\n","      <td>63009</td>\n","      <td>4097511</td>\n","      <td>75027</td>\n","      <td>158</td>\n","      <td>31</td>\n","      <td>1.061900e+08</td>\n","    </tr>\n","    <tr>\n","      <th>Nassau County</th>\n","      <td>115.8</td>\n","      <td>28.5</td>\n","      <td>203.0</td>\n","      <td>75.0</td>\n","      <td>218.5</td>\n","      <td>42.9</td>\n","      <td>10.05</td>\n","      <td>9.01</td>\n","      <td>7484</td>\n","      <td>9.1</td>\n","      <td>70590</td>\n","      <td>1886261</td>\n","      <td>85832</td>\n","      <td>49</td>\n","      <td>16</td>\n","      <td>4.184525e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Okeechobee County</th>\n","      <td>77.1</td>\n","      <td>22.1</td>\n","      <td>239.2</td>\n","      <td>62.0</td>\n","      <td>210.8</td>\n","      <td>40.0</td>\n","      <td>2.63</td>\n","      <td>1.36</td>\n","      <td>8415</td>\n","      <td>21.8</td>\n","      <td>42524</td>\n","      <td>1021477</td>\n","      <td>41537</td>\n","      <td>7</td>\n","      <td>2</td>\n","      <td>2.920370e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Orange County</th>\n","      <td>107.1</td>\n","      <td>25.5</td>\n","      <td>216.3</td>\n","      <td>66.0</td>\n","      <td>244.9</td>\n","      <td>44.1</td>\n","      <td>10.36</td>\n","      <td>7.48</td>\n","      <td>201528</td>\n","      <td>15.3</td>\n","      <td>54021</td>\n","      <td>89817807</td>\n","      <td>1380645</td>\n","      <td>1794</td>\n","      <td>346</td>\n","      <td>5.216380e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Osceola County</th>\n","      <td>115.5</td>\n","      <td>29.9</td>\n","      <td>268.0</td>\n","      <td>69.0</td>\n","      <td>285.7</td>\n","      <td>49.9</td>\n","      <td>13.43</td>\n","      <td>7.02</td>\n","      <td>48892</td>\n","      <td>14.0</td>\n","      <td>49284</td>\n","      <td>9207981</td>\n","      <td>367990</td>\n","      <td>205</td>\n","      <td>50</td>\n","      <td>1.244058e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Palm Beach County</th>\n","      <td>145.0</td>\n","      <td>31.0</td>\n","      <td>335.2</td>\n","      <td>76.0</td>\n","      <td>273.0</td>\n","      <td>51.1</td>\n","      <td>3.96</td>\n","      <td>1.92</td>\n","      <td>170868</td>\n","      <td>11.8</td>\n","      <td>60059</td>\n","      <td>76866505</td>\n","      <td>1485941</td>\n","      <td>904</td>\n","      <td>167</td>\n","      <td>8.307278e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Pasco County</th>\n","      <td>103.3</td>\n","      <td>28.8</td>\n","      <td>186.8</td>\n","      <td>55.9</td>\n","      <td>214.7</td>\n","      <td>33.0</td>\n","      <td>13.18</td>\n","      <td>5.97</td>\n","      <td>67635</td>\n","      <td>13.0</td>\n","      <td>51247</td>\n","      <td>9330553</td>\n","      <td>539630</td>\n","      <td>206</td>\n","      <td>58</td>\n","      <td>1.824896e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Pinellas County</th>\n","      <td>113.5</td>\n","      <td>24.6</td>\n","      <td>242.0</td>\n","      <td>63.9</td>\n","      <td>231.7</td>\n","      <td>42.9</td>\n","      <td>5.85</td>\n","      <td>4.32</td>\n","      <td>115990</td>\n","      <td>12.2</td>\n","      <td>51488</td>\n","      <td>44125945</td>\n","      <td>975280</td>\n","      <td>730</td>\n","      <td>159</td>\n","      <td>5.632790e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Polk County</th>\n","      <td>77.5</td>\n","      <td>33.5</td>\n","      <td>165.8</td>\n","      <td>55.9</td>\n","      <td>157.9</td>\n","      <td>36.9</td>\n","      <td>8.06</td>\n","      <td>6.21</td>\n","      <td>107844</td>\n","      <td>16.1</td>\n","      <td>48328</td>\n","      <td>20779632</td>\n","      <td>708009</td>\n","      <td>524</td>\n","      <td>116</td>\n","      <td>4.351088e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Putnam County</th>\n","      <td>160.0</td>\n","      <td>35.5</td>\n","      <td>205.8</td>\n","      <td>62.0</td>\n","      <td>254.7</td>\n","      <td>45.1</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>18954</td>\n","      <td>26.3</td>\n","      <td>34390</td>\n","      <td>1925314</td>\n","      <td>74163</td>\n","      <td>16</td>\n","      <td>4</td>\n","      <td>1.110617e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Sarasota County</th>\n","      <td>160.0</td>\n","      <td>35.5</td>\n","      <td>205.8</td>\n","      <td>62.0</td>\n","      <td>254.7</td>\n","      <td>45.1</td>\n","      <td>9.21</td>\n","      <td>7.06</td>\n","      <td>20118</td>\n","      <td>8.3</td>\n","      <td>77022</td>\n","      <td>7313073</td>\n","      <td>254261</td>\n","      <td>243</td>\n","      <td>68</td>\n","      <td>1.306549e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Seminole County</th>\n","      <td>107.0</td>\n","      <td>24.0</td>\n","      <td>251.2</td>\n","      <td>76.9</td>\n","      <td>240.5</td>\n","      <td>49.9</td>\n","      <td>16.32</td>\n","      <td>9.43</td>\n","      <td>39839</td>\n","      <td>12.8</td>\n","      <td>49995</td>\n","      <td>7030683</td>\n","      <td>321128</td>\n","      <td>331</td>\n","      <td>81</td>\n","      <td>2.173058e+07</td>\n","    </tr>\n","    <tr>\n","      <th>St. Johns County</th>\n","      <td>116.2</td>\n","      <td>25.2</td>\n","      <td>240.8</td>\n","      <td>55.9</td>\n","      <td>234.3</td>\n","      <td>42.0</td>\n","      <td>7.08</td>\n","      <td>5.71</td>\n","      <td>38065</td>\n","      <td>9.2</td>\n","      <td>58423</td>\n","      <td>15773229</td>\n","      <td>426718</td>\n","      <td>154</td>\n","      <td>34</td>\n","      <td>1.862228e+07</td>\n","    </tr>\n","    <tr>\n","      <th>St. Lucie County</th>\n","      <td>107.8</td>\n","      <td>25.9</td>\n","      <td>219.3</td>\n","      <td>61.0</td>\n","      <td>251.1</td>\n","      <td>44.1</td>\n","      <td>11.28</td>\n","      <td>9.24</td>\n","      <td>51321</td>\n","      <td>11.2</td>\n","      <td>63865</td>\n","      <td>17902542</td>\n","      <td>467832</td>\n","      <td>112</td>\n","      <td>32</td>\n","      <td>2.350643e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Sumter County</th>\n","      <td>101.7</td>\n","      <td>25.4</td>\n","      <td>248.1</td>\n","      <td>60.0</td>\n","      <td>206.4</td>\n","      <td>36.9</td>\n","      <td>10.51</td>\n","      <td>8.05</td>\n","      <td>10672</td>\n","      <td>9.1</td>\n","      <td>57931</td>\n","      <td>2312425</td>\n","      <td>128754</td>\n","      <td>21</td>\n","      <td>7</td>\n","      <td>3.424526e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Suwannee County</th>\n","      <td>57.7</td>\n","      <td>17.0</td>\n","      <td>135.9</td>\n","      <td>32.1</td>\n","      <td>132.8</td>\n","      <td>20.0</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>8299</td>\n","      <td>20.3</td>\n","      <td>44144</td>\n","      <td>851332</td>\n","      <td>44191</td>\n","      <td>12</td>\n","      <td>4</td>\n","      <td>2.045323e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Union County</th>\n","      <td>87.2</td>\n","      <td>21.4</td>\n","      <td>173.0</td>\n","      <td>53.0</td>\n","      <td>186.8</td>\n","      <td>35.0</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>2291</td>\n","      <td>22.2</td>\n","      <td>47373</td>\n","      <td>341763</td>\n","      <td>14940</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>5.774985e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Volusia County</th>\n","      <td>62.6</td>\n","      <td>21.6</td>\n","      <td>148.1</td>\n","      <td>55.0</td>\n","      <td>147.0</td>\n","      <td>35.0</td>\n","      <td>8.66</td>\n","      <td>4.66</td>\n","      <td>79877</td>\n","      <td>15.2</td>\n","      <td>46911</td>\n","      <td>14864234</td>\n","      <td>547538</td>\n","      <td>266</td>\n","      <td>51</td>\n","      <td>3.782572e+07</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                     wind_total  wind_peak  ...  twt_peak           dmg\n","county                                      ...                        \n","Alachua County             87.2       21.4  ...        39  9.306765e+06\n","Baker County               81.0       18.6  ...         1  1.360526e+06\n","Bradford County            87.2       21.4  ...         1  3.246248e+06\n","Brevard County            130.9       28.7  ...        71  3.192891e+07\n","Broward County            128.2       31.7  ...       382  1.329551e+08\n","Charlotte County          112.1       24.9  ...        20  6.625988e+06\n","Citrus County             103.3       28.8  ...        13  5.568339e+06\n","Clay County                81.0       18.6  ...         8  1.219590e+07\n","Collier County             41.5       12.1  ...        63  6.194133e+07\n","Columbia County            87.2       21.4  ...         4  3.225476e+06\n","DeSoto County             112.1       24.9  ...         2  4.049290e+06\n","Dixie County               96.2       26.8  ...         5  9.079057e+05\n","Duval County              143.0       29.3  ...       137  4.740938e+07\n","Flagler County            116.3       23.5  ...        16  7.243310e+06\n","Gilchrist County           96.2       26.8  ...         1  6.418368e+05\n","Glades County              77.1       22.1  ...         2  1.684916e+06\n","Hamilton County            57.7       17.0  ...         3  7.796505e+05\n","Hardee County             100.2       25.9  ...         3  6.791781e+06\n","Hendry County             115.1       27.8  ...         1  4.864095e+06\n","Hernando County           103.3       28.8  ...        12  6.987439e+06\n","Highlands County          100.2       25.9  ...        16  1.104181e+07\n","Hillsborough County        42.3       13.5  ...       234  4.139342e+07\n","Indian River County       107.0       24.0  ...        23  5.417251e+06\n","Lafayette County           57.7       17.0  ...         1  4.387254e+05\n","Lake County               101.7       25.4  ...        47  1.418739e+07\n","Lee County                101.2       22.7  ...        63  6.269670e+07\n","Levy County                96.2       26.8  ...         2  1.823098e+06\n","Manatee County            116.2       25.2  ...        33  1.369299e+07\n","Marion County              60.5       22.0  ...        30  1.934269e+07\n","Martin County             101.2       13.7  ...        22  2.936391e+06\n","Miami-Dade County         129.6       28.7  ...       730  2.417464e+08\n","Monroe County             129.6       28.7  ...        31  1.061900e+08\n","Nassau County             115.8       28.5  ...        16  4.184525e+06\n","Okeechobee County          77.1       22.1  ...         2  2.920370e+06\n","Orange County             107.1       25.5  ...       346  5.216380e+07\n","Osceola County            115.5       29.9  ...        50  1.244058e+07\n","Palm Beach County         145.0       31.0  ...       167  8.307278e+07\n","Pasco County              103.3       28.8  ...        58  1.824896e+07\n","Pinellas County           113.5       24.6  ...       159  5.632790e+07\n","Polk County                77.5       33.5  ...       116  4.351088e+07\n","Putnam County             160.0       35.5  ...         4  1.110617e+07\n","Sarasota County           160.0       35.5  ...        68  1.306549e+07\n","Seminole County           107.0       24.0  ...        81  2.173058e+07\n","St. Johns County          116.2       25.2  ...        34  1.862228e+07\n","St. Lucie County          107.8       25.9  ...        32  2.350643e+07\n","Sumter County             101.7       25.4  ...         7  3.424526e+06\n","Suwannee County            57.7       17.0  ...         4  2.045323e+06\n","Union County               87.2       21.4  ...         3  5.774985e+05\n","Volusia County             62.6       21.6  ...        51  3.782572e+07\n","\n","[49 rows x 16 columns]"]},"metadata":{"tags":[]},"execution_count":1}]},{"cell_type":"markdown","metadata":{"id":"Fg-Ticrhdpih"},"source":["## Feature Selection\n","\n","We have 15 features, but do we really need them all? Especially when we only have 49 data points. Intuitively, some of these parameters should be redundant; 6 wind parameters surely can be summarized by just one parameter. The following heatmap illustrates this intuition well."]},{"cell_type":"code","metadata":{"id":"B-5M2buOeaQV","executionInfo":{"status":"ok","timestamp":1603527193659,"user_tz":240,"elapsed":2303,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"966b48be-4726-448f-c8f8-799007ce543c","colab":{"base_uri":"https://localhost:8080/","height":508}},"source":["plt.figure(figsize=(12,7))\n","sns.heatmap(df.corr(),\n","            annot=True,\n","            fmt = '.2f',\n","            cmap='coolwarm')\n","plt.show()"],"execution_count":2,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 864x504 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"SWRPvSoZQ341"},"source":["We can see clusters of highly correlated parameters, such as gust and max wind, or GDP, population, poverty population, and Twitter activity (i.e. parameters that scale with population). Let's find these redundancies quantitivately. Specifically, we will use **Variance Inflation Factor (VIF)**. The VIF of an independent variable is a measure of how much its variation can be attributed to other independent variables. The higher it is, the more redundant the (not so) independent variable is. VIF is calculated as follows:\n","\n","$$ VIF = \\frac{1}{1 - R^2_i} $$\n","\n","where $R_i^2$ is the $R^2$ of the multilinear regression model of the $i^{\\text{th}}$ independent variable using the other independent variables as predictors. Why not just use $R^2_i$ to measure redundancy? One intuition is that the inverse relationship will harshly penalize smaller and smaller values of $1 - R^2_i$ (the so-called **tolerance**).\n","\n","We will loop through the independent variables, construct a multilinear regressor for each one, and compute and collect the VIF's. Standard practice is to discard predictors with VIF's over 10. 5 is used sometimes too, and we'll try both threshholds and see how well they filter out our data in the models."]},{"cell_type":"code","metadata":{"id":"nnUg2sP6-DIk","executionInfo":{"status":"ok","timestamp":1603527193662,"user_tz":240,"elapsed":2289,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"57295083-34c5-44fb-dc11-c1b5c2d939ea","colab":{"base_uri":"https://localhost:8080/","height":284}},"source":["from sklearn.linear_model import LinearRegression\n","from sklearn.preprocessing import robust_scale\n","\n","# preprocess data\n","features = df.drop(labels = ['dmg'], axis = 1).columns\n","X = df[features].apply(robust_scale)\n","Y = robust_scale(df['dmg']) # get a weird error if I try .apply\n","\n","vif_dict = {}\n","# run linear regression for each feature and calculate VIF\n","for feature in features:\n","    X_i = X.drop(labels = [feature], axis = 1)\n","    Y_i = X[feature]\n","    reg = LinearRegression()\n","    reg.fit(X_i, Y_i)\n","    r2 = reg.score(X_i, Y_i)\n","    vif = 1. / (1 - r2)\n","    vif_dict[feature] = vif\n","vif_dict"],"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'gdp': 52.9500797270263,\n"," 'gust_peak': 12.338585234562844,\n"," 'gust_total': 7.567335957063809,\n"," 'maxwind_peak': 20.868875746207838,\n"," 'maxwind_total': 19.164251074726092,\n"," 'mhi': 5.406652921497213,\n"," 'population': 160.54620481443504,\n"," 'poverty_pop': 151.20740399956702,\n"," 'poverty_rate': 5.049258457172382,\n"," 'precip_peak': 16.206418387213727,\n"," 'precip_total': 16.29621857409362,\n"," 'twt_peak': 276.13105651634396,\n"," 'twt_total': 252.13557403271057,\n"," 'wind_peak': 4.817369273234568,\n"," 'wind_total': 8.387395886294627}"]},"metadata":{"tags":[]},"execution_count":3}]},{"cell_type":"code","metadata":{"id":"vbIlotUwTksT","executionInfo":{"status":"ok","timestamp":1603527193666,"user_tz":240,"elapsed":2279,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"fd16bb89-6474-4093-9a44-184dbf78bb7c","colab":{"base_uri":"https://localhost:8080/","height":141}},"source":["vif_s = pd.Series(data = list(vif_dict.values()),\n","                  index = list(vif_dict.keys()))\n","print(\"Variables with VIF less than 10:\")\n","vif_s[vif_s < 10]"],"execution_count":4,"outputs":[{"output_type":"stream","text":["Variables with VIF less than 10:\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["wind_total      8.387396\n","wind_peak       4.817369\n","gust_total      7.567336\n","poverty_rate    5.049258\n","mhi             5.406653\n","dtype: float64"]},"metadata":{"tags":[]},"execution_count":4}]},{"cell_type":"markdown","metadata":{"id":"jFmHET7jZGLm"},"source":["So... using a tolerance of 10, the VIF test says we should use three wind variables, poverty rate, and mhi (the last two being strongly correlated with each other; see heat map). This does not look like it will work out well. Let's see:"]},{"cell_type":"code","metadata":{"id":"0ONf_rgoZhOS","executionInfo":{"status":"ok","timestamp":1603527193670,"user_tz":240,"elapsed":2271,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"17e077fb-ecdf-41b8-a467-3240fb71b03e","colab":{"base_uri":"https://localhost:8080/","height":35}},"source":["from sklearn.model_selection import cross_validate\n","\n","vif_features = vif_s[vif_s < 10].index.values\n","\n","reg = LinearRegression()\n","cv_scores = cross_validate(reg,\n","                           X[vif_features], Y,\n","                           scoring = 'r2',\n","                           cv = 5)\n","best_score = np.max(cv_scores['test_score'])\n","print('Best CV r2: %.2f' % best_score)"],"execution_count":5,"outputs":[{"output_type":"stream","text":["Best CV r2: 0.25\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"M7zFHveFb8GG"},"source":["By using only `wind_total`, `wind_peak`, `gust_total`, `povery_rate`, and `mhi`, the best $R^2$ from 5-fold cross-validation was 0.25. Not so hot. Let's rethink the multicollinearity problem. Looking back at the heat map,there's 4 distinct clusters:\n","\n","- Wind: `wind_total`, `wind_peak`, `gust_total`, `gust_peak`, `maxwind_total`, `maxwind_peak`\n","- Precipitation: `precip_total`, `precip_peak`\n","- Socioeconomic: `poverty_rate`, `mhi`\n","- Population: `poverty_pop`, `gdp`, `population`, `twt_total`, `twt_peak`\n","\n","Looking back at this I wonder two things:\n","\n","1. Why are there so many wind features?\n","2. Why the sum of wind features?\n","\n","The answer to #1 is actually easy: I don't know which one of average winds, gusts (i.e. sudden, fast winds), and maximum sustained winds (i.e. the highest average wind speed that is sustained over 1-minute intervals) is the best predictor for hurricane damages. But in retrospect, the popular Saffir-Simpson scale for classifying hurricanes in the US uses maximum sustained wind speed, so I should just use that.\n","\n","For #2, this is a good question. There's really no good reason, physically or analytically, to use the sum. What does the sum of average winds over a time period represent? The distance wind travelled? That doesn't seem physically significant. Furthermore, not every county has the same amount of samples of wind data, so I can't even say that it's a proxy of averages.\n","\n","So, the next step right now will be to look back at the weather data and\n","\n","- Remove `wind_` and `gust_` features.\n","- Replace `maxwind_total` with `maxwind_mean`"]}]}
\ No newline at end of file
+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"irma_modeling.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true,"mount_file_id":"1Q4J-Du4O02VX-aMhBgnqA8CcQVFolx1x","authorship_tag":"ABX9TyPO/sXn6d3j8rTj+S49aF7/"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"dpQIA2trCnVq"},"source":["# Hurricane Irma Damage Assessment Modeling\n","\n","In this notebook we develop a multilinear and decision tree model to assess damages from hurricane Irma.\n","\n","Our dataset consists of weather, socioeconomic, and Twitter parameters from 49 counties in Florida during Irma. The dependent variable is the amount of federal aid from FEMA that a county received, `dmg`."]},{"cell_type":"code","metadata":{"id":"ShFs31gOCjKO","executionInfo":{"status":"ok","timestamp":1603605566570,"user_tz":240,"elapsed":1032,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"2c6c1ef5-6a1e-4237-e7dd-8b113aecf266","colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["%cd '/content/drive/My Drive/Colab Notebooks/disaster_assessment/irma_modeling'\n","\n","import pandas as pd\n","import numpy as np\n","from matplotlib import pyplot as plt\n","import seaborn as sns; sns.set()\n","\n","df = pd.read_csv('irma.csv')\n","df.set_index(keys='county',inplace=True)\n","df"],"execution_count":1,"outputs":[{"output_type":"stream","text":["/content/drive/My Drive/Colab Notebooks/disaster_assessment/irma_modeling\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>maxwind_mean</th>\n","      <th>maxwind_peak</th>\n","      <th>precip_total</th>\n","      <th>precip_peak</th>\n","      <th>mhi</th>\n","      <th>poverty_rate</th>\n","      <th>poverty_pop</th>\n","      <th>population</th>\n","      <th>gdp</th>\n","      <th>twt_total</th>\n","      <th>twt_peak</th>\n","      <th>dmg</th>\n","    </tr>\n","    <tr>\n","      <th>county</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Alachua County</th>\n","      <td>12.453333</td>\n","      <td>35.0</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>45230</td>\n","      <td>21.2</td>\n","      <td>53816</td>\n","      <td>269956</td>\n","      <td>11912080</td>\n","      <td>182</td>\n","      <td>39</td>\n","      <td>9.306765e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Baker County</th>\n","      <td>10.200000</td>\n","      <td>24.1</td>\n","      <td>9.21</td>\n","      <td>7.06</td>\n","      <td>51856</td>\n","      <td>15.3</td>\n","      <td>3900</td>\n","      <td>28355</td>\n","      <td>472948</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1.360526e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Bradford County</th>\n","      <td>12.453333</td>\n","      <td>35.0</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>44997</td>\n","      <td>19.1</td>\n","      <td>4533</td>\n","      <td>27732</td>\n","      <td>532487</td>\n","      <td>4</td>\n","      <td>1</td>\n","      <td>3.246248e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Brevard County</th>\n","      <td>14.900000</td>\n","      <td>41.0</td>\n","      <td>4.69</td>\n","      <td>2.25</td>\n","      <td>52596</td>\n","      <td>12.4</td>\n","      <td>72303</td>\n","      <td>596849</td>\n","      <td>20453753</td>\n","      <td>354</td>\n","      <td>71</td>\n","      <td>3.192891e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Broward County</th>\n","      <td>15.680000</td>\n","      <td>49.0</td>\n","      <td>10.44</td>\n","      <td>4.11</td>\n","      <td>56702</td>\n","      <td>13.1</td>\n","      <td>252288</td>\n","      <td>1951260</td>\n","      <td>96591919</td>\n","      <td>2036</td>\n","      <td>382</td>\n","      <td>1.329551e+08</td>\n","    </tr>\n","    <tr>\n","      <th>Charlotte County</th>\n","      <td>17.666667</td>\n","      <td>44.1</td>\n","      <td>1.69</td>\n","      <td>0.76</td>\n","      <td>51583</td>\n","      <td>10.8</td>\n","      <td>19300</td>\n","      <td>184998</td>\n","      <td>3966314</td>\n","      <td>72</td>\n","      <td>20</td>\n","      <td>6.625988e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Citrus County</th>\n","      <td>14.313333</td>\n","      <td>33.0</td>\n","      <td>13.18</td>\n","      <td>5.97</td>\n","      <td>43147</td>\n","      <td>14.4</td>\n","      <td>20654</td>\n","      <td>147929</td>\n","      <td>3335110</td>\n","      <td>67</td>\n","      <td>13</td>\n","      <td>5.568339e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Clay County</th>\n","      <td>10.200000</td>\n","      <td>24.1</td>\n","      <td>9.21</td>\n","      <td>7.06</td>\n","      <td>65375</td>\n","      <td>9.9</td>\n","      <td>20889</td>\n","      <td>216072</td>\n","      <td>3976007</td>\n","      <td>53</td>\n","      <td>8</td>\n","      <td>1.219590e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Collier County</th>\n","      <td>18.866667</td>\n","      <td>63.9</td>\n","      <td>5.12</td>\n","      <td>4.20</td>\n","      <td>66709</td>\n","      <td>11.7</td>\n","      <td>43075</td>\n","      <td>378488</td>\n","      <td>16124953</td>\n","      <td>231</td>\n","      <td>63</td>\n","      <td>6.194133e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Columbia County</th>\n","      <td>12.453333</td>\n","      <td>35.0</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>42097</td>\n","      <td>16.5</td>\n","      <td>10720</td>\n","      <td>70503</td>\n","      <td>1826541</td>\n","      <td>14</td>\n","      <td>4</td>\n","      <td>3.225476e+06</td>\n","    </tr>\n","    <tr>\n","      <th>DeSoto County</th>\n","      <td>17.666667</td>\n","      <td>44.1</td>\n","      <td>1.69</td>\n","      <td>0.76</td>\n","      <td>37342</td>\n","      <td>26.1</td>\n","      <td>8766</td>\n","      <td>37489</td>\n","      <td>735286</td>\n","      <td>5</td>\n","      <td>2</td>\n","      <td>4.049290e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Dixie County</th>\n","      <td>13.393333</td>\n","      <td>35.9</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>38355</td>\n","      <td>24.4</td>\n","      <td>3627</td>\n","      <td>16700</td>\n","      <td>178261</td>\n","      <td>7</td>\n","      <td>5</td>\n","      <td>9.079057e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Duval County</th>\n","      <td>15.626667</td>\n","      <td>42.9</td>\n","      <td>9.21</td>\n","      <td>7.06</td>\n","      <td>52105</td>\n","      <td>15.1</td>\n","      <td>138069</td>\n","      <td>950181</td>\n","      <td>60146765</td>\n","      <td>772</td>\n","      <td>137</td>\n","      <td>4.740938e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Flagler County</th>\n","      <td>15.920000</td>\n","      <td>44.1</td>\n","      <td>8.66</td>\n","      <td>4.66</td>\n","      <td>52713</td>\n","      <td>12.0</td>\n","      <td>13137</td>\n","      <td>112067</td>\n","      <td>1809151</td>\n","      <td>63</td>\n","      <td>16</td>\n","      <td>7.243310e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Gilchrist County</th>\n","      <td>13.393333</td>\n","      <td>35.9</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>42880</td>\n","      <td>16.1</td>\n","      <td>2675</td>\n","      <td>18256</td>\n","      <td>254260</td>\n","      <td>3</td>\n","      <td>1</td>\n","      <td>6.418368e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Glades County</th>\n","      <td>14.053333</td>\n","      <td>40.0</td>\n","      <td>9.96</td>\n","      <td>7.09</td>\n","      <td>42865</td>\n","      <td>18.9</td>\n","      <td>2312</td>\n","      <td>13724</td>\n","      <td>171573</td>\n","      <td>4</td>\n","      <td>2</td>\n","      <td>1.684916e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Hamilton County</th>\n","      <td>11.066667</td>\n","      <td>20.0</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>35262</td>\n","      <td>24.0</td>\n","      <td>2791</td>\n","      <td>14310</td>\n","      <td>377309</td>\n","      <td>5</td>\n","      <td>3</td>\n","      <td>7.796505e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Hardee County</th>\n","      <td>18.146667</td>\n","      <td>54.0</td>\n","      <td>2.63</td>\n","      <td>1.36</td>\n","      <td>40056</td>\n","      <td>23.3</td>\n","      <td>6026</td>\n","      <td>27245</td>\n","      <td>893349</td>\n","      <td>8</td>\n","      <td>3</td>\n","      <td>6.791781e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Hendry County</th>\n","      <td>18.866667</td>\n","      <td>63.9</td>\n","      <td>12.61</td>\n","      <td>8.84</td>\n","      <td>38361</td>\n","      <td>23.9</td>\n","      <td>9525</td>\n","      <td>41556</td>\n","      <td>1241872</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>4.864095e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Hernando County</th>\n","      <td>14.313333</td>\n","      <td>33.0</td>\n","      <td>13.18</td>\n","      <td>5.97</td>\n","      <td>44710</td>\n","      <td>14.0</td>\n","      <td>25773</td>\n","      <td>190865</td>\n","      <td>3031267</td>\n","      <td>43</td>\n","      <td>12</td>\n","      <td>6.987439e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Highlands County</th>\n","      <td>18.146667</td>\n","      <td>54.0</td>\n","      <td>2.63</td>\n","      <td>1.36</td>\n","      <td>37445</td>\n","      <td>19.8</td>\n","      <td>20051</td>\n","      <td>105424</td>\n","      <td>2088782</td>\n","      <td>46</td>\n","      <td>16</td>\n","      <td>1.104181e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Hillsborough County</th>\n","      <td>10.140000</td>\n","      <td>27.0</td>\n","      <td>5.43</td>\n","      <td>4.50</td>\n","      <td>54741</td>\n","      <td>15.5</td>\n","      <td>214442</td>\n","      <td>1436888</td>\n","      <td>77093796</td>\n","      <td>990</td>\n","      <td>234</td>\n","      <td>4.139342e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Indian River County</th>\n","      <td>16.033333</td>\n","      <td>49.9</td>\n","      <td>10.86</td>\n","      <td>8.11</td>\n","      <td>51797</td>\n","      <td>10.6</td>\n","      <td>16249</td>\n","      <td>157413</td>\n","      <td>5001702</td>\n","      <td>79</td>\n","      <td>23</td>\n","      <td>5.417251e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Lafayette County</th>\n","      <td>11.066667</td>\n","      <td>20.0</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>41549</td>\n","      <td>22.7</td>\n","      <td>1579</td>\n","      <td>8732</td>\n","      <td>160614</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>4.387254e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Lake County</th>\n","      <td>13.760000</td>\n","      <td>36.9</td>\n","      <td>10.51</td>\n","      <td>8.05</td>\n","      <td>51429</td>\n","      <td>12.6</td>\n","      <td>43020</td>\n","      <td>356495</td>\n","      <td>7452383</td>\n","      <td>151</td>\n","      <td>47</td>\n","      <td>1.418739e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Lee County</th>\n","      <td>15.206667</td>\n","      <td>49.9</td>\n","      <td>6.08</td>\n","      <td>1.89</td>\n","      <td>54198</td>\n","      <td>11.8</td>\n","      <td>85844</td>\n","      <td>754610</td>\n","      <td>23806704</td>\n","      <td>380</td>\n","      <td>63</td>\n","      <td>6.269670e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Levy County</th>\n","      <td>13.393333</td>\n","      <td>35.9</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>37272</td>\n","      <td>20.8</td>\n","      <td>8329</td>\n","      <td>40770</td>\n","      <td>636701</td>\n","      <td>7</td>\n","      <td>2</td>\n","      <td>1.823098e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Manatee County</th>\n","      <td>15.620000</td>\n","      <td>42.0</td>\n","      <td>7.08</td>\n","      <td>5.71</td>\n","      <td>55189</td>\n","      <td>10.8</td>\n","      <td>41057</td>\n","      <td>394855</td>\n","      <td>11968028</td>\n","      <td>170</td>\n","      <td>33</td>\n","      <td>1.369299e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Marion County</th>\n","      <td>11.150000</td>\n","      <td>32.1</td>\n","      <td>0.44</td>\n","      <td>0.23</td>\n","      <td>43772</td>\n","      <td>16.2</td>\n","      <td>55880</td>\n","      <td>359977</td>\n","      <td>7956019</td>\n","      <td>121</td>\n","      <td>30</td>\n","      <td>1.934269e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Martin County</th>\n","      <td>12.593333</td>\n","      <td>22.0</td>\n","      <td>16.32</td>\n","      <td>9.43</td>\n","      <td>58344</td>\n","      <td>10.9</td>\n","      <td>17002</td>\n","      <td>160912</td>\n","      <td>6533103</td>\n","      <td>85</td>\n","      <td>22</td>\n","      <td>2.936391e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Miami-Dade County</th>\n","      <td>15.900000</td>\n","      <td>42.9</td>\n","      <td>9.33</td>\n","      <td>5.18</td>\n","      <td>49758</td>\n","      <td>16.7</td>\n","      <td>452649</td>\n","      <td>2761581</td>\n","      <td>141734334</td>\n","      <td>4063</td>\n","      <td>730</td>\n","      <td>2.417464e+08</td>\n","    </tr>\n","    <tr>\n","      <th>Monroe County</th>\n","      <td>15.900000</td>\n","      <td>42.9</td>\n","      <td>9.33</td>\n","      <td>5.18</td>\n","      <td>63009</td>\n","      <td>11.8</td>\n","      <td>8963</td>\n","      <td>75027</td>\n","      <td>4097511</td>\n","      <td>158</td>\n","      <td>31</td>\n","      <td>1.061900e+08</td>\n","    </tr>\n","    <tr>\n","      <th>Nassau County</th>\n","      <td>14.566667</td>\n","      <td>42.9</td>\n","      <td>10.05</td>\n","      <td>9.01</td>\n","      <td>70590</td>\n","      <td>9.1</td>\n","      <td>7484</td>\n","      <td>85832</td>\n","      <td>1886261</td>\n","      <td>49</td>\n","      <td>16</td>\n","      <td>4.184525e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Okeechobee County</th>\n","      <td>14.053333</td>\n","      <td>40.0</td>\n","      <td>2.63</td>\n","      <td>1.36</td>\n","      <td>42524</td>\n","      <td>21.8</td>\n","      <td>8415</td>\n","      <td>41537</td>\n","      <td>1021477</td>\n","      <td>7</td>\n","      <td>2</td>\n","      <td>2.920370e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Orange County</th>\n","      <td>16.326667</td>\n","      <td>44.1</td>\n","      <td>10.36</td>\n","      <td>7.48</td>\n","      <td>54021</td>\n","      <td>15.3</td>\n","      <td>201528</td>\n","      <td>1380645</td>\n","      <td>89817807</td>\n","      <td>1794</td>\n","      <td>346</td>\n","      <td>5.216380e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Osceola County</th>\n","      <td>19.046667</td>\n","      <td>49.9</td>\n","      <td>13.43</td>\n","      <td>7.02</td>\n","      <td>49284</td>\n","      <td>14.0</td>\n","      <td>48892</td>\n","      <td>367990</td>\n","      <td>9207981</td>\n","      <td>205</td>\n","      <td>50</td>\n","      <td>1.244058e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Palm Beach County</th>\n","      <td>18.200000</td>\n","      <td>51.1</td>\n","      <td>3.96</td>\n","      <td>1.92</td>\n","      <td>60059</td>\n","      <td>11.8</td>\n","      <td>170868</td>\n","      <td>1485941</td>\n","      <td>76866505</td>\n","      <td>904</td>\n","      <td>167</td>\n","      <td>8.307278e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Pasco County</th>\n","      <td>14.313333</td>\n","      <td>33.0</td>\n","      <td>13.18</td>\n","      <td>5.97</td>\n","      <td>51247</td>\n","      <td>13.0</td>\n","      <td>67635</td>\n","      <td>539630</td>\n","      <td>9330553</td>\n","      <td>206</td>\n","      <td>58</td>\n","      <td>1.824896e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Pinellas County</th>\n","      <td>15.446667</td>\n","      <td>42.9</td>\n","      <td>5.85</td>\n","      <td>4.32</td>\n","      <td>51488</td>\n","      <td>12.2</td>\n","      <td>115990</td>\n","      <td>975280</td>\n","      <td>44125945</td>\n","      <td>730</td>\n","      <td>159</td>\n","      <td>5.632790e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Polk County</th>\n","      <td>17.544444</td>\n","      <td>36.9</td>\n","      <td>8.06</td>\n","      <td>6.21</td>\n","      <td>48328</td>\n","      <td>16.1</td>\n","      <td>107844</td>\n","      <td>708009</td>\n","      <td>20779632</td>\n","      <td>524</td>\n","      <td>116</td>\n","      <td>4.351088e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Putnam County</th>\n","      <td>16.980000</td>\n","      <td>45.1</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>34390</td>\n","      <td>26.3</td>\n","      <td>18954</td>\n","      <td>74163</td>\n","      <td>1925314</td>\n","      <td>16</td>\n","      <td>4</td>\n","      <td>1.110617e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Sarasota County</th>\n","      <td>15.620000</td>\n","      <td>45.1</td>\n","      <td>9.21</td>\n","      <td>7.06</td>\n","      <td>77022</td>\n","      <td>8.3</td>\n","      <td>20118</td>\n","      <td>254261</td>\n","      <td>7313073</td>\n","      <td>243</td>\n","      <td>68</td>\n","      <td>1.306549e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Seminole County</th>\n","      <td>16.740000</td>\n","      <td>49.9</td>\n","      <td>16.32</td>\n","      <td>9.43</td>\n","      <td>49995</td>\n","      <td>12.8</td>\n","      <td>39839</td>\n","      <td>321128</td>\n","      <td>7030683</td>\n","      <td>331</td>\n","      <td>81</td>\n","      <td>2.173058e+07</td>\n","    </tr>\n","    <tr>\n","      <th>St. Johns County</th>\n","      <td>16.980000</td>\n","      <td>42.0</td>\n","      <td>7.08</td>\n","      <td>5.71</td>\n","      <td>58423</td>\n","      <td>9.2</td>\n","      <td>38065</td>\n","      <td>426718</td>\n","      <td>15773229</td>\n","      <td>154</td>\n","      <td>34</td>\n","      <td>1.862228e+07</td>\n","    </tr>\n","    <tr>\n","      <th>St. Lucie County</th>\n","      <td>16.033333</td>\n","      <td>44.1</td>\n","      <td>11.28</td>\n","      <td>9.24</td>\n","      <td>63865</td>\n","      <td>11.2</td>\n","      <td>51321</td>\n","      <td>467832</td>\n","      <td>17902542</td>\n","      <td>112</td>\n","      <td>32</td>\n","      <td>2.350643e+07</td>\n","    </tr>\n","    <tr>\n","      <th>Sumter County</th>\n","      <td>13.760000</td>\n","      <td>36.9</td>\n","      <td>10.51</td>\n","      <td>8.05</td>\n","      <td>57931</td>\n","      <td>9.1</td>\n","      <td>10672</td>\n","      <td>128754</td>\n","      <td>2312425</td>\n","      <td>21</td>\n","      <td>7</td>\n","      <td>3.424526e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Suwannee County</th>\n","      <td>11.066667</td>\n","      <td>20.0</td>\n","      <td>4.39</td>\n","      <td>2.38</td>\n","      <td>44144</td>\n","      <td>20.3</td>\n","      <td>8299</td>\n","      <td>44191</td>\n","      <td>851332</td>\n","      <td>12</td>\n","      <td>4</td>\n","      <td>2.045323e+06</td>\n","    </tr>\n","    <tr>\n","      <th>Union County</th>\n","      <td>12.453333</td>\n","      <td>35.0</td>\n","      <td>18.25</td>\n","      <td>11.39</td>\n","      <td>47373</td>\n","      <td>22.2</td>\n","      <td>2291</td>\n","      <td>14940</td>\n","      <td>341763</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>5.774985e+05</td>\n","    </tr>\n","    <tr>\n","      <th>Volusia County</th>\n","      <td>16.333333</td>\n","      <td>35.0</td>\n","      <td>8.66</td>\n","      <td>4.66</td>\n","      <td>46911</td>\n","      <td>15.2</td>\n","      <td>79877</td>\n","      <td>547538</td>\n","      <td>14864234</td>\n","      <td>266</td>\n","      <td>51</td>\n","      <td>3.782572e+07</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                     maxwind_mean  maxwind_peak  ...  twt_peak           dmg\n","county                                           ...                        \n","Alachua County          12.453333          35.0  ...        39  9.306765e+06\n","Baker County            10.200000          24.1  ...         1  1.360526e+06\n","Bradford County         12.453333          35.0  ...         1  3.246248e+06\n","Brevard County          14.900000          41.0  ...        71  3.192891e+07\n","Broward County          15.680000          49.0  ...       382  1.329551e+08\n","Charlotte County        17.666667          44.1  ...        20  6.625988e+06\n","Citrus County           14.313333          33.0  ...        13  5.568339e+06\n","Clay County             10.200000          24.1  ...         8  1.219590e+07\n","Collier County          18.866667          63.9  ...        63  6.194133e+07\n","Columbia County         12.453333          35.0  ...         4  3.225476e+06\n","DeSoto County           17.666667          44.1  ...         2  4.049290e+06\n","Dixie County            13.393333          35.9  ...         5  9.079057e+05\n","Duval County            15.626667          42.9  ...       137  4.740938e+07\n","Flagler County          15.920000          44.1  ...        16  7.243310e+06\n","Gilchrist County        13.393333          35.9  ...         1  6.418368e+05\n","Glades County           14.053333          40.0  ...         2  1.684916e+06\n","Hamilton County         11.066667          20.0  ...         3  7.796505e+05\n","Hardee County           18.146667          54.0  ...         3  6.791781e+06\n","Hendry County           18.866667          63.9  ...         1  4.864095e+06\n","Hernando County         14.313333          33.0  ...        12  6.987439e+06\n","Highlands County        18.146667          54.0  ...        16  1.104181e+07\n","Hillsborough County     10.140000          27.0  ...       234  4.139342e+07\n","Indian River County     16.033333          49.9  ...        23  5.417251e+06\n","Lafayette County        11.066667          20.0  ...         1  4.387254e+05\n","Lake County             13.760000          36.9  ...        47  1.418739e+07\n","Lee County              15.206667          49.9  ...        63  6.269670e+07\n","Levy County             13.393333          35.9  ...         2  1.823098e+06\n","Manatee County          15.620000          42.0  ...        33  1.369299e+07\n","Marion County           11.150000          32.1  ...        30  1.934269e+07\n","Martin County           12.593333          22.0  ...        22  2.936391e+06\n","Miami-Dade County       15.900000          42.9  ...       730  2.417464e+08\n","Monroe County           15.900000          42.9  ...        31  1.061900e+08\n","Nassau County           14.566667          42.9  ...        16  4.184525e+06\n","Okeechobee County       14.053333          40.0  ...         2  2.920370e+06\n","Orange County           16.326667          44.1  ...       346  5.216380e+07\n","Osceola County          19.046667          49.9  ...        50  1.244058e+07\n","Palm Beach County       18.200000          51.1  ...       167  8.307278e+07\n","Pasco County            14.313333          33.0  ...        58  1.824896e+07\n","Pinellas County         15.446667          42.9  ...       159  5.632790e+07\n","Polk County             17.544444          36.9  ...       116  4.351088e+07\n","Putnam County           16.980000          45.1  ...         4  1.110617e+07\n","Sarasota County         15.620000          45.1  ...        68  1.306549e+07\n","Seminole County         16.740000          49.9  ...        81  2.173058e+07\n","St. Johns County        16.980000          42.0  ...        34  1.862228e+07\n","St. Lucie County        16.033333          44.1  ...        32  2.350643e+07\n","Sumter County           13.760000          36.9  ...         7  3.424526e+06\n","Suwannee County         11.066667          20.0  ...         4  2.045323e+06\n","Union County            12.453333          35.0  ...         3  5.774985e+05\n","Volusia County          16.333333          35.0  ...        51  3.782572e+07\n","\n","[49 rows x 12 columns]"]},"metadata":{"tags":[]},"execution_count":1}]},{"cell_type":"markdown","metadata":{"id":"Fg-Ticrhdpih"},"source":["## Feature Selection\n","\n","We have 11 features, but do we really need them all? Especially when we only have 49 data points. As the following heat map shows, a lot of the variables correlate with each other, forming distinct clusters."]},{"cell_type":"code","metadata":{"id":"B-5M2buOeaQV","executionInfo":{"status":"ok","timestamp":1603605567553,"user_tz":240,"elapsed":1990,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"03ab3528-f9cc-4e71-f9f3-7c6e0c94d69c","colab":{"base_uri":"https://localhost:8080/","height":512}},"source":["plt.figure(figsize=(12,7))\n","sns.heatmap(df.corr(),\n","            annot=True,\n","            fmt = '.2f',\n","            cmap='coolwarm')\n","plt.show()"],"execution_count":2,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 864x504 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"SWRPvSoZQ341"},"source":["We can identify these clusters as follows:\n","\n","- Wind: `maxwind_mean`, `maxwind_peak`\n","- Precipitation: `precip_total`, `precip_peak`\n","- Socioeconomic: `mhi`, `poverty_rate`\n","- Population: `poverty_pop`, `population`, `gdp`, `twt_total`, `twt_peak`\n","\n","Our goal is to predict `dmg`. To avoid high multicollinearity among our predictors, let's simply take one variable from each cluster. We'll pick the ones with the strongest correlation to `dmg`. This gives us `maxwind_peak`, `precip_peak`, `mhi`, `twt_total`.\n","\n","Let's verify that these variables are independent of eacher using **Variance Inflation Factor (VIF)**. The VIF of an independent variable is a measure of how much its variation can be attributed to other independent variables. The higher it is, the more redundant the (not so) independent variable is. VIF is calculated as follows:\n","\n","$$ VIF = \\frac{1}{1 - R^2_i} $$\n","\n","where $R_i^2$ is the $R^2$ of the multilinear regression model of the $i^{\\text{th}}$ independent variable using the other independent variables as predictors. Why not just use $R^2_i$ to measure redundancy? One intuition is that the inverse relationship will harshly penalize smaller and smaller values of $1 - R^2_i$ (the so-called **tolerance**).\n","\n","Let's compute the VIF for each of the four predictors we're using:"]},{"cell_type":"code","metadata":{"id":"nnUg2sP6-DIk","executionInfo":{"status":"ok","timestamp":1603605568034,"user_tz":240,"elapsed":2453,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"e055b869-8298-4a60-e0fd-5f89f120ed63","colab":{"base_uri":"https://localhost:8080/","height":144}},"source":["from sklearn.preprocessing import robust_scale\n","from statsmodels.stats.outliers_influence import variance_inflation_factor as vif\n","import statsmodels.api as sm\n","\n","# preprocess data\n","features = ['maxwind_peak', 'precip_peak', 'mhi', 'twt_total']\n","X = df[features].apply(robust_scale)\n","X_vif = sm.add_constant(X.values) # for the vif func\n","\n","vif_dict = {}\n","for f in features:\n","    idx = features.index(f) # need this for vif func\n","    vif_dict[f] = vif(X_vif, idx)\n","vif_dict"],"execution_count":3,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n","  import pandas.util.testing as tm\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["{'maxwind_peak': 1.1609234512973168,\n"," 'mhi': 1.0514008951220526,\n"," 'precip_peak': 1.0447003684876797,\n"," 'twt_total': 1.097731476287398}"]},"metadata":{"tags":[]},"execution_count":3}]},{"cell_type":"markdown","metadata":{"id":"jFmHET7jZGLm"},"source":["This is good! The typical threshhold for VIF's is 10, sometimes 5. All the VIF's calculated were close to 1, indicating that the variables are very much independent of each other.\n","\n","## Modeling\n","Now that we have settled on our features, let's model our data. We will try out a linear regression and decision tree model and see which comes out best."]},{"cell_type":"code","metadata":{"id":"XHNL9NDLGKy6","executionInfo":{"status":"ok","timestamp":1603605568039,"user_tz":240,"elapsed":2442,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}}},"source":["from sklearn.model_selection import train_test_split\n","\n","Y = robust_scale(df['dmg'])\n","\n","X_train, X_test, Y_train, Y_test = train_test_split(X, Y,\n","                                                    test_size = 0.1,\n","                                                    random_state = 0,\n","                                                    shuffle = True)"],"execution_count":4,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"SpztfD5hGLd1"},"source":["### Linear Regression\n","\n","First, we will run cross validation on linear regressors and find the best performing model."]},{"cell_type":"code","metadata":{"id":"0ONf_rgoZhOS","executionInfo":{"status":"ok","timestamp":1603605568041,"user_tz":240,"elapsed":2429,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"3121c275-e795-4bef-d9e8-792b1a27ddd9","colab":{"base_uri":"https://localhost:8080/","height":195}},"source":["from sklearn.model_selection import cross_validate, KFold\n","from sklearn.linear_model import LinearRegression\n","\n","reg = LinearRegression()\n","kf = KFold(5)\n","cv_scores = cross_validate(reg,\n","                           X_train, Y_train,\n","                           cv = kf,\n","                           scoring = 'r2',\n","                           return_train_score = True,\n","                           return_estimator = True)\n","\n","best_score = np.max(cv_scores['test_score'])\n","best_idx = np.where(cv_scores['test_score'] == best_score)[0][0] # need the [0][0] to get the idx\n","linreg_model = cv_scores['estimator'][best_idx]\n","print('Best CV r2: %.2f' % best_score)\n","cv_scores"],"execution_count":5,"outputs":[{"output_type":"stream","text":["Best CV r2: 0.81\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["{'estimator': (LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False),\n","  LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False),\n","  LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False),\n","  LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False),\n","  LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)),\n"," 'fit_time': array([0.00223398, 0.00137377, 0.00139618, 0.00130749, 0.00127864]),\n"," 'score_time': array([0.00135279, 0.00084329, 0.00083733, 0.00079083, 0.00079751]),\n"," 'test_score': array([-0.17218448, -1.99457306,  0.57294813,  0.81115215,  0.6499881 ]),\n"," 'train_score': array([0.80465442, 0.62029971, 0.54761734, 0.42716121, 0.54831034])}"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"markdown","metadata":{"id":"J4WYVukfMbh2"},"source":["### Decision Tree\n","Now let's find the optimal decision tree model."]},{"cell_type":"code","metadata":{"id":"sS8der1cMoYP","executionInfo":{"status":"ok","timestamp":1603605568050,"user_tz":240,"elapsed":2421,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"2254943f-f274-4d1b-efdc-6a11aa0ac136","colab":{"base_uri":"https://localhost:8080/","height":639}},"source":["from sklearn.tree import DecisionTreeRegressor\n","\n","tree = DecisionTreeRegressor(random_state = 0)\n","\n","cv_scores = cross_validate(tree,\n","                           X_train, Y_train,\n","                           cv = kf,\n","                           scoring = 'r2',\n","                           return_train_score = True,\n","                           return_estimator = True)\n","\n","best_score = np.max(cv_scores['test_score'])\n","best_idx = np.where(cv_scores['test_score'] == best_score)[0][0]\n","dt_model = cv_scores['estimator'][best_idx]\n","print(\"Best CV r2: %.2f\" % best_score)\n","cv_scores"],"execution_count":6,"outputs":[{"output_type":"stream","text":["Best CV r2: 0.82\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["{'estimator': (DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n","                        max_features=None, max_leaf_nodes=None,\n","                        min_impurity_decrease=0.0, min_impurity_split=None,\n","                        min_samples_leaf=1, min_samples_split=2,\n","                        min_weight_fraction_leaf=0.0, presort='deprecated',\n","                        random_state=0, splitter='best'),\n","  DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n","                        max_features=None, max_leaf_nodes=None,\n","                        min_impurity_decrease=0.0, min_impurity_split=None,\n","                        min_samples_leaf=1, min_samples_split=2,\n","                        min_weight_fraction_leaf=0.0, presort='deprecated',\n","                        random_state=0, splitter='best'),\n","  DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n","                        max_features=None, max_leaf_nodes=None,\n","                        min_impurity_decrease=0.0, min_impurity_split=None,\n","                        min_samples_leaf=1, min_samples_split=2,\n","                        min_weight_fraction_leaf=0.0, presort='deprecated',\n","                        random_state=0, splitter='best'),\n","  DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n","                        max_features=None, max_leaf_nodes=None,\n","                        min_impurity_decrease=0.0, min_impurity_split=None,\n","                        min_samples_leaf=1, min_samples_split=2,\n","                        min_weight_fraction_leaf=0.0, presort='deprecated',\n","                        random_state=0, splitter='best'),\n","  DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n","                        max_features=None, max_leaf_nodes=None,\n","                        min_impurity_decrease=0.0, min_impurity_split=None,\n","                        min_samples_leaf=1, min_samples_split=2,\n","                        min_weight_fraction_leaf=0.0, presort='deprecated',\n","                        random_state=0, splitter='best')),\n"," 'fit_time': array([0.00195765, 0.00157475, 0.00157881, 0.00152278, 0.00159955]),\n"," 'score_time': array([0.00102186, 0.00093675, 0.00092006, 0.00089002, 0.00084209]),\n"," 'test_score': array([ 0.25140641, -1.84462954,  0.17624502,  0.82366205,  0.04245883]),\n"," 'train_score': array([1., 1., 1., 1., 1.])}"]},"metadata":{"tags":[]},"execution_count":6}]},{"cell_type":"markdown","metadata":{"id":"g0Jhv1mSQ4gA"},"source":["The decision tree appears to be grossly overfitting, as the last two rows show. The train $R^2$ values are all 1! Let's see how these two models compare on the test set..."]},{"cell_type":"code","metadata":{"id":"cLZDH08SRgyS","executionInfo":{"status":"ok","timestamp":1603605568054,"user_tz":240,"elapsed":2409,"user":{"displayName":"Angel Umana","photoUrl":"","userId":"02017183028986324110"}},"outputId":"1af108b9-1275-4073-d717-065b8ab303fa","colab":{"base_uri":"https://localhost:8080/","height":141}},"source":["linreg_train_score = linreg_model.score(X_train, Y_train)\n","linreg_test_score = linreg_model.score(X_test, Y_test)\n","tree_train_score = dt_model.score(X_train, Y_train)\n","tree_test_score = dt_model.score(X_test, Y_test)\n","\n","print(\"===== Linear Regression r2 Scores =====\")\n","print(\"Train: %.2f\" % linreg_train_score)\n","print(\"Test: %.2f\" % linreg_test_score)\n","print()\n","print(\"===== Decision Tree Regressor r2 Scores =====\")\n","print(\"Train: %.2f\" % tree_train_score)\n","print(\"Test: %.2f\" % tree_test_score)"],"execution_count":7,"outputs":[{"output_type":"stream","text":["===== Linear Regression r2 Scores =====\n","Train: 0.55\n","Test: 0.65\n","\n","===== Decision Tree Regressor r2 Scores =====\n","Train: 0.95\n","Test: 0.50\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"LRrQZPrrTY-j"},"source":["Both models overfit, although the linear regressor less so than the decision tree. The test scores are also modest. What do we do now?\n","\n","Ideas:\n","\n","- Use regularization for linear regression: ridge\n","- Look at the parameters of the dt. Is there anything that looks like it should be tweaked to prevent overfitting? Maybe eg the depth is too large.\n","- Can we use another model? Random forest regression seems like a popular alternative. It will eliminate some of the explainability form DT regression, but should alleviate some of the overfitting."]}]}
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