Impact of storms and severe wheather events across the USA Between 1950 and end of November 2011
Synopsis
The purpose of this report is to describe the impact of storms and severe wheater events across the Unites States of America. Our hypothesis is that many severe events can result in fatalities, injuries, and property damage. So, preventing as many of those events to the extend possible could have major positive impact in the USA communities. To investigate this hypothesis we obtained the data from the National Oceanic and Atmospheric Administration’s (NOAA) storm database. The events in the database start in the year 1950 and end in November 2011. In the earlier years of the database there are generally fewer events recorded, most likely due to a lack of good records. More recent years should be considered more complete.
From these data, we found that the most harmful types of events with respect to population health are…
And across the USA, the types of events with the greatest economic consequences are…
Data Processing
Loading and Processing the Raw Data
First, we read the data from the NOAA storm database, which contains data from year 1950 to end of November 2011.
# read the data from the downloaded bz2 file.
stormdata <- read.table("repdata_data_StormData.csv.bz2", stringsAsFactors=FALSE, sep=",", header = TRUE)Some general preview of the data to undertand its nature and structure.
Total rows (records) in the dataset: 902,297. Total colums(fields): 37
dim(stormdata)## [1] 902297 37Check the first few rows in the dataset
head(stormdata)## STATE__ BGN_DATE BGN_TIME TIME_ZONE COUNTY COUNTYNAME STATE
## 1 1 4/18/1950 0:00:00 0130 CST 97 MOBILE AL
## 2 1 4/18/1950 0:00:00 0145 CST 3 BALDWIN AL
## 3 1 2/20/1951 0:00:00 1600 CST 57 FAYETTE AL
## 4 1 6/8/1951 0:00:00 0900 CST 89 MADISON AL
## 5 1 11/15/1951 0:00:00 1500 CST 43 CULLMAN AL
## 6 1 11/15/1951 0:00:00 2000 CST 77 LAUDERDALE AL
## EVTYPE BGN_RANGE BGN_AZI BGN_LOCATI END_DATE END_TIME COUNTY_END
## 1 TORNADO 0 0
## 2 TORNADO 0 0
## 3 TORNADO 0 0
## 4 TORNADO 0 0
## 5 TORNADO 0 0
## 6 TORNADO 0 0
## COUNTYENDN END_RANGE END_AZI END_LOCATI LENGTH WIDTH F MAG FATALITIES
## 1 NA 0 14.0 100 3 0 0
## 2 NA 0 2.0 150 2 0 0
## 3 NA 0 0.1 123 2 0 0
## 4 NA 0 0.0 100 2 0 0
## 5 NA 0 0.0 150 2 0 0
## 6 NA 0 1.5 177 2 0 0
## INJURIES PROPDMG PROPDMGEXP CROPDMG CROPDMGEXP WFO STATEOFFIC ZONENAMES
## 1 15 25.0 K 0
## 2 0 2.5 K 0
## 3 2 25.0 K 0
## 4 2 2.5 K 0
## 5 2 2.5 K 0
## 6 6 2.5 K 0
## LATITUDE LONGITUDE LATITUDE_E LONGITUDE_ REMARKS REFNUM
## 1 3040 8812 3051 8806 1
## 2 3042 8755 0 0 2
## 3 3340 8742 0 0 3
## 4 3458 8626 0 0 4
## 5 3412 8642 0 0 5
## 6 3450 8748 0 0 6We then check all column names in the dataset to see if there is any changes needed to make it tidy
names(stormdata)## [1] "STATE__" "BGN_DATE" "BGN_TIME" "TIME_ZONE" "COUNTY"
## [6] "COUNTYNAME" "STATE" "EVTYPE" "BGN_RANGE" "BGN_AZI"
## [11] "BGN_LOCATI" "END_DATE" "END_TIME" "COUNTY_END" "COUNTYENDN"
## [16] "END_RANGE" "END_AZI" "END_LOCATI" "LENGTH" "WIDTH"
## [21] "F" "MAG" "FATALITIES" "INJURIES" "PROPDMG"
## [26] "PROPDMGEXP" "CROPDMG" "CROPDMGEXP" "WFO" "STATEOFFIC"
## [31] "ZONENAMES" "LATITUDE" "LONGITUDE" "LATITUDE_E" "LONGITUDE_"
## [36] "REMARKS" "REFNUM"Since the types of events are key to create the main reports, we want to see a list of the distinct events in the dataset
We learn after running the “names()” command that there is a column name: EVTYPE, so we examine it here…We then found that there are 985 unique Even types. However, there are 76 records with the word “Summary” that should be exclude when doing the reports to avoid doubling the results. (See records 689 and onward)
unique(stormdata$EVTYPE)## [1] "TORNADO" "TSTM WIND"
## [3] "HAIL" "FREEZING RAIN"
## [5] "SNOW" "ICE STORM/FLASH FLOOD"
## [7] "SNOW/ICE" "WINTER STORM"
## [9] "HURRICANE OPAL/HIGH WINDS" "THUNDERSTORM WINDS"
## [11] "RECORD COLD" "HURRICANE ERIN"
## [13] "HURRICANE OPAL" "HEAVY RAIN"
## [15] "LIGHTNING" "THUNDERSTORM WIND"
## [17] "DENSE FOG" "RIP CURRENT"
## [19] "THUNDERSTORM WINS" "FLASH FLOOD"
## [21] "FLASH FLOODING" "HIGH WINDS"
## [23] "FUNNEL CLOUD" "TORNADO F0"
## [25] "THUNDERSTORM WINDS LIGHTNING" "THUNDERSTORM WINDS/HAIL"
## [27] "HEAT" "WIND"
## [29] "LIGHTING" "HEAVY RAINS"
## [31] "LIGHTNING AND HEAVY RAIN" "FUNNEL"
## [33] "WALL CLOUD" "FLOODING"
## [35] "THUNDERSTORM WINDS HAIL" "FLOOD"
## [37] "COLD" "HEAVY RAIN/LIGHTNING"
## [39] "FLASH FLOODING/THUNDERSTORM WI" "WALL CLOUD/FUNNEL CLOUD"
## [41] "THUNDERSTORM" "WATERSPOUT"
## [43] "EXTREME COLD" "HAIL 1.75)"
## [45] "LIGHTNING/HEAVY RAIN" "HIGH WIND"
## [47] "BLIZZARD" "BLIZZARD WEATHER"
## [49] "WIND CHILL" "BREAKUP FLOODING"
## [51] "HIGH WIND/BLIZZARD" "RIVER FLOOD"
## [53] "HEAVY SNOW" "FREEZE"
## [55] "COASTAL FLOOD" "HIGH WIND AND HIGH TIDES"
## [57] "HIGH WIND/BLIZZARD/FREEZING RA" "HIGH TIDES"
## [59] "HIGH WIND AND HEAVY SNOW" "RECORD COLD AND HIGH WIND"
## [61] "RECORD HIGH TEMPERATURE" "RECORD HIGH"
## [63] "HIGH WINDS HEAVY RAINS" "HIGH WIND/ BLIZZARD"
## [65] "ICE STORM" "BLIZZARD/HIGH WIND"
## [67] "HIGH WIND/LOW WIND CHILL" "HEAVY SNOW/HIGH"
## [69] "RECORD LOW" "HIGH WINDS AND WIND CHILL"
## [71] "HEAVY SNOW/HIGH WINDS/FREEZING" "LOW TEMPERATURE RECORD"
## [73] "AVALANCHE" "MARINE MISHAP"
## [75] "WIND CHILL/HIGH WIND" "HIGH WIND/WIND CHILL/BLIZZARD"
## [77] "HIGH WIND/WIND CHILL" "HIGH WIND/HEAVY SNOW"
## [79] "HIGH TEMPERATURE RECORD" "FLOOD WATCH/"
## [81] "RECORD HIGH TEMPERATURES" "HIGH WIND/SEAS"
## [83] "HIGH WINDS/HEAVY RAIN" "HIGH SEAS"
## [85] "SEVERE TURBULENCE" "RECORD RAINFALL"
## [87] "RECORD SNOWFALL" "RECORD WARMTH"
## [89] "HEAVY SNOW/WIND" "EXTREME HEAT"
## [91] "WIND DAMAGE" "DUST STORM"
## [93] "APACHE COUNTY" "SLEET"
## [95] "HAIL STORM" "FUNNEL CLOUDS"
## [97] "FLASH FLOODS" "DUST DEVIL"
## [99] "EXCESSIVE HEAT" "THUNDERSTORM WINDS/FUNNEL CLOU"
## [101] "WINTER STORM/HIGH WIND" "WINTER STORM/HIGH WINDS"
## [103] "GUSTY WINDS" "STRONG WINDS"
## [105] "FLOODING/HEAVY RAIN" "SNOW AND WIND"
## [107] "HEAVY SURF COASTAL FLOODING" "HEAVY SURF"
## [109] "HEAVY PRECIPATATION" "URBAN FLOODING"
## [111] "HIGH SURF" "BLOWING DUST"
## [113] "URBAN/SMALL" "WILD FIRES"
## [115] "HIGH" "URBAN/SMALL FLOODING"
## [117] "WATER SPOUT" "HIGH WINDS DUST STORM"
## [119] "WINTER STORM HIGH WINDS" "LOCAL FLOOD"
## [121] "WINTER STORMS" "MUDSLIDES"
## [123] "RAINSTORM" "SEVERE THUNDERSTORM"
## [125] "SEVERE THUNDERSTORMS" "SEVERE THUNDERSTORM WINDS"
## [127] "THUNDERSTORMS WINDS" "DRY MICROBURST"
## [129] "FLOOD/FLASH FLOOD" "FLOOD/RAIN/WINDS"
## [131] "WINDS" "DRY MICROBURST 61"
## [133] "THUNDERSTORMS" "FLASH FLOOD WINDS"
## [135] "URBAN/SMALL STREAM FLOODING" "MICROBURST"
## [137] "STRONG WIND" "HIGH WIND DAMAGE"
## [139] "STREAM FLOODING" "URBAN AND SMALL"
## [141] "HEAVY SNOWPACK" "ICE"
## [143] "FLASH FLOOD/" "DOWNBURST"
## [145] "GUSTNADO AND" "FLOOD/RAIN/WIND"
## [147] "WET MICROBURST" "DOWNBURST WINDS"
## [149] "DRY MICROBURST WINDS" "DRY MIRCOBURST WINDS"
## [151] "DRY MICROBURST 53" "SMALL STREAM URBAN FLOOD"
## [153] "MICROBURST WINDS" "HIGH WINDS 57"
## [155] "DRY MICROBURST 50" "HIGH WINDS 66"
## [157] "HIGH WINDS 76" "HIGH WINDS 63"
## [159] "HIGH WINDS 67" "BLIZZARD/HEAVY SNOW"
## [161] "HEAVY SNOW/HIGH WINDS" "BLOWING SNOW"
## [163] "HIGH WINDS 82" "HIGH WINDS 80"
## [165] "HIGH WINDS 58" "FREEZING DRIZZLE"
## [167] "LIGHTNING THUNDERSTORM WINDSS" "DRY MICROBURST 58"
## [169] "HAIL 75" "HIGH WINDS 73"
## [171] "HIGH WINDS 55" "LIGHT SNOW AND SLEET"
## [173] "URBAN FLOOD" "DRY MICROBURST 84"
## [175] "THUNDERSTORM WINDS 60" "HEAVY RAIN/FLOODING"
## [177] "THUNDERSTORM WINDSS" "TORNADOS"
## [179] "GLAZE" "RECORD HEAT"
## [181] "COASTAL FLOODING" "HEAT WAVE"
## [183] "FIRST SNOW" "FREEZING RAIN AND SLEET"
## [185] "UNSEASONABLY DRY" "UNSEASONABLY WET"
## [187] "WINTRY MIX" "WINTER WEATHER"
## [189] "UNSEASONABLY COLD" "EXTREME/RECORD COLD"
## [191] "RIP CURRENTS HEAVY SURF" "SLEET/RAIN/SNOW"
## [193] "UNSEASONABLY WARM" "DROUGHT"
## [195] "NORMAL PRECIPITATION" "HIGH WINDS/FLOODING"
## [197] "DRY" "RAIN/SNOW"
## [199] "SNOW/RAIN/SLEET" "WATERSPOUT/TORNADO"
## [201] "WATERSPOUTS" "WATERSPOUT TORNADO"
## [203] "URBAN/SMALL STREAM FLOOD" "STORM SURGE"
## [205] "WATERSPOUT-TORNADO" "WATERSPOUT-"
## [207] "TORNADOES, TSTM WIND, HAIL" "TROPICAL STORM ALBERTO"
## [209] "TROPICAL STORM" "TROPICAL STORM GORDON"
## [211] "TROPICAL STORM JERRY" "LIGHTNING THUNDERSTORM WINDS"
## [213] "WAYTERSPOUT" "MINOR FLOODING"
## [215] "LIGHTNING INJURY" "URBAN/SMALL STREAM FLOOD"
## [217] "LIGHTNING AND THUNDERSTORM WIN" "THUNDERSTORM WINDS53"
## [219] "URBAN AND SMALL STREAM FLOOD" "URBAN AND SMALL STREAM"
## [221] "WILDFIRE" "DAMAGING FREEZE"
## [223] "THUNDERSTORM WINDS 13" "SMALL HAIL"
## [225] "HEAVY SNOW/HIGH WIND" "HURRICANE"
## [227] "WILD/FOREST FIRE" "SMALL STREAM FLOODING"
## [229] "MUD SLIDE" "LIGNTNING"
## [231] "FROST" "FREEZING RAIN/SNOW"
## [233] "HIGH WINDS/" "THUNDERSNOW"
## [235] "FLOODS" "EXTREME WIND CHILLS"
## [237] "COOL AND WET" "HEAVY RAIN/SNOW"
## [239] "SMALL STREAM AND URBAN FLOODIN" "SMALL STREAM/URBAN FLOOD"
## [241] "SNOW/SLEET/FREEZING RAIN" "SEVERE COLD"
## [243] "GLAZE ICE" "COLD WAVE"
## [245] "EARLY SNOW" "SMALL STREAM AND URBAN FLOOD"
## [247] "HIGH WINDS" "RURAL FLOOD"
## [249] "SMALL STREAM AND" "MUD SLIDES"
## [251] "HAIL 80" "EXTREME WIND CHILL"
## [253] "COLD AND WET CONDITIONS" "EXCESSIVE WETNESS"
## [255] "GRADIENT WINDS" "HEAVY SNOW/BLOWING SNOW"
## [257] "SLEET/ICE STORM" "THUNDERSTORM WINDS URBAN FLOOD"
## [259] "THUNDERSTORM WINDS SMALL STREA" "ROTATING WALL CLOUD"
## [261] "LARGE WALL CLOUD" "COLD AIR FUNNEL"
## [263] "GUSTNADO" "COLD AIR FUNNELS"
## [265] "BLOWING SNOW- EXTREME WIND CHI" "SNOW AND HEAVY SNOW"
## [267] "GROUND BLIZZARD" "MAJOR FLOOD"
## [269] "SNOW/HEAVY SNOW" "FREEZING RAIN/SLEET"
## [271] "ICE JAM FLOODING" "SNOW- HIGH WIND- WIND CHILL"
## [273] "STREET FLOOD" "COLD AIR TORNADO"
## [275] "SMALL STREAM FLOOD" "FOG"
## [277] "THUNDERSTORM WINDS 2" "FUNNEL CLOUD/HAIL"
## [279] "ICE/SNOW" "TSTM WIND 51"
## [281] "TSTM WIND 50" "TSTM WIND 52"
## [283] "TSTM WIND 55" "HEAVY SNOW/BLIZZARD"
## [285] "THUNDERSTORM WINDS 61" "HAIL 0.75"
## [287] "THUNDERSTORM DAMAGE" "THUNDERTORM WINDS"
## [289] "HAIL 1.00" "HAIL/WINDS"
## [291] "SNOW AND ICE" "WIND STORM"
## [293] "SNOWSTORM" "GRASS FIRES"
## [295] "LAKE FLOOD" "PROLONG COLD"
## [297] "HAIL/WIND" "HAIL 1.75"
## [299] "THUNDERSTORMW 50" "WIND/HAIL"
## [301] "SNOW AND ICE STORM" "URBAN AND SMALL STREAM FLOODIN"
## [303] "THUNDERSTORMS WIND" "THUNDERSTORM WINDS"
## [305] "HEAVY SNOW/SLEET" "AGRICULTURAL FREEZE"
## [307] "DROUGHT/EXCESSIVE HEAT" "TUNDERSTORM WIND"
## [309] "TROPICAL STORM DEAN" "THUNDERTSORM WIND"
## [311] "THUNDERSTORM WINDS/ HAIL" "THUNDERSTORM WIND/LIGHTNING"
## [313] "HEAVY RAIN/SEVERE WEATHER" "THUNDESTORM WINDS"
## [315] "WATERSPOUT/ TORNADO" "LIGHTNING."
## [317] "WARM DRY CONDITIONS" "HURRICANE-GENERATED SWELLS"
## [319] "HEAVY SNOW/ICE STORM" "RIVER AND STREAM FLOOD"
## [321] "HIGH WIND 63" "COASTAL SURGE"
## [323] "HEAVY SNOW AND ICE STORM" "MINOR FLOOD"
## [325] "HIGH WINDS/COASTAL FLOOD" "RAIN"
## [327] "RIVER FLOODING" "SNOW/RAIN"
## [329] "ICE FLOES" "HIGH WAVES"
## [331] "SNOW SQUALLS" "SNOW SQUALL"
## [333] "THUNDERSTORM WIND G50" "LIGHTNING FIRE"
## [335] "BLIZZARD/FREEZING RAIN" "HEAVY LAKE SNOW"
## [337] "HEAVY SNOW/FREEZING RAIN" "LAKE EFFECT SNOW"
## [339] "HEAVY WET SNOW" "DUST DEVIL WATERSPOUT"
## [341] "THUNDERSTORM WINDS/HEAVY RAIN" "THUNDERSTROM WINDS"
## [343] "THUNDERSTORM WINDS LE CEN" "HAIL 225"
## [345] "BLIZZARD AND HEAVY SNOW" "HEAVY SNOW AND ICE"
## [347] "ICE STORM AND SNOW" "HEAVY SNOW ANDBLOWING SNOW"
## [349] "HEAVY SNOW/ICE" "BLIZZARD AND EXTREME WIND CHIL"
## [351] "LOW WIND CHILL" "BLOWING SNOW & EXTREME WIND CH"
## [353] "WATERSPOUT/" "URBAN/SMALL STREAM"
## [355] "TORNADO F3" "FUNNEL CLOUD."
## [357] "TORNDAO" "HAIL 0.88"
## [359] "FLOOD/RIVER FLOOD" "MUD SLIDES URBAN FLOODING"
## [361] "TORNADO F1" "THUNDERSTORM WINDS G"
## [363] "DEEP HAIL" "GLAZE/ICE STORM"
## [365] "HEAVY SNOW/WINTER STORM" "AVALANCE"
## [367] "BLIZZARD/WINTER STORM" "DUST STORM/HIGH WINDS"
## [369] "ICE JAM" "FOREST FIRES"
## [371] "THUNDERSTORM WIND G60" "FROST\\FREEZE"
## [373] "THUNDERSTORM WINDS." "HAIL 88"
## [375] "HAIL 175" "HVY RAIN"
## [377] "HAIL 100" "HAIL 150"
## [379] "HAIL 075" "THUNDERSTORM WIND G55"
## [381] "HAIL 125" "THUNDERSTORM WINDS G60"
## [383] "HARD FREEZE" "HAIL 200"
## [385] "THUNDERSTORM WINDS FUNNEL CLOU" "THUNDERSTORM WINDS 62"
## [387] "WILDFIRES" "RECORD HEAT WAVE"
## [389] "HEAVY SNOW AND HIGH WINDS" "HEAVY SNOW/HIGH WINDS & FLOOD"
## [391] "HAIL FLOODING" "THUNDERSTORM WINDS/FLASH FLOOD"
## [393] "HIGH WIND 70" "WET SNOW"
## [395] "HEAVY RAIN AND FLOOD" "LOCAL FLASH FLOOD"
## [397] "THUNDERSTORM WINDS 53" "FLOOD/FLASH FLOODING"
## [399] "TORNADO/WATERSPOUT" "RAIN AND WIND"
## [401] "THUNDERSTORM WIND 59" "THUNDERSTORM WIND 52"
## [403] "COASTAL/TIDAL FLOOD" "SNOW/ICE STORM"
## [405] "BELOW NORMAL PRECIPITATION" "RIP CURRENTS/HEAVY SURF"
## [407] "FLASH FLOOD/FLOOD" "EXCESSIVE RAIN"
## [409] "RECORD/EXCESSIVE HEAT" "HEAT WAVES"
## [411] "LIGHT SNOW" "THUNDERSTORM WIND 69"
## [413] "HAIL DAMAGE" "LIGHTNING DAMAGE"
## [415] "RECORD TEMPERATURES" "LIGHTNING AND WINDS"
## [417] "FOG AND COLD TEMPERATURES" "OTHER"
## [419] "RECORD SNOW" "SNOW/COLD"
## [421] "FLASH FLOOD FROM ICE JAMS" "TSTM WIND G58"
## [423] "MUDSLIDE" "HEAVY SNOW SQUALLS"
## [425] "HEAVY SNOW/SQUALLS" "HEAVY SNOW-SQUALLS"
## [427] "ICY ROADS" "HEAVY MIX"
## [429] "SNOW FREEZING RAIN" "LACK OF SNOW"
## [431] "SNOW/SLEET" "SNOW/FREEZING RAIN"
## [433] "SNOW DROUGHT" "THUNDERSTORMW WINDS"
## [435] "THUNDERSTORM WIND 60 MPH" "THUNDERSTORM WIND 65MPH"
## [437] "THUNDERSTORM WIND/ TREES" "THUNDERSTORM WIND/AWNING"
## [439] "THUNDERSTORM WIND 98 MPH" "THUNDERSTORM WIND TREES"
## [441] "TORRENTIAL RAIN" "TORNADO F2"
## [443] "RIP CURRENTS" "HURRICANE EMILY"
## [445] "HURRICANE GORDON" "HURRICANE FELIX"
## [447] "THUNDERSTORM WIND 59 MPH" "THUNDERSTORM WINDS 63 MPH"
## [449] "THUNDERSTORM WIND/ TREE" "THUNDERSTORM DAMAGE TO"
## [451] "THUNDERSTORM WIND 65 MPH" "FLASH FLOOD - HEAVY RAIN"
## [453] "THUNDERSTORM WIND." "FLASH FLOOD/ STREET"
## [455] "THUNDERSTORM WIND 59 MPH." "HEAVY SNOW FREEZING RAIN"
## [457] "DAM FAILURE" "THUNDERSTORM HAIL"
## [459] "HAIL 088" "THUNDERSTORM WINDSHAIL"
## [461] "LIGHTNING WAUSEON" "THUDERSTORM WINDS"
## [463] "ICE AND SNOW" "RECORD COLD/FROST"
## [465] "STORM FORCE WINDS" "FREEZING RAIN AND SNOW"
## [467] "FREEZING RAIN SLEET AND" "SOUTHEAST"
## [469] "HEAVY SNOW & ICE" "FREEZING DRIZZLE AND FREEZING"
## [471] "THUNDERSTORM WINDS AND" "HAIL/ICY ROADS"
## [473] "FLASH FLOOD/HEAVY RAIN" "HEAVY RAIN; URBAN FLOOD WINDS;"
## [475] "HEAVY PRECIPITATION" "TSTM WIND DAMAGE"
## [477] "HIGH WATER" "FLOOD FLASH"
## [479] "RAIN/WIND" "THUNDERSTORM WINDS 50"
## [481] "THUNDERSTORM WIND G52" "FLOOD FLOOD/FLASH"
## [483] "THUNDERSTORM WINDS 52" "SNOW SHOWERS"
## [485] "THUNDERSTORM WIND G51" "HEAT WAVE DROUGHT"
## [487] "HEAVY SNOW/BLIZZARD/AVALANCHE" "RECORD SNOW/COLD"
## [489] "WET WEATHER" "UNSEASONABLY WARM AND DRY"
## [491] "FREEZING RAIN SLEET AND LIGHT" "RECORD/EXCESSIVE RAINFALL"
## [493] "TIDAL FLOOD" "BEACH EROSIN"
## [495] "THUNDERSTORM WIND G61" "FLOOD/FLASH"
## [497] "LOW TEMPERATURE" "SLEET & FREEZING RAIN"
## [499] "HEAVY RAINS/FLOODING" "THUNDERESTORM WINDS"
## [501] "THUNDERSTORM WINDS/FLOODING" "THUNDEERSTORM WINDS"
## [503] "HIGHWAY FLOODING" "THUNDERSTORM W INDS"
## [505] "HYPOTHERMIA" "FLASH FLOOD/ FLOOD"
## [507] "THUNDERSTORM WIND 50" "THUNERSTORM WINDS"
## [509] "HEAVY RAIN/MUDSLIDES/FLOOD" "MUD/ROCK SLIDE"
## [511] "HIGH WINDS/COLD" "BEACH EROSION/COASTAL FLOOD"
## [513] "COLD/WINDS" "SNOW/ BITTER COLD"
## [515] "THUNDERSTORM WIND 56" "SNOW SLEET"
## [517] "DRY HOT WEATHER" "COLD WEATHER"
## [519] "RAPIDLY RISING WATER" "HAIL ALOFT"
## [521] "EARLY FREEZE" "ICE/STRONG WINDS"
## [523] "EXTREME WIND CHILL/BLOWING SNO" "SNOW/HIGH WINDS"
## [525] "HIGH WINDS/SNOW" "EARLY FROST"
## [527] "SNOWMELT FLOODING" "HEAVY SNOW AND STRONG WINDS"
## [529] "SNOW ACCUMULATION" "BLOWING SNOW/EXTREME WIND CHIL"
## [531] "SNOW/ ICE" "SNOW/BLOWING SNOW"
## [533] "TORNADOES" "THUNDERSTORM WIND/HAIL"
## [535] "FLASH FLOODING/FLOOD" "HAIL 275"
## [537] "HAIL 450" "FLASH FLOOODING"
## [539] "EXCESSIVE RAINFALL" "THUNDERSTORMW"
## [541] "HAILSTORM" "TSTM WINDS"
## [543] "BEACH FLOOD" "HAILSTORMS"
## [545] "TSTMW" "FUNNELS"
## [547] "TSTM WIND 65)" "THUNDERSTORM WINDS/ FLOOD"
## [549] "HEAVY RAINFALL" "HEAT/DROUGHT"
## [551] "HEAT DROUGHT" "NEAR RECORD SNOW"
## [553] "LANDSLIDE" "HIGH WIND AND SEAS"
## [555] "THUNDERSTORMWINDS" "THUNDERSTORM WINDS HEAVY RAIN"
## [557] "SLEET/SNOW" "EXCESSIVE"
## [559] "SNOW/SLEET/RAIN" "WILD/FOREST FIRES"
## [561] "HEAVY SEAS" "DUSTSTORM"
## [563] "FLOOD & HEAVY RAIN" "?"
## [565] "THUNDERSTROM WIND" "FLOOD/FLASHFLOOD"
## [567] "SNOW AND COLD" "HOT PATTERN"
## [569] "PROLONG COLD/SNOW" "BRUSH FIRES"
## [571] "SNOW\\COLD" "WINTER MIX"
## [573] "EXCESSIVE PRECIPITATION" "SNOWFALL RECORD"
## [575] "HOT/DRY PATTERN" "DRY PATTERN"
## [577] "MILD/DRY PATTERN" "MILD PATTERN"
## [579] "LANDSLIDES" "HEAVY SHOWERS"
## [581] "HEAVY SNOW AND" "HIGH WIND 48"
## [583] "LAKE-EFFECT SNOW" "BRUSH FIRE"
## [585] "WATERSPOUT FUNNEL CLOUD" "URBAN SMALL STREAM FLOOD"
## [587] "SAHARAN DUST" "HEAVY SHOWER"
## [589] "URBAN FLOOD LANDSLIDE" "HEAVY SWELLS"
## [591] "URBAN SMALL" "URBAN FLOODS"
## [593] "SMALL STREAM" "HEAVY RAIN/URBAN FLOOD"
## [595] "FLASH FLOOD/LANDSLIDE" "LANDSLIDE/URBAN FLOOD"
## [597] "HEAVY RAIN/SMALL STREAM URBAN" "FLASH FLOOD LANDSLIDES"
## [599] "EXTREME WINDCHILL" "URBAN/SML STREAM FLD"
## [601] "TSTM WIND/HAIL" "Other"
## [603] "Record dry month" "Temperature record"
## [605] "Minor Flooding" "Ice jam flood (minor"
## [607] "High Wind" "Tstm Wind"
## [609] "ROUGH SURF" "Wind"
## [611] "Heavy Surf" "Dust Devil"
## [613] "Wind Damage" "Marine Accident"
## [615] "Snow" "Freeze"
## [617] "Snow Squalls" "Coastal Flooding"
## [619] "Heavy Rain" "Strong Wind"
## [621] "COASTAL STORM" "COASTALFLOOD"
## [623] "Erosion/Cstl Flood" "Heavy Rain and Wind"
## [625] "Light Snow/Flurries" "Wet Month"
## [627] "Wet Year" "Tidal Flooding"
## [629] "River Flooding" "Damaging Freeze"
## [631] "Beach Erosion" "Hot and Dry"
## [633] "Flood/Flash Flood" "Icy Roads"
## [635] "High Surf" "Heavy Rain/High Surf"
## [637] "Thunderstorm Wind" "Rain Damage"
## [639] "Unseasonable Cold" "Early Frost"
## [641] "Wintry Mix" "blowing snow"
## [643] "STREET FLOODING" "Record Cold"
## [645] "Extreme Cold" "Ice Fog"
## [647] "Excessive Cold" "Torrential Rainfall"
## [649] "Freezing Rain" "Landslump"
## [651] "Late-season Snowfall" "Hurricane Edouard"
## [653] "Coastal Storm" "Flood"
## [655] "HEAVY RAIN/WIND" "TIDAL FLOODING"
## [657] "Winter Weather" "Snow squalls"
## [659] "Strong Winds" "Strong winds"
## [661] "RECORD WARM TEMPS." "Ice/Snow"
## [663] "Mudslide" "Glaze"
## [665] "Extended Cold" "Snow Accumulation"
## [667] "Freezing Fog" "Drifting Snow"
## [669] "Whirlwind" "Heavy snow shower"
## [671] "Heavy rain" "LATE SNOW"
## [673] "Record May Snow" "Record Winter Snow"
## [675] "Heavy Precipitation" " COASTAL FLOOD"
## [677] "Record temperature" "Light snow"
## [679] "Late Season Snowfall" "Gusty Wind"
## [681] "small hail" "Light Snow"
## [683] "MIXED PRECIP" "Black Ice"
## [685] "Mudslides" "Gradient wind"
## [687] "Snow and Ice" "Freezing Spray"
## [689] "Summary Jan 17" "Summary of March 14"
## [691] "Summary of March 23" "Summary of March 24"
## [693] "Summary of April 3rd" "Summary of April 12"
## [695] "Summary of April 13" "Summary of April 21"
## [697] "Summary August 11" "Summary of April 27"
## [699] "Summary of May 9-10" "Summary of May 10"
## [701] "Summary of May 13" "Summary of May 14"
## [703] "Summary of May 22 am" "Summary of May 22 pm"
## [705] "Heatburst" "Summary of May 26 am"
## [707] "Summary of May 26 pm" "Metro Storm, May 26"
## [709] "Summary of May 31 am" "Summary of May 31 pm"
## [711] "Summary of June 3" "Summary of June 4"
## [713] "Summary June 5-6" "Summary June 6"
## [715] "Summary of June 11" "Summary of June 12"
## [717] "Summary of June 13" "Summary of June 15"
## [719] "Summary of June 16" "Summary June 18-19"
## [721] "Summary of June 23" "Summary of June 24"
## [723] "Summary of June 30" "Summary of July 2"
## [725] "Summary of July 3" "Summary of July 11"
## [727] "Summary of July 22" "Summary July 23-24"
## [729] "Summary of July 26" "Summary of July 29"
## [731] "Summary of August 1" "Summary August 2-3"
## [733] "Summary August 7" "Summary August 9"
## [735] "Summary August 10" "Summary August 17"
## [737] "Summary August 21" "Summary August 28"
## [739] "Summary September 4" "Summary September 20"
## [741] "Summary September 23" "Summary Sept. 25-26"
## [743] "Summary: Oct. 20-21" "Summary: October 31"
## [745] "Summary: Nov. 6-7" "Summary: Nov. 16"
## [747] "Microburst" "wet micoburst"
## [749] "Hail(0.75)" "Funnel Cloud"
## [751] "Urban Flooding" "No Severe Weather"
## [753] "Urban flood" "Urban Flood"
## [755] "Cold" "Summary of May 22"
## [757] "Summary of June 6" "Summary August 4"
## [759] "Summary of June 10" "Summary of June 18"
## [761] "Summary September 3" "Summary: Sept. 18"
## [763] "Coastal Flood" "coastal flooding"
## [765] "Small Hail" "Record Temperatures"
## [767] "Light Snowfall" "Freezing Drizzle"
## [769] "Gusty wind/rain" "GUSTY WIND/HVY RAIN"
## [771] "Blowing Snow" "Early snowfall"
## [773] "Monthly Snowfall" "Record Heat"
## [775] "Seasonal Snowfall" "Monthly Rainfall"
## [777] "Cold Temperature" "Sml Stream Fld"
## [779] "Heat Wave" "MUDSLIDE/LANDSLIDE"
## [781] "Saharan Dust" "Volcanic Ash"
## [783] "Volcanic Ash Plume" "Thundersnow shower"
## [785] "NONE" "COLD AND SNOW"
## [787] "DAM BREAK" "TSTM WIND (G45)"
## [789] "SLEET/FREEZING RAIN" "BLACK ICE"
## [791] "BLOW-OUT TIDES" "UNSEASONABLY COOL"
## [793] "TSTM HEAVY RAIN" "Gusty Winds"
## [795] "GUSTY WIND" "TSTM WIND 40"
## [797] "TSTM WIND 45" "TSTM WIND (41)"
## [799] "TSTM WIND (G40)" "TSTM WND"
## [801] "Wintry mix" " TSTM WIND"
## [803] "Frost" "Frost/Freeze"
## [805] "RAIN (HEAVY)" "Record Warmth"
## [807] "Prolong Cold" "Cold and Frost"
## [809] "URBAN/SML STREAM FLDG" "STRONG WIND GUST"
## [811] "LATE FREEZE" "BLOW-OUT TIDE"
## [813] "Hypothermia/Exposure" "HYPOTHERMIA/EXPOSURE"
## [815] "Lake Effect Snow" "Mixed Precipitation"
## [817] "Record High" "COASTALSTORM"
## [819] "Snow and sleet" "Freezing rain"
## [821] "Gusty winds" "Blizzard Summary"
## [823] "SUMMARY OF MARCH 24-25" "SUMMARY OF MARCH 27"
## [825] "SUMMARY OF MARCH 29" "GRADIENT WIND"
## [827] "Icestorm/Blizzard" "Flood/Strong Wind"
## [829] "TSTM WIND AND LIGHTNING" "gradient wind"
## [831] "Freezing drizzle" "Mountain Snows"
## [833] "URBAN/SMALL STRM FLDG" "Heavy surf and wind"
## [835] "Mild and Dry Pattern" "COLD AND FROST"
## [837] "TYPHOON" "HIGH SWELLS"
## [839] "HIGH SWELLS" "VOLCANIC ASH"
## [841] "DRY SPELL" " LIGHTNING"
## [843] "BEACH EROSION" "UNSEASONAL RAIN"
## [845] "EARLY RAIN" "PROLONGED RAIN"
## [847] "WINTERY MIX" "COASTAL FLOODING/EROSION"
## [849] "HOT SPELL" "UNSEASONABLY HOT"
## [851] " TSTM WIND (G45)" "TSTM WIND (G45)"
## [853] "HIGH WIND (G40)" "TSTM WIND (G35)"
## [855] "DRY WEATHER" "ABNORMAL WARMTH"
## [857] "UNUSUAL WARMTH" "WAKE LOW WIND"
## [859] "MONTHLY RAINFALL" "COLD TEMPERATURES"
## [861] "COLD WIND CHILL TEMPERATURES" "MODERATE SNOW"
## [863] "MODERATE SNOWFALL" "URBAN/STREET FLOODING"
## [865] "COASTAL EROSION" "UNUSUAL/RECORD WARMTH"
## [867] "BITTER WIND CHILL" "BITTER WIND CHILL TEMPERATURES"
## [869] "SEICHE" "TSTM"
## [871] "COASTAL FLOODING/EROSION" "UNSEASONABLY WARM YEAR"
## [873] "HYPERTHERMIA/EXPOSURE" "ROCK SLIDE"
## [875] "ICE PELLETS" "PATCHY DENSE FOG"
## [877] "RECORD COOL" "RECORD WARM"
## [879] "HOT WEATHER" "RECORD TEMPERATURE"
## [881] "TROPICAL DEPRESSION" "VOLCANIC ERUPTION"
## [883] "COOL SPELL" "WIND ADVISORY"
## [885] "GUSTY WIND/HAIL" "RED FLAG FIRE WX"
## [887] "FIRST FROST" "EXCESSIVELY DRY"
## [889] "SNOW AND SLEET" "LIGHT SNOW/FREEZING PRECIP"
## [891] "VOG" "MONTHLY PRECIPITATION"
## [893] "MONTHLY TEMPERATURE" "RECORD DRYNESS"
## [895] "EXTREME WINDCHILL TEMPERATURES" "MIXED PRECIPITATION"
## [897] "DRY CONDITIONS" "REMNANTS OF FLOYD"
## [899] "EARLY SNOWFALL" "FREEZING FOG"
## [901] "LANDSPOUT" "DRIEST MONTH"
## [903] "RECORD COLD" "LATE SEASON HAIL"
## [905] "EXCESSIVE SNOW" "DRYNESS"
## [907] "FLOOD/FLASH/FLOOD" "WIND AND WAVE"
## [909] "LIGHT FREEZING RAIN" " WIND"
## [911] "MONTHLY SNOWFALL" "RECORD PRECIPITATION"
## [913] "ICE ROADS" "ROUGH SEAS"
## [915] "UNSEASONABLY WARM/WET" "UNSEASONABLY COOL & WET"
## [917] "UNUSUALLY WARM" "TSTM WIND G45"
## [919] "NON SEVERE HAIL" "NON-SEVERE WIND DAMAGE"
## [921] "UNUSUALLY COLD" "WARM WEATHER"
## [923] "LANDSLUMP" "THUNDERSTORM WIND (G40)"
## [925] "UNSEASONABLY WARM & WET" " FLASH FLOOD"
## [927] "LOCALLY HEAVY RAIN" "WIND GUSTS"
## [929] "UNSEASONAL LOW TEMP" "HIGH SURF ADVISORY"
## [931] "LATE SEASON SNOW" "GUSTY LAKE WIND"
## [933] "ABNORMALLY DRY" "WINTER WEATHER MIX"
## [935] "RED FLAG CRITERIA" "WND"
## [937] "CSTL FLOODING/EROSION" "SMOKE"
## [939] " WATERSPOUT" "SNOW ADVISORY"
## [941] "EXTREMELY WET" "UNUSUALLY LATE SNOW"
## [943] "VERY DRY" "RECORD LOW RAINFALL"
## [945] "ROGUE WAVE" "PROLONG WARMTH"
## [947] "ACCUMULATED SNOWFALL" "FALLING SNOW/ICE"
## [949] "DUST DEVEL" "NON-TSTM WIND"
## [951] "NON TSTM WIND" "GUSTY THUNDERSTORM WINDS"
## [953] "PATCHY ICE" "HEAVY RAIN EFFECTS"
## [955] "EXCESSIVE HEAT/DROUGHT" "NORTHERN LIGHTS"
## [957] "MARINE TSTM WIND" " HIGH SURF ADVISORY"
## [959] "HAZARDOUS SURF" "FROST/FREEZE"
## [961] "WINTER WEATHER/MIX" "ASTRONOMICAL HIGH TIDE"
## [963] "WHIRLWIND" "VERY WARM"
## [965] "ABNORMALLY WET" "TORNADO DEBRIS"
## [967] "EXTREME COLD/WIND CHILL" "ICE ON ROAD"
## [969] "DROWNING" "GUSTY THUNDERSTORM WIND"
## [971] "MARINE HAIL" "HIGH SURF ADVISORIES"
## [973] "HURRICANE/TYPHOON" "HEAVY SURF/HIGH SURF"
## [975] "SLEET STORM" "STORM SURGE/TIDE"
## [977] "COLD/WIND CHILL" "MARINE HIGH WIND"
## [979] "TSUNAMI" "DENSE SMOKE"
## [981] "LAKESHORE FLOOD" "MARINE THUNDERSTORM WIND"
## [983] "MARINE STRONG WIND" "ASTRONOMICAL LOW TIDE"
## [985] "VOLCANIC ASHFALL"Appying some data cleansing to the original dataset
Check how many records contain the word “Summary” in the EVTYPE column.
# Find any record where EVTYPE contains the word "Summary"
evtype.withsummary = grepl("*summary*", stormdata$EVTYPE, ignore.case = TRUE)
# See the results
nrow(stormdata[evtype.withsummary==TRUE,c("STATE","EVTYPE")])## [1] 76See some sample records below - showing only the STATE and EVTYPE columns
# First records
head(stormdata[evtype.withsummary==TRUE,c("STATE","EVTYPE")])## STATE EVTYPE
## 269504 OK Summary Jan 17
## 269586 OK Summary of March 14
## 269610 OK Summary of March 23
## 269679 OK Summary of March 24
## 269784 OK Summary of April 3rd
## 269843 OK Summary of April 12# Last records
tail(stormdata[evtype.withsummary==TRUE,c("STATE","EVTYPE")])## STATE EVTYPE
## 277677 TX Summary September 23
## 278098 TX Summary: Nov. 16
## 298058 ND Blizzard Summary
## 299357 OK SUMMARY OF MARCH 24-25
## 299447 OK SUMMARY OF MARCH 27
## 299496 OK SUMMARY OF MARCH 29See dataset excluding any record with the word “summary”" exists in the EVTYPE column
# Create a new dataset with records where "Summary" is not found in the EVTYPE column
stormdatanew = stormdata[evtype.withsummary==FALSE,]Compare original vs modified dataset…
# Original dataset observations
dim(stormdata)## [1] 902297 37# Modified dataset observations
dim(stormdatanew)## [1] 902221 37# See that new dataset now has 76 less records than the original one.See whether there is any field data type that would need to be changed (i.e. chr to factor, chr to date…)
str(stormdatanew)## 'data.frame': 902221 obs. of 37 variables:
## $ STATE__ : num 1 1 1 1 1 1 1 1 1 1 ...
## $ BGN_DATE : chr "4/18/1950 0:00:00" "4/18/1950 0:00:00" "2/20/1951 0:00:00" "6/8/1951 0:00:00" ...
## $ BGN_TIME : chr "0130" "0145" "1600" "0900" ...
## $ TIME_ZONE : chr "CST" "CST" "CST" "CST" ...
## $ COUNTY : num 97 3 57 89 43 77 9 123 125 57 ...
## $ COUNTYNAME: chr "MOBILE" "BALDWIN" "FAYETTE" "MADISON" ...
## $ STATE : chr "AL" "AL" "AL" "AL" ...
## $ EVTYPE : chr "TORNADO" "TORNADO" "TORNADO" "TORNADO" ...
## $ BGN_RANGE : num 0 0 0 0 0 0 0 0 0 0 ...
## $ BGN_AZI : chr "" "" "" "" ...
## $ BGN_LOCATI: chr "" "" "" "" ...
## $ END_DATE : chr "" "" "" "" ...
## $ END_TIME : chr "" "" "" "" ...
## $ COUNTY_END: num 0 0 0 0 0 0 0 0 0 0 ...
## $ COUNTYENDN: logi NA NA NA NA NA NA ...
## $ END_RANGE : num 0 0 0 0 0 0 0 0 0 0 ...
## $ END_AZI : chr "" "" "" "" ...
## $ END_LOCATI: chr "" "" "" "" ...
## $ LENGTH : num 14 2 0.1 0 0 1.5 1.5 0 3.3 2.3 ...
## $ WIDTH : num 100 150 123 100 150 177 33 33 100 100 ...
## $ F : int 3 2 2 2 2 2 2 1 3 3 ...
## $ MAG : num 0 0 0 0 0 0 0 0 0 0 ...
## $ FATALITIES: num 0 0 0 0 0 0 0 0 1 0 ...
## $ INJURIES : num 15 0 2 2 2 6 1 0 14 0 ...
## $ PROPDMG : num 25 2.5 25 2.5 2.5 2.5 2.5 2.5 25 25 ...
## $ PROPDMGEXP: chr "K" "K" "K" "K" ...
## $ CROPDMG : num 0 0 0 0 0 0 0 0 0 0 ...
## $ CROPDMGEXP: chr "" "" "" "" ...
## $ WFO : chr "" "" "" "" ...
## $ STATEOFFIC: chr "" "" "" "" ...
## $ ZONENAMES : chr "" "" "" "" ...
## $ LATITUDE : num 3040 3042 3340 3458 3412 ...
## $ LONGITUDE : num 8812 8755 8742 8626 8642 ...
## $ LATITUDE_E: num 3051 0 0 0 0 ...
## $ LONGITUDE_: num 8806 0 0 0 0 ...
## $ REMARKS : chr "" "" "" "" ...
## $ REFNUM : num 1 2 3 4 5 6 7 8 9 10 ...Review some key columns for the final reports…
# Columns: COUNTY, COUNTYNAME, STATE, EVTYPE, F, MAG, FATALITIES, INJURIES, PROPDMG, PROPDMGEXP, CROPDMG
ds.selected.columns = stormdata[,c(5,6,7,8, 21:25, 26:29, 36)]
# See first few rows...
head(ds.selected.columns)## COUNTY COUNTYNAME STATE EVTYPE F MAG FATALITIES INJURIES PROPDMG
## 1 97 MOBILE AL TORNADO 3 0 0 15 25.0
## 2 3 BALDWIN AL TORNADO 2 0 0 0 2.5
## 3 57 FAYETTE AL TORNADO 2 0 0 2 25.0
## 4 89 MADISON AL TORNADO 2 0 0 2 2.5
## 5 43 CULLMAN AL TORNADO 2 0 0 2 2.5
## 6 77 LAUDERDALE AL TORNADO 2 0 0 6 2.5
## PROPDMGEXP CROPDMG CROPDMGEXP WFO REMARKS
## 1 K 0
## 2 K 0
## 3 K 0
## 4 K 0
## 5 K 0
## 6 K 0Review unique list of values signifying the magnitude of the number (K = thousands, M = millions, B = billions)
# See unique list of values signifying the magnitude of the number
# For Property Damage
unique(stormdatanew$PROPDMGEXP)## [1] "K" "M" "" "B" "m" "+" "0" "5" "6" "?" "4" "2" "3" "h" "7" "H" "-"
## [18] "1" "8"# Total count of unique values to signify magnitude of the number: i.e.
# K = thousands, M = millions, B = billions
length(unique(stormdatanew$PROPDMGEXP))## [1] 19# For CROP Damage
unique(stormdatanew$CROPDMGEXP)## [1] "" "M" "K" "m" "B" "?" "0" "k" "2"# Total count of unique values to signify magnitude of the number: i.e.
# K = thousands, M = millions, B = billions
length(unique(stormdatanew$CROPDMGEXP))## [1] 9From this report, we found that some magnitudes values are in lower case (“m”, “k”). We need to take that into account when running other scripts. That is either ignore cases or update dataset with all capital letters for magnitudes…
Find how many records contain these “undefinded” magnitude: “”, “?” “-” “+” in PROPDMGEXP field and where Property damage > 0
# For CROP
nrow(stormdatanew[stormdatanew$CROPDMGEXP %in% c('','+','-','?') & stormdatanew$CROPDMG > 0 ,])## [1] 3# For Property
nrow(stormdatanew[stormdatanew$PROPDMGEXP %in% c('','+','-','?') & stormdatanew$PROPDMG > 0 ,])## [1] 82Since there are only 3+82 = 85 observations (records) with these “undefined” magnitudes, for this study, we will represent them as “H” for hundreds…
# vectors to create a dataframe for the different magnitudes
#options(digits=15)
#options(scipen=FALSE)
vmagnitude = c(0:8)
vmultiplier =c("1", "10", "100", "1000", "10000", "100000", "1000000", "10000000", "100000000")See the multipliers we will use to calculate the Property and Crop damage in dollars.
dfmag = data.frame(vmagnitude, vmultiplier)
# Display dataframe with magnitudes...
dfmag## vmagnitude vmultiplier
## 1 0 1
## 2 1 10
## 3 2 100
## 4 3 1000
## 5 4 10000
## 6 5 100000
## 7 6 1000000
## 8 7 10000000
## 9 8 100000000We will also use:
#---------------------------------------------
# 100 for "H" and "h" (hundreds)
# 1000 for "K" and "h" (thousands)
# 1000000 for "M" and "m" (millions)
# 1000000000 for "B" and "b" (billions)
#---------------------------------------------Now that we have consistent magnitude symbols across the dataset, we will proceed to add a few new variables for the final reports and plots preparation
# Load the package
#library(sqldf)
## Pending to fix the ifelse to make sure the calculate is done properly...
stormdatanew = transform(stormdatanew,
Prop.Dmg.Dollars = ifelse(PROPDMGEXP == "0", (PROPDMG * (10^0)),
ifelse(PROPDMGEXP == "1", (PROPDMG * (10^1)),
ifelse(PROPDMGEXP %in% c("2","h","H"), (PROPDMG * (10^2)),
ifelse(PROPDMGEXP %in% c("K","k","3"), (PROPDMG * (10^3)),
ifelse(PROPDMGEXP == "4", (PROPDMG * (10^4)),
ifelse(PROPDMGEXP == "5", (PROPDMG * (10^5)),
ifelse(PROPDMGEXP %in% c("M","m","6"), (PROPDMG * (10^6)),
ifelse(PROPDMGEXP == "7", (PROPDMG * (10^7)),
ifelse(PROPDMGEXP == "8", (PROPDMG * (10^8)),
ifelse(PROPDMGEXP %in% c("B","b"), (PROPDMG * (10^9)),
ifelse(PROPDMGEXP %in% c("","?","-","+"), (PROPDMG * (10^2)),
0))))))))))),
Crop.Dmg.Dollars = ifelse(CROPDMGEXP =="0", (CROPDMG * (10^0)),
ifelse(CROPDMGEXP =="1", (CROPDMG * (10^1)),
ifelse(CROPDMGEXP %in% c("2","h","H"), (CROPDMG * (10^2)),
ifelse(CROPDMGEXP %in% c("K","k","3"), (CROPDMG * (10^3)),
ifelse(CROPDMGEXP =="4", (CROPDMG * (10^4)),
ifelse(CROPDMGEXP =="5", (CROPDMG * (10^5)),
ifelse(CROPDMGEXP %in% c("M","m","6"), (CROPDMG * (10^6)),
ifelse(CROPDMGEXP =="7", (CROPDMG * (10^7)),
ifelse(CROPDMGEXP =="8", (CROPDMG * (10^8)),
ifelse(CROPDMGEXP %in% c("B","b"), (CROPDMG * (10^9)),
ifelse(CROPDMGEXP %in% c("","?","-","+"), (CROPDMG * (10^2)),
0)))))))))))
) #End of transformAdd a variable for Total property damage and crop damage in Dollars
stormdatanew = transform(stormdatanew, TotalDmgDollars = Prop.Dmg.Dollars + Crop.Dmg.Dollars)Create summary variables to use in the final results
library("sqldf")
# Calculate Economic impact across USA for the top 25 Event Types
Top10.Economic.Impact.USA = sqldf('select EVTYPE, sum(TotalDmgDollars/1000000) as TotalDamageDollars
from stormdatanew
group by EVTYPE
Order by 2 desc
limit 10')## Loading required package: tcltkTop5.Economic.Impact.State = sqldf('select EVTYPE, STATE, sum(TotalDmgDollars/1000000) as TotalDamageDollars
from stormdatanew
group by EVTYPE, STATE
Order by 3 desc
limit 5')Determine the Top 10 Event Types with the most impact to the Population Health across the USA
library("sqldf")## Loading required package: gsubfn
## Loading required package: proto
## Loading required package: RSQLite
## Loading required package: DBI
## Loading required package: RSQLite.extfunsTop10.PopulationHealth.Impact.USA = sqldf('select EVTYPE, Sum(INJURIES) as INJURIES,
SUM(FATALITIES) AS FATALITIES,
Sum(INJURIES+FATALITIES) as Total_Injuries_Fatalities
from stormdatanew
group by EVTYPE
Order by 4 desc
limit 10')## Loading required package: tcltkDetermine the Top 10 Event Types (by STATE) with the most impact to the Population Health across the USA
library("sqldf")
# Calculate Population Health impact by STATE and Top 10 Event Types across USA
Top10.PopulationHealth.Impact.STATE = sqldf('select EVTYPE, STATE, Sum(INJURIES) as INJURIES,
SUM(FATALITIES) AS FATALITIES,
Sum(INJURIES+FATALITIES) as Total_Injuries_Fatalities
from stormdatanew
group by EVTYPE
Order by 5 desc
limit 10')We are now ready to start reporting the results. We wil use summaries, tables, and graphs…
Results
We will present first some results regarding the Economic consequences of the top 10 Event types across the USA from 1950 to 2011.
Top 10 Property and CROP damage in Dolloars by Event Type across USA (in descending order). See that the first event types had the greatest economic impact.
This summary addresses the question: “Which event type have the greatest economic consequences”
(Figures are in “Millions”)
# Top 10 Event types with the greatest economic impact.
Top10.Economic.Impact.USA## EVTYPE TotalDamageDollars
## 1 FLOOD 150320
## 2 HURRICANE/TYPHOON 71914
## 3 TORNADO 57362
## 4 STORM SURGE 43324
## 5 HAIL 18761
## 6 FLASH FLOOD 18244
## 7 DROUGHT 15019
## 8 HURRICANE 14610
## 9 RIVER FLOOD 10148
## 10 ICE STORM 8967Top 5 Property and CROP damage in Dolloars by Event Type and STATE (across USA) (in descending order). See that the first event types had the greatest economic impact.
(Figures are in “Millions”)
Top5.Economic.Impact.State## EVTYPE STATE TotalDamageDollars
## 1 FLOOD CA 117378
## 2 STORM SURGE LA 31743
## 3 HURRICANE/TYPHOON FL 28552
## 4 HURRICANE/TYPHOON LA 21051
## 5 HURRICANE/TYPHOON MS 15008See some plots with the Top 10 Event Types and Economic impact across USA
The following plot (points) shows the economic impact of the top 10 Event Types across the USA (1950 - 2011)
# Plot for Top 10 Event types with the greatest economic impact.
library(ggplot2)
ggplot(data=Top10.Economic.Impact.USA, aes(y=EVTYPE, x=TotalDamageDollars, stat="identity", colour = EVTYPE)) +
geom_point(size = 5)+
xlab("Damage in Dollars (Millions)") +
ylab("Event Type") +
ggtitle("Top 10 Event Types and Economic Impact in USA (1950 - 2011)") +
scale_color_discrete(name = "Event Type")
The following bar plot shows the economic impact of the top 10 Event Types across the USA (1950 - 2011)
ggplot(data=Top10.Economic.Impact.USA, aes(y=TotalDamageDollars, x=EVTYPE,
colour=EVTYPE, fill=EVTYPE ))+
geom_bar(stat="identity")+
ylab("Damage in Dollars (Millions)") +
xlab("Event Type") +
ggtitle("Top 10 Event Types and Economic Impact in USA (1950 - 2011)") +
theme(axis.text.x = element_text(angle=-45, hjust=0, vjust=1),
plot.title = element_text(size = 15))
Now, let us see the impact to the population heath of these Event Types across the USA from 1950 to 2011.
Top 10 Event Types with the most impact to the Population Health across the USA
Top10.PopulationHealth.Impact.USA## EVTYPE INJURIES FATALITIES Total_Injuries_Fatalities
## 1 TORNADO 91346 5633 96979
## 2 EXCESSIVE HEAT 6525 1903 8428
## 3 TSTM WIND 6957 504 7461
## 4 FLOOD 6789 470 7259
## 5 LIGHTNING 5230 816 6046
## 6 HEAT 2100 937 3037
## 7 FLASH FLOOD 1777 978 2755
## 8 ICE STORM 1975 89 2064
## 9 THUNDERSTORM WIND 1488 133 1621
## 10 WINTER STORM 1321 206 1527Top 10 Event Types (by STATE) with the most impact to the Population Health across the USA
Top10.PopulationHealth.Impact.STATE## EVTYPE STATE INJURIES FATALITIES Total_Injuries_Fatalities
## 1 TORNADO AL 91346 5633 96979
## 2 EXCESSIVE HEAT OK 6525 1903 8428
## 3 TSTM WIND PR 6957 504 7461
## 4 FLOOD KY 6789 470 7259
## 5 LIGHTNING KY 5230 816 6046
## 6 HEAT FL 2100 937 3037
## 7 FLASH FLOOD AS 1777 978 2755
## 8 ICE STORM MT 1975 89 2064
## 9 THUNDERSTORM WIND GA 1488 133 1621
## 10 WINTER STORM AK 1321 206 1527ggplot(data=Top10.PopulationHealth.Impact.USA, aes(y=Total_Injuries_Fatalities, x=EVTYPE,
colour=EVTYPE, fill=EVTYPE ))+
geom_bar(stat="identity")+
ylab("Population Health Impact (# people)") +
xlab("Event Type") +
ggtitle("Top 10 Event Types and Population Health Impact in USA (1950 - 2011)") +
theme(axis.text.x = element_text(angle=-45, hjust=0, vjust=1),
plot.title = element_text(size = 15))
This chart shows the Top 10 Event Types with the most impact to the Population Health across the USA