R Notebook
BRIEF
This document is about exploring and extracting some insights from the Storm Data which is an official publication of National Oceanic and Atmospheric Administration. Across the USA starting from 1950 to 2011 meteorological events are observed with its results such as injuries, fatalities and damages on crops and on properties. We are going to investigate if event types are correlated with damage types.
At first section We will download the data and clean some of it, transform the data, look at columns and group events to have ideas which events are more dangerous for human life and have strong impact on economy. We will compare top events that effects most. We will plot our data to understand better and see relations between events and damages. And we will examine by years and also by seasons of events. This data can be investigated by different points of view. But for more detailed analysis data has to be cleaned very carefully. Especially between 1950-1970 some stats are missing or deployed with personal measurements.
DATA PROCESSING
We will download the data as bz2 zip file format.
url <- "https://d396qusza40orc.cloudfront.net/repdata%2Fdata%2FStormData.csv.bz2"
download.file(url, destfile = "./data.zip")Bzfiles can be read without decompositioning.
data <- read.csv(bzfile("./data.zip"))First we look at structure of our dataset.
str(data)'data.frame': 902297 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 ...And let’s have a look at first rows of the data:
And dimension of data:
dim(data)[1] 902297 37So we have 37 columns and 902297 rows. As we understand from the first impression from the data we have day and time of starting and ending event, place (county), event type (EVTYPE), length and width, force of event (F), fatalities and injuries from the event, damage types, latitude and longitude knowledge. But we have NA values in data. So let’s have a look how many NAs we have:
colSums(is.na(data)) STATE__ BGN_DATE BGN_TIME TIME_ZONE COUNTY COUNTYNAME STATE EVTYPE BGN_RANGE
0 0 0 0 0 0 0 0 0
BGN_AZI BGN_LOCATI END_DATE END_TIME COUNTY_END COUNTYENDN END_RANGE END_AZI END_LOCATI
0 0 0 0 0 902297 0 0 0
LENGTH WIDTH F MAG FATALITIES INJURIES PROPDMG PROPDMGEXP CROPDMG
0 0 843563 0 0 0 0 0 0
CROPDMGEXP WFO STATEOFFIC ZONENAMES LATITUDE LONGITUDE LATITUDE_E LONGITUDE_ REMARKS
0 0 0 0 47 0 40 0 0
REFNUM
0 We have char columns and there are “” values which can’t be detected by is.na function. So let’s try to find empty chars:
table(data$CROPDMGEXP)
? 0 2 B k K m M
618413 7 19 1 9 21 281832 1 1994 We see count of empty chars as 618413. When we use table function we can see empty chars in first item, another example:
table(data$PROPDMGEXP)
- ? + 0 1 2 3 4 5 6 7 8 B h
465934 1 8 5 216 25 13 4 4 28 4 5 1 40 1
H K m M
6 424665 7 11330 So let’s take a look only first item of what table’s retrieve in only character type columns:
for(i in 1:length(names(data))){
if (class(data[,i]) =="character"){
print(names(data)[i])
print(table(data[,i])[1])
}
}[1] "BGN_DATE"
1/1/1966 0:00:00
2
[1] "BGN_TIME"
00:00:00 AM
2383
[1] "TIME_ZONE"
ADT
3
[1] "COUNTYNAME"
1589
[1] "STATE"
AK
4391
[1] "EVTYPE"
HIGH SURF ADVISORY
1
[1] "BGN_AZI"
547332
[1] "BGN_LOCATI"
287743
[1] "END_DATE"
243411
[1] "END_TIME"
238978
[1] "END_AZI"
724837
[1] "END_LOCATI"
499225
[1] "PROPDMGEXP"
465934
[1] "CROPDMGEXP"
618413
[1] "WFO"
142069
[1] "STATEOFFIC"
248769
[1] "ZONENAMES"
594029
[1] "REMARKS"
287433 So we have empty chars in most of char columns. And what is the ratio of empty chars on total rows in same column?
for(i in 1:length(names(data))){
if (class(data[,i]) =="character"){
print(names(data)[i])
print(table(data[,i])[1]/902297)
}
}[1] "BGN_DATE"
1/1/1966 0:00:00
2.216565e-06
[1] "BGN_TIME"
00:00:00 AM
0.002641037
[1] "TIME_ZONE"
ADT
3.324848e-06
[1] "COUNTYNAME"
0.001761061
[1] "STATE"
AK
0.004866469
[1] "EVTYPE"
HIGH SURF ADVISORY
1.108283e-06
[1] "BGN_AZI"
0.6065985
[1] "BGN_LOCATI"
0.3189005
[1] "END_DATE"
0.2697682
[1] "END_TIME"
0.2648551
[1] "END_AZI"
0.8033242
[1] "END_LOCATI"
0.5532823
[1] "PROPDMGEXP"
0.5163865
[1] "CROPDMGEXP"
0.6853763
[1] "WFO"
0.1574526
[1] "STATEOFFIC"
0.2757063
[1] "ZONENAMES"
0.658352
[1] "REMARKS"
0.318557 Some character columns don’t have any empty item which are:BGN_DATE,BGN_TIME, TIME_ZONE, STATE, EVTYPE. But in some columns empty chars are more common than others like %80.33 of END_AZI are empty chars.
data$BGN_DATE[1][1] "4/18/1950 0:00:00"We already have a time column and in BGN_DATE column time ” 0:00:00” is unnecessary:
data$BGN_DATE <- gsub(" 0:00:00","",as.character(data$BGN_DATE))
data$BGN_DATE <- as.Date(data$BGN_DATE, format = "%m/%d/%Y")
We have 3 columns about date and time, first one is BGN_DATE second one is BGN_TIME and the last one is TIME_ZONE. We can paste all the columns and create a POSIXct column for further analysis.
data$date_time <- paste(data$BGN_DATE, data$BGN_TIME, data$TIME_ZONE)Let’s see if have what we wanted
data$date_time[1][1] "1950-04-18 0130 CST"It looks good. Now let’s have a look other char columns:
str(data)'data.frame': 902297 obs. of 38 variables:
$ STATE__ : num 1 1 1 1 1 1 1 1 1 1 ...
$ BGN_DATE : Date, format: "1950-04-18" "1950-04-18" "1951-02-20" ...
$ 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 ...
$ date_time : chr "1950-04-18 0130 CST" "1950-04-18 0145 CST" "1951-02-20 1600 CST" "1951-06-08 0900 CST" ...Let’s look at END_DATE.
unique(sapply(data$END_DATE, nchar))[1] 0 17 16 18So we can assume we have 4 kind of values in EDN_DATE including empty chars.
table(sapply(data$END_DATE, nchar))
0 16 17 18
243411 176777 436199 45910 We have many empty chars on this column. Let’s have a look at EVTYPE column:
sort(unique(data$EVTYPE)) [1] " HIGH SURF ADVISORY" " COASTAL FLOOD" " FLASH FLOOD"
[4] " LIGHTNING" " TSTM WIND" " TSTM WIND (G45)"
[7] " WATERSPOUT" " WIND" "?"
[10] "ABNORMAL WARMTH" "ABNORMALLY DRY" "ABNORMALLY WET"
[13] "ACCUMULATED SNOWFALL" "AGRICULTURAL FREEZE" "APACHE COUNTY"
[16] "ASTRONOMICAL HIGH TIDE" "ASTRONOMICAL LOW TIDE" "AVALANCE"
[19] "AVALANCHE" "BEACH EROSIN" "Beach Erosion"
[22] "BEACH EROSION" "BEACH EROSION/COASTAL FLOOD" "BEACH FLOOD"
[25] "BELOW NORMAL PRECIPITATION" "BITTER WIND CHILL" "BITTER WIND CHILL TEMPERATURES"
[28] "Black Ice" "BLACK ICE" "BLIZZARD"
[31] "BLIZZARD AND EXTREME WIND CHIL" "BLIZZARD AND HEAVY SNOW" "Blizzard Summary"
[34] "BLIZZARD WEATHER" "BLIZZARD/FREEZING RAIN" "BLIZZARD/HEAVY SNOW"
[37] "BLIZZARD/HIGH WIND" "BLIZZARD/WINTER STORM" "BLOW-OUT TIDE"
[40] "BLOW-OUT TIDES" "BLOWING DUST" "blowing snow"
[43] "Blowing Snow" "BLOWING SNOW" "BLOWING SNOW- EXTREME WIND CHI"
[46] "BLOWING SNOW & EXTREME WIND CH" "BLOWING SNOW/EXTREME WIND CHIL" "BREAKUP FLOODING"
[49] "BRUSH FIRE" "BRUSH FIRES" "COASTAL FLOODING/EROSION"
[52] "COASTAL EROSION" "Coastal Flood" "COASTAL FLOOD"
[55] "coastal flooding" "Coastal Flooding" "COASTAL FLOODING"
[58] "COASTAL FLOODING/EROSION" "Coastal Storm" "COASTAL STORM"
[61] "COASTAL SURGE" "COASTAL/TIDAL FLOOD" "COASTALFLOOD"
[64] "COASTALSTORM" "Cold" "COLD"
[67] "COLD AIR FUNNEL" "COLD AIR FUNNELS" "COLD AIR TORNADO"
[70] "Cold and Frost" "COLD AND FROST" "COLD AND SNOW"
[73] "COLD AND WET CONDITIONS" "Cold Temperature" "COLD TEMPERATURES"
[76] "COLD WAVE" "COLD WEATHER" "COLD WIND CHILL TEMPERATURES"
[79] "COLD/WIND CHILL" "COLD/WINDS" "COOL AND WET"
[82] "COOL SPELL" "CSTL FLOODING/EROSION" "DAM BREAK"
[85] "DAM FAILURE" "Damaging Freeze" "DAMAGING FREEZE"
[88] "DEEP HAIL" "DENSE FOG" "DENSE SMOKE"
[91] "DOWNBURST" "DOWNBURST WINDS" "DRIEST MONTH"
[94] "Drifting Snow" "DROUGHT" "DROUGHT/EXCESSIVE HEAT"
[97] "DROWNING" "DRY" "DRY CONDITIONS"
[100] "DRY HOT WEATHER" "DRY MICROBURST" "DRY MICROBURST 50"
[103] "DRY MICROBURST 53" "DRY MICROBURST 58" "DRY MICROBURST 61"
[106] "DRY MICROBURST 84" "DRY MICROBURST WINDS" "DRY MIRCOBURST WINDS"
[109] "DRY PATTERN" "DRY SPELL" "DRY WEATHER"
[112] "DRYNESS" "DUST DEVEL" "Dust Devil"
[115] "DUST DEVIL" "DUST DEVIL WATERSPOUT" "DUST STORM"
[118] "DUST STORM/HIGH WINDS" "DUSTSTORM" "EARLY FREEZE"
[121] "Early Frost" "EARLY FROST" "EARLY RAIN"
[124] "EARLY SNOW" "Early snowfall" "EARLY SNOWFALL"
[127] "Erosion/Cstl Flood" "EXCESSIVE" "Excessive Cold"
[130] "EXCESSIVE HEAT" "EXCESSIVE HEAT/DROUGHT" "EXCESSIVE PRECIPITATION"
[133] "EXCESSIVE RAIN" "EXCESSIVE RAINFALL" "EXCESSIVE SNOW"
[136] "EXCESSIVE WETNESS" "EXCESSIVELY DRY" "Extended Cold"
[139] "Extreme Cold" "EXTREME COLD" "EXTREME COLD/WIND CHILL"
[142] "EXTREME HEAT" "EXTREME WIND CHILL" "EXTREME WIND CHILL/BLOWING SNO"
[145] "EXTREME WIND CHILLS" "EXTREME WINDCHILL" "EXTREME WINDCHILL TEMPERATURES"
[148] "EXTREME/RECORD COLD" "EXTREMELY WET" "FALLING SNOW/ICE"
[151] "FIRST FROST" "FIRST SNOW" "FLASH FLOOD"
[154] "FLASH FLOOD - HEAVY RAIN" "FLASH FLOOD FROM ICE JAMS" "FLASH FLOOD LANDSLIDES"
[157] "FLASH FLOOD WINDS" "FLASH FLOOD/" "FLASH FLOOD/ FLOOD"
[160] "FLASH FLOOD/ STREET" "FLASH FLOOD/FLOOD" "FLASH FLOOD/HEAVY RAIN"
[163] "FLASH FLOOD/LANDSLIDE" "FLASH FLOODING" "FLASH FLOODING/FLOOD"
[166] "FLASH FLOODING/THUNDERSTORM WI" "FLASH FLOODS" "FLASH FLOOODING"
[169] "Flood" "FLOOD" "FLOOD & HEAVY RAIN"
[172] "FLOOD FLASH" "FLOOD FLOOD/FLASH" "FLOOD WATCH/"
[175] "FLOOD/FLASH" "Flood/Flash Flood" "FLOOD/FLASH FLOOD"
[178] "FLOOD/FLASH FLOODING" "FLOOD/FLASH/FLOOD" "FLOOD/FLASHFLOOD"
[181] "FLOOD/RAIN/WIND" "FLOOD/RAIN/WINDS" "FLOOD/RIVER FLOOD"
[184] "Flood/Strong Wind" "FLOODING" "FLOODING/HEAVY RAIN"
[187] "FLOODS" "FOG" "FOG AND COLD TEMPERATURES"
[190] "FOREST FIRES" "Freeze" "FREEZE"
[193] "Freezing drizzle" "Freezing Drizzle" "FREEZING DRIZZLE"
[196] "FREEZING DRIZZLE AND FREEZING" "Freezing Fog" "FREEZING FOG"
[199] "Freezing rain" "Freezing Rain" "FREEZING RAIN"
[202] "FREEZING RAIN AND SLEET" "FREEZING RAIN AND SNOW" "FREEZING RAIN SLEET AND"
[205] "FREEZING RAIN SLEET AND LIGHT" "FREEZING RAIN/SLEET" "FREEZING RAIN/SNOW"
[208] "Freezing Spray" "Frost" "FROST"
[211] "Frost/Freeze" "FROST/FREEZE" "FROST\\FREEZE"
[214] "FUNNEL" "Funnel Cloud" "FUNNEL CLOUD"
[217] "FUNNEL CLOUD." "FUNNEL CLOUD/HAIL" "FUNNEL CLOUDS"
[220] "FUNNELS" "Glaze" "GLAZE"
[223] "GLAZE ICE" "GLAZE/ICE STORM" "gradient wind"
[226] "Gradient wind" "GRADIENT WIND" "GRADIENT WINDS"
[229] "GRASS FIRES" "GROUND BLIZZARD" "GUSTNADO"
[232] "GUSTNADO AND" "GUSTY LAKE WIND" "GUSTY THUNDERSTORM WIND"
[235] "GUSTY THUNDERSTORM WINDS" "Gusty Wind" "GUSTY WIND"
[238] "GUSTY WIND/HAIL" "GUSTY WIND/HVY RAIN" "Gusty wind/rain"
[241] "Gusty winds" "Gusty Winds" "GUSTY WINDS"
[244] "HAIL" "HAIL 0.75" "HAIL 0.88"
[247] "HAIL 075" "HAIL 088" "HAIL 1.00"
[250] "HAIL 1.75" "HAIL 1.75)" "HAIL 100"
[253] "HAIL 125" "HAIL 150" "HAIL 175"
[256] "HAIL 200" "HAIL 225" "HAIL 275"
[259] "HAIL 450" "HAIL 75" "HAIL 80"
[262] "HAIL 88" "HAIL ALOFT" "HAIL DAMAGE"
[265] "HAIL FLOODING" "HAIL STORM" "Hail(0.75)"
[268] "HAIL/ICY ROADS" "HAIL/WIND" "HAIL/WINDS"
[271] "HAILSTORM" "HAILSTORMS" "HARD FREEZE"
[274] "HAZARDOUS SURF" "HEAT" "HEAT DROUGHT"
[277] "Heat Wave" "HEAT WAVE" "HEAT WAVE DROUGHT"
[280] "HEAT WAVES" "HEAT/DROUGHT" "Heatburst"
[283] "HEAVY LAKE SNOW" "HEAVY MIX" "HEAVY PRECIPATATION"
[286] "Heavy Precipitation" "HEAVY PRECIPITATION" "Heavy rain"
[289] "Heavy Rain" "HEAVY RAIN" "HEAVY RAIN AND FLOOD"
[292] "Heavy Rain and Wind" "HEAVY RAIN EFFECTS" "HEAVY RAIN/FLOODING"
[295] "Heavy Rain/High Surf" "HEAVY RAIN/LIGHTNING" "HEAVY RAIN/MUDSLIDES/FLOOD"
[298] "HEAVY RAIN/SEVERE WEATHER" "HEAVY RAIN/SMALL STREAM URBAN" "HEAVY RAIN/SNOW"
[301] "HEAVY RAIN/URBAN FLOOD" "HEAVY RAIN/WIND" "HEAVY RAIN; URBAN FLOOD WINDS;"
[304] "HEAVY RAINFALL" "HEAVY RAINS" "HEAVY RAINS/FLOODING"
[307] "HEAVY SEAS" "HEAVY SHOWER" "HEAVY SHOWERS"
[310] "HEAVY SNOW" "HEAVY SNOW-SQUALLS" "HEAVY SNOW FREEZING RAIN"
[313] "HEAVY SNOW & ICE" "HEAVY SNOW AND" "HEAVY SNOW AND HIGH WINDS"
[316] "HEAVY SNOW AND ICE" "HEAVY SNOW AND ICE STORM" "HEAVY SNOW AND STRONG WINDS"
[319] "HEAVY SNOW ANDBLOWING SNOW" "Heavy snow shower" "HEAVY SNOW SQUALLS"
[322] "HEAVY SNOW/BLIZZARD" "HEAVY SNOW/BLIZZARD/AVALANCHE" "HEAVY SNOW/BLOWING SNOW"
[325] "HEAVY SNOW/FREEZING RAIN" "HEAVY SNOW/HIGH" "HEAVY SNOW/HIGH WIND"
[328] "HEAVY SNOW/HIGH WINDS" "HEAVY SNOW/HIGH WINDS & FLOOD" "HEAVY SNOW/HIGH WINDS/FREEZING"
[331] "HEAVY SNOW/ICE" "HEAVY SNOW/ICE STORM" "HEAVY SNOW/SLEET"
[334] "HEAVY SNOW/SQUALLS" "HEAVY SNOW/WIND" "HEAVY SNOW/WINTER STORM"
[337] "HEAVY SNOWPACK" "Heavy Surf" "HEAVY SURF"
[340] "Heavy surf and wind" "HEAVY SURF COASTAL FLOODING" "HEAVY SURF/HIGH SURF"
[343] "HEAVY SWELLS" "HEAVY WET SNOW" "HIGH"
[346] "HIGH SWELLS" "HIGH WINDS" "HIGH SEAS"
[349] "High Surf" "HIGH SURF" "HIGH SURF ADVISORIES"
[352] "HIGH SURF ADVISORY" "HIGH SWELLS" "HIGH TEMPERATURE RECORD"
[355] "HIGH TIDES" "HIGH WATER" "HIGH WAVES"
[358] "High Wind" "HIGH WIND" "HIGH WIND (G40)"
[361] "HIGH WIND 48" "HIGH WIND 63" "HIGH WIND 70"
[364] "HIGH WIND AND HEAVY SNOW" "HIGH WIND AND HIGH TIDES" "HIGH WIND AND SEAS"
[367] "HIGH WIND DAMAGE" "HIGH WIND/ BLIZZARD" "HIGH WIND/BLIZZARD"
[370] "HIGH WIND/BLIZZARD/FREEZING RA" "HIGH WIND/HEAVY SNOW" "HIGH WIND/LOW WIND CHILL"
[373] "HIGH WIND/SEAS" "HIGH WIND/WIND CHILL" "HIGH WIND/WIND CHILL/BLIZZARD"
[376] "HIGH WINDS" "HIGH WINDS 55" "HIGH WINDS 57"
[379] "HIGH WINDS 58" "HIGH WINDS 63" "HIGH WINDS 66"
[382] "HIGH WINDS 67" "HIGH WINDS 73" "HIGH WINDS 76"
[385] "HIGH WINDS 80" "HIGH WINDS 82" "HIGH WINDS AND WIND CHILL"
[388] "HIGH WINDS DUST STORM" "HIGH WINDS HEAVY RAINS" "HIGH WINDS/"
[391] "HIGH WINDS/COASTAL FLOOD" "HIGH WINDS/COLD" "HIGH WINDS/FLOODING"
[394] "HIGH WINDS/HEAVY RAIN" "HIGH WINDS/SNOW" "HIGHWAY FLOODING"
[397] "Hot and Dry" "HOT PATTERN" "HOT SPELL"
[400] "HOT WEATHER" "HOT/DRY PATTERN" "HURRICANE"
[403] "HURRICANE-GENERATED SWELLS" "Hurricane Edouard" "HURRICANE EMILY"
[406] "HURRICANE ERIN" "HURRICANE FELIX" "HURRICANE GORDON"
[409] "HURRICANE OPAL" "HURRICANE OPAL/HIGH WINDS" "HURRICANE/TYPHOON"
[412] "HVY RAIN" "HYPERTHERMIA/EXPOSURE" "HYPOTHERMIA"
[415] "Hypothermia/Exposure" "HYPOTHERMIA/EXPOSURE" "ICE"
[418] "ICE AND SNOW" "ICE FLOES" "Ice Fog"
[421] "ICE JAM" "Ice jam flood (minor" "ICE JAM FLOODING"
[424] "ICE ON ROAD" "ICE PELLETS" "ICE ROADS"
[427] "ICE STORM" "ICE STORM AND SNOW" "ICE STORM/FLASH FLOOD"
[430] "Ice/Snow" "ICE/SNOW" "ICE/STRONG WINDS"
[433] "Icestorm/Blizzard" "Icy Roads" "ICY ROADS"
[436] "LACK OF SNOW" "LAKE-EFFECT SNOW" "Lake Effect Snow"
[439] "LAKE EFFECT SNOW" "LAKE FLOOD" "LAKESHORE FLOOD"
[442] "LANDSLIDE" "LANDSLIDE/URBAN FLOOD" "LANDSLIDES"
[445] "Landslump" "LANDSLUMP" "LANDSPOUT"
[448] "LARGE WALL CLOUD" "Late-season Snowfall" "LATE FREEZE"
[451] "LATE SEASON HAIL" "LATE SEASON SNOW" "Late Season Snowfall"
[454] "LATE SNOW" "LIGHT FREEZING RAIN" "Light snow"
[457] "Light Snow" "LIGHT SNOW" "LIGHT SNOW AND SLEET"
[460] "Light Snow/Flurries" "LIGHT SNOW/FREEZING PRECIP" "Light Snowfall"
[463] "LIGHTING" "LIGHTNING" "LIGHTNING WAUSEON"
[466] "LIGHTNING AND HEAVY RAIN" "LIGHTNING AND THUNDERSTORM WIN" "LIGHTNING AND WINDS"
[469] "LIGHTNING DAMAGE" "LIGHTNING FIRE" "LIGHTNING INJURY"
[472] "LIGHTNING THUNDERSTORM WINDS" "LIGHTNING THUNDERSTORM WINDSS" "LIGHTNING."
[475] "LIGHTNING/HEAVY RAIN" "LIGNTNING" "LOCAL FLASH FLOOD"
[478] "LOCAL FLOOD" "LOCALLY HEAVY RAIN" "LOW TEMPERATURE"
[481] "LOW TEMPERATURE RECORD" "LOW WIND CHILL" "MAJOR FLOOD"
[484] "Marine Accident" "MARINE HAIL" "MARINE HIGH WIND"
[487] "MARINE MISHAP" "MARINE STRONG WIND" "MARINE THUNDERSTORM WIND"
[490] "MARINE TSTM WIND" "Metro Storm, May 26" "Microburst"
[493] "MICROBURST" "MICROBURST WINDS" "Mild and Dry Pattern"
[496] "MILD PATTERN" "MILD/DRY PATTERN" "MINOR FLOOD"
[499] "Minor Flooding" "MINOR FLOODING" "MIXED PRECIP"
[502] "Mixed Precipitation" "MIXED PRECIPITATION" "MODERATE SNOW"
[505] "MODERATE SNOWFALL" "MONTHLY PRECIPITATION" "Monthly Rainfall"
[508] "MONTHLY RAINFALL" "Monthly Snowfall" "MONTHLY SNOWFALL"
[511] "MONTHLY TEMPERATURE" "Mountain Snows" "MUD SLIDE"
[514] "MUD SLIDES" "MUD SLIDES URBAN FLOODING" "MUD/ROCK SLIDE"
[517] "Mudslide" "MUDSLIDE" "MUDSLIDE/LANDSLIDE"
[520] "Mudslides" "MUDSLIDES" "NEAR RECORD SNOW"
[523] "No Severe Weather" "NON-SEVERE WIND DAMAGE" "NON-TSTM WIND"
[526] "NON SEVERE HAIL" "NON TSTM WIND" "NONE"
[529] "NORMAL PRECIPITATION" "NORTHERN LIGHTS" "Other"
[532] "OTHER" "PATCHY DENSE FOG" "PATCHY ICE"
[535] "Prolong Cold" "PROLONG COLD" "PROLONG COLD/SNOW"
[538] "PROLONG WARMTH" "PROLONGED RAIN" "RAIN"
[541] "RAIN (HEAVY)" "RAIN AND WIND" "Rain Damage"
[544] "RAIN/SNOW" "RAIN/WIND" "RAINSTORM"
[547] "RAPIDLY RISING WATER" "RECORD COLD" "Record Cold"
[550] "RECORD COLD" "RECORD COLD AND HIGH WIND" "RECORD COLD/FROST"
[553] "RECORD COOL" "Record dry month" "RECORD DRYNESS"
[556] "Record Heat" "RECORD HEAT" "RECORD HEAT WAVE"
[559] "Record High" "RECORD HIGH" "RECORD HIGH TEMPERATURE"
[562] "RECORD HIGH TEMPERATURES" "RECORD LOW" "RECORD LOW RAINFALL"
[565] "Record May Snow" "RECORD PRECIPITATION" "RECORD RAINFALL"
[568] "RECORD SNOW" "RECORD SNOW/COLD" "RECORD SNOWFALL"
[571] "Record temperature" "RECORD TEMPERATURE" "Record Temperatures"
[574] "RECORD TEMPERATURES" "RECORD WARM" "RECORD WARM TEMPS."
[577] "Record Warmth" "RECORD WARMTH" "Record Winter Snow"
[580] "RECORD/EXCESSIVE HEAT" "RECORD/EXCESSIVE RAINFALL" "RED FLAG CRITERIA"
[583] "RED FLAG FIRE WX" "REMNANTS OF FLOYD" "RIP CURRENT"
[586] "RIP CURRENTS" "RIP CURRENTS HEAVY SURF" "RIP CURRENTS/HEAVY SURF"
[589] "RIVER AND STREAM FLOOD" "RIVER FLOOD" "River Flooding"
[592] "RIVER FLOODING" "ROCK SLIDE" "ROGUE WAVE"
[595] "ROTATING WALL CLOUD" "ROUGH SEAS" "ROUGH SURF"
[598] "RURAL FLOOD" "Saharan Dust" "SAHARAN DUST"
[601] "Seasonal Snowfall" "SEICHE" "SEVERE COLD"
[604] "SEVERE THUNDERSTORM" "SEVERE THUNDERSTORM WINDS" "SEVERE THUNDERSTORMS"
[607] "SEVERE TURBULENCE" "SLEET" "SLEET & FREEZING RAIN"
[610] "SLEET STORM" "SLEET/FREEZING RAIN" "SLEET/ICE STORM"
[613] "SLEET/RAIN/SNOW" "SLEET/SNOW" "small hail"
[616] "Small Hail" "SMALL HAIL" "SMALL STREAM"
[619] "SMALL STREAM AND" "SMALL STREAM AND URBAN FLOOD" "SMALL STREAM AND URBAN FLOODIN"
[622] "SMALL STREAM FLOOD" "SMALL STREAM FLOODING" "SMALL STREAM URBAN FLOOD"
[625] "SMALL STREAM/URBAN FLOOD" "Sml Stream Fld" "SMOKE"
[628] "Snow" "SNOW" "SNOW- HIGH WIND- WIND CHILL"
[631] "Snow Accumulation" "SNOW ACCUMULATION" "SNOW ADVISORY"
[634] "SNOW AND COLD" "SNOW AND HEAVY SNOW" "Snow and Ice"
[637] "SNOW AND ICE" "SNOW AND ICE STORM" "Snow and sleet"
[640] "SNOW AND SLEET" "SNOW AND WIND" "SNOW DROUGHT"
[643] "SNOW FREEZING RAIN" "SNOW SHOWERS" "SNOW SLEET"
[646] "SNOW SQUALL" "Snow squalls" "Snow Squalls"
[649] "SNOW SQUALLS" "SNOW/ BITTER COLD" "SNOW/ ICE"
[652] "SNOW/BLOWING SNOW" "SNOW/COLD" "SNOW/FREEZING RAIN"
[655] "SNOW/HEAVY SNOW" "SNOW/HIGH WINDS" "SNOW/ICE"
[658] "SNOW/ICE STORM" "SNOW/RAIN" "SNOW/RAIN/SLEET"
[661] "SNOW/SLEET" "SNOW/SLEET/FREEZING RAIN" "SNOW/SLEET/RAIN"
[664] "SNOW\\COLD" "SNOWFALL RECORD" "SNOWMELT FLOODING"
[667] "SNOWSTORM" "SOUTHEAST" "STORM FORCE WINDS"
[670] "STORM SURGE" "STORM SURGE/TIDE" "STREAM FLOODING"
[673] "STREET FLOOD" "STREET FLOODING" "Strong Wind"
[676] "STRONG WIND" "STRONG WIND GUST" "Strong winds"
[679] "Strong Winds" "STRONG WINDS" "Summary August 10"
[682] "Summary August 11" "Summary August 17" "Summary August 2-3"
[685] "Summary August 21" "Summary August 28" "Summary August 4"
[688] "Summary August 7" "Summary August 9" "Summary Jan 17"
[691] "Summary July 23-24" "Summary June 18-19" "Summary June 5-6"
[694] "Summary June 6" "Summary of April 12" "Summary of April 13"
[697] "Summary of April 21" "Summary of April 27" "Summary of April 3rd"
[700] "Summary of August 1" "Summary of July 11" "Summary of July 2"
[703] "Summary of July 22" "Summary of July 26" "Summary of July 29"
[706] "Summary of July 3" "Summary of June 10" "Summary of June 11"
[709] "Summary of June 12" "Summary of June 13" "Summary of June 15"
[712] "Summary of June 16" "Summary of June 18" "Summary of June 23"
[715] "Summary of June 24" "Summary of June 3" "Summary of June 30"
[718] "Summary of June 4" "Summary of June 6" "Summary of March 14"
[721] "Summary of March 23" "Summary of March 24" "SUMMARY OF MARCH 24-25"
[724] "SUMMARY OF MARCH 27" "SUMMARY OF MARCH 29" "Summary of May 10"
[727] "Summary of May 13" "Summary of May 14" "Summary of May 22"
[730] "Summary of May 22 am" "Summary of May 22 pm" "Summary of May 26 am"
[733] "Summary of May 26 pm" "Summary of May 31 am" "Summary of May 31 pm"
[736] "Summary of May 9-10" "Summary Sept. 25-26" "Summary September 20"
[739] "Summary September 23" "Summary September 3" "Summary September 4"
[742] "Summary: Nov. 16" "Summary: Nov. 6-7" "Summary: Oct. 20-21"
[745] "Summary: October 31" "Summary: Sept. 18" "Temperature record"
[748] "THUDERSTORM WINDS" "THUNDEERSTORM WINDS" "THUNDERESTORM WINDS"
[751] "THUNDERSNOW" "Thundersnow shower" "THUNDERSTORM"
[754] "THUNDERSTORM WINDS" "THUNDERSTORM DAMAGE" "THUNDERSTORM DAMAGE TO"
[757] "THUNDERSTORM HAIL" "THUNDERSTORM W INDS" "Thunderstorm Wind"
[760] "THUNDERSTORM WIND" "THUNDERSTORM WIND (G40)" "THUNDERSTORM WIND 50"
[763] "THUNDERSTORM WIND 52" "THUNDERSTORM WIND 56" "THUNDERSTORM WIND 59"
[766] "THUNDERSTORM WIND 59 MPH" "THUNDERSTORM WIND 59 MPH." "THUNDERSTORM WIND 60 MPH"
[769] "THUNDERSTORM WIND 65 MPH" "THUNDERSTORM WIND 65MPH" "THUNDERSTORM WIND 69"
[772] "THUNDERSTORM WIND 98 MPH" "THUNDERSTORM WIND G50" "THUNDERSTORM WIND G51"
[775] "THUNDERSTORM WIND G52" "THUNDERSTORM WIND G55" "THUNDERSTORM WIND G60"
[778] "THUNDERSTORM WIND G61" "THUNDERSTORM WIND TREES" "THUNDERSTORM WIND."
[781] "THUNDERSTORM WIND/ TREE" "THUNDERSTORM WIND/ TREES" "THUNDERSTORM WIND/AWNING"
[784] "THUNDERSTORM WIND/HAIL" "THUNDERSTORM WIND/LIGHTNING" "THUNDERSTORM WINDS"
[787] "THUNDERSTORM WINDS LE CEN" "THUNDERSTORM WINDS 13" "THUNDERSTORM WINDS 2"
[790] "THUNDERSTORM WINDS 50" "THUNDERSTORM WINDS 52" "THUNDERSTORM WINDS 53"
[793] "THUNDERSTORM WINDS 60" "THUNDERSTORM WINDS 61" "THUNDERSTORM WINDS 62"
[796] "THUNDERSTORM WINDS 63 MPH" "THUNDERSTORM WINDS AND" "THUNDERSTORM WINDS FUNNEL CLOU"
[799] "THUNDERSTORM WINDS G" "THUNDERSTORM WINDS G60" "THUNDERSTORM WINDS HAIL"
[802] "THUNDERSTORM WINDS HEAVY RAIN" "THUNDERSTORM WINDS LIGHTNING" "THUNDERSTORM WINDS SMALL STREA"
[805] "THUNDERSTORM WINDS URBAN FLOOD" "THUNDERSTORM WINDS." "THUNDERSTORM WINDS/ FLOOD"
[808] "THUNDERSTORM WINDS/ HAIL" "THUNDERSTORM WINDS/FLASH FLOOD" "THUNDERSTORM WINDS/FLOODING"
[811] "THUNDERSTORM WINDS/FUNNEL CLOU" "THUNDERSTORM WINDS/HAIL" "THUNDERSTORM WINDS/HEAVY RAIN"
[814] "THUNDERSTORM WINDS53" "THUNDERSTORM WINDSHAIL" "THUNDERSTORM WINDSS"
[817] "THUNDERSTORM WINS" "THUNDERSTORMS" "THUNDERSTORMS WIND"
[820] "THUNDERSTORMS WINDS" "THUNDERSTORMW" "THUNDERSTORMW 50"
[823] "THUNDERSTORMW WINDS" "THUNDERSTORMWINDS" "THUNDERSTROM WIND"
[826] "THUNDERSTROM WINDS" "THUNDERTORM WINDS" "THUNDERTSORM WIND"
[829] "THUNDESTORM WINDS" "THUNERSTORM WINDS" "TIDAL FLOOD"
[832] "Tidal Flooding" "TIDAL FLOODING" "TORNADO"
[835] "TORNADO DEBRIS" "TORNADO F0" "TORNADO F1"
[838] "TORNADO F2" "TORNADO F3" "TORNADO/WATERSPOUT"
[841] "TORNADOES" "TORNADOES, TSTM WIND, HAIL" "TORNADOS"
[844] "TORNDAO" "TORRENTIAL RAIN" "Torrential Rainfall"
[847] "TROPICAL DEPRESSION" "TROPICAL STORM" "TROPICAL STORM ALBERTO"
[850] "TROPICAL STORM DEAN" "TROPICAL STORM GORDON" "TROPICAL STORM JERRY"
[853] "TSTM" "TSTM HEAVY RAIN" "Tstm Wind"
[856] "TSTM WIND" "TSTM WIND (G45)" "TSTM WIND (41)"
[859] "TSTM WIND (G35)" "TSTM WIND (G40)" "TSTM WIND (G45)"
[862] "TSTM WIND 40" "TSTM WIND 45" "TSTM WIND 50"
[865] "TSTM WIND 51" "TSTM WIND 52" "TSTM WIND 55"
[868] "TSTM WIND 65)" "TSTM WIND AND LIGHTNING" "TSTM WIND DAMAGE"
[871] "TSTM WIND G45" "TSTM WIND G58" "TSTM WIND/HAIL"
[874] "TSTM WINDS" "TSTM WND" "TSTMW"
[877] "TSUNAMI" "TUNDERSTORM WIND" "TYPHOON"
[880] "Unseasonable Cold" "UNSEASONABLY COLD" "UNSEASONABLY COOL"
[883] "UNSEASONABLY COOL & WET" "UNSEASONABLY DRY" "UNSEASONABLY HOT"
[886] "UNSEASONABLY WARM" "UNSEASONABLY WARM & WET" "UNSEASONABLY WARM AND DRY"
[889] "UNSEASONABLY WARM YEAR" "UNSEASONABLY WARM/WET" "UNSEASONABLY WET"
[892] "UNSEASONAL LOW TEMP" "UNSEASONAL RAIN" "UNUSUAL WARMTH"
[895] "UNUSUAL/RECORD WARMTH" "UNUSUALLY COLD" "UNUSUALLY LATE SNOW"
[898] "UNUSUALLY WARM" "URBAN AND SMALL" "URBAN AND SMALL STREAM"
[901] "URBAN AND SMALL STREAM FLOOD" "URBAN AND SMALL STREAM FLOODIN" "Urban flood"
[904] "Urban Flood" "URBAN FLOOD" "URBAN FLOOD LANDSLIDE"
[907] "Urban Flooding" "URBAN FLOODING" "URBAN FLOODS"
[910] "URBAN SMALL" "URBAN SMALL STREAM FLOOD" "URBAN/SMALL"
[913] "URBAN/SMALL FLOODING" "URBAN/SMALL STREAM" "URBAN/SMALL STREAM FLOOD"
[916] "URBAN/SMALL STREAM FLOOD" "URBAN/SMALL STREAM FLOODING" "URBAN/SMALL STRM FLDG"
[919] "URBAN/SML STREAM FLD" "URBAN/SML STREAM FLDG" "URBAN/STREET FLOODING"
[922] "VERY DRY" "VERY WARM" "VOG"
[925] "Volcanic Ash" "VOLCANIC ASH" "Volcanic Ash Plume"
[928] "VOLCANIC ASHFALL" "VOLCANIC ERUPTION" "WAKE LOW WIND"
[931] "WALL CLOUD" "WALL CLOUD/FUNNEL CLOUD" "WARM DRY CONDITIONS"
[934] "WARM WEATHER" "WATER SPOUT" "WATERSPOUT"
[937] "WATERSPOUT-" "WATERSPOUT-TORNADO" "WATERSPOUT FUNNEL CLOUD"
[940] "WATERSPOUT TORNADO" "WATERSPOUT/" "WATERSPOUT/ TORNADO"
[943] "WATERSPOUT/TORNADO" "WATERSPOUTS" "WAYTERSPOUT"
[946] "wet micoburst" "WET MICROBURST" "Wet Month"
[949] "WET SNOW" "WET WEATHER" "Wet Year"
[952] "Whirlwind" "WHIRLWIND" "WILD FIRES"
[955] "WILD/FOREST FIRE" "WILD/FOREST FIRES" "WILDFIRE"
[958] "WILDFIRES" "Wind" "WIND"
[961] "WIND ADVISORY" "WIND AND WAVE" "WIND CHILL"
[964] "WIND CHILL/HIGH WIND" "Wind Damage" "WIND DAMAGE"
[967] "WIND GUSTS" "WIND STORM" "WIND/HAIL"
[970] "WINDS" "WINTER MIX" "WINTER STORM"
[973] "WINTER STORM HIGH WINDS" "WINTER STORM/HIGH WIND" "WINTER STORM/HIGH WINDS"
[976] "WINTER STORMS" "Winter Weather" "WINTER WEATHER"
[979] "WINTER WEATHER MIX" "WINTER WEATHER/MIX" "WINTERY MIX"
[982] "Wintry mix" "Wintry Mix" "WINTRY MIX"
[985] "WND" There are typos on the EVTYPE column and misplaced empty spaces also. And There are some Summary knowledge which will be investigated afterwards. But let’s first we fix the upper lower cases:
data$EVTYPE <- toupper(data$EVTYPE)Let’s have a look at Wind kind of events:
grep("^WIND", unique(data$EVTYPE), value = TRUE) [1] "WIND" "WIND CHILL" "WIND CHILL/HIGH WIND" "WIND DAMAGE"
[5] "WINDS" "WIND STORM" "WIND/HAIL" "WIND ADVISORY"
[9] "WIND AND WAVE" "WIND GUSTS" Also there is WND or ” WIND”:
grep("^WND", unique(data$EVTYPE), value = TRUE)[1] "WND"grep("^ WIND", unique(data$EVTYPE), value = TRUE)[1] " WIND"Let’s merge them into one type:
data$EVTYPE[data$EVTYPE =="WND" | data$EVTYPE ==" WIND" | data$EVTYPE =="WINDS"] <- "WIND"And there are empty spaces in front of the words.
spaced_list <- list(grep("^ ", unique(data$EVTYPE), value = TRUE))Let’s fix empty spaces with trimws:
for (i in 1:length(spaced_list[[1]])){
data$EVTYPE[data$EVTYPE== spaced_list[[1]][i]]<- trimws(spaced_list[[1]][i])
}Now what do we have?
unique(data$EVTYPE) [1] "TORNADO" "TSTM WIND" "HAIL"
[4] "FREEZING RAIN" "SNOW" "ICE STORM/FLASH FLOOD"
[7] "SNOW/ICE" "WINTER STORM" "HURRICANE OPAL/HIGH WINDS"
[10] "THUNDERSTORM WINDS" "RECORD COLD" "HURRICANE ERIN"
[13] "HURRICANE OPAL" "HEAVY RAIN" "LIGHTNING"
[16] "THUNDERSTORM WIND" "DENSE FOG" "RIP CURRENT"
[19] "THUNDERSTORM WINS" "FLASH FLOOD" "FLASH FLOODING"
[22] "HIGH WINDS" "FUNNEL CLOUD" "TORNADO F0"
[25] "THUNDERSTORM WINDS LIGHTNING" "THUNDERSTORM WINDS/HAIL" "HEAT"
[28] "WIND" "LIGHTING" "HEAVY RAINS"
[31] "LIGHTNING AND HEAVY RAIN" "FUNNEL" "WALL CLOUD"
[34] "FLOODING" "THUNDERSTORM WINDS HAIL" "FLOOD"
[37] "COLD" "HEAVY RAIN/LIGHTNING" "FLASH FLOODING/THUNDERSTORM WI"
[40] "WALL CLOUD/FUNNEL CLOUD" "THUNDERSTORM" "WATERSPOUT"
[43] "EXTREME COLD" "HAIL 1.75)" "LIGHTNING/HEAVY RAIN"
[46] "HIGH WIND" "BLIZZARD" "BLIZZARD WEATHER"
[49] "WIND CHILL" "BREAKUP FLOODING" "HIGH WIND/BLIZZARD"
[52] "RIVER FLOOD" "HEAVY SNOW" "FREEZE"
[55] "COASTAL FLOOD" "HIGH WIND AND HIGH TIDES" "HIGH WIND/BLIZZARD/FREEZING RA"
[58] "HIGH TIDES" "HIGH WIND AND HEAVY SNOW" "RECORD COLD AND HIGH WIND"
[61] "RECORD HIGH TEMPERATURE" "RECORD HIGH" "HIGH WINDS HEAVY RAINS"
[64] "HIGH WIND/ BLIZZARD" "ICE STORM" "BLIZZARD/HIGH WIND"
[67] "HIGH WIND/LOW WIND CHILL" "HEAVY SNOW/HIGH" "RECORD LOW"
[70] "HIGH WINDS AND WIND CHILL" "HEAVY SNOW/HIGH WINDS/FREEZING" "LOW TEMPERATURE RECORD"
[73] "AVALANCHE" "MARINE MISHAP" "WIND CHILL/HIGH WIND"
[76] "HIGH WIND/WIND CHILL/BLIZZARD" "HIGH WIND/WIND CHILL" "HIGH WIND/HEAVY SNOW"
[79] "HIGH TEMPERATURE RECORD" "FLOOD WATCH/" "RECORD HIGH TEMPERATURES"
[82] "HIGH WIND/SEAS" "HIGH WINDS/HEAVY RAIN" "HIGH SEAS"
[85] "SEVERE TURBULENCE" "RECORD RAINFALL" "RECORD SNOWFALL"
[88] "RECORD WARMTH" "HEAVY SNOW/WIND" "EXTREME HEAT"
[91] "WIND DAMAGE" "DUST STORM" "APACHE COUNTY"
[94] "SLEET" "HAIL STORM" "FUNNEL CLOUDS"
[97] "FLASH FLOODS" "DUST DEVIL" "EXCESSIVE HEAT"
[100] "THUNDERSTORM WINDS/FUNNEL CLOU" "WINTER STORM/HIGH WIND" "WINTER STORM/HIGH WINDS"
[103] "GUSTY WINDS" "STRONG WINDS" "FLOODING/HEAVY RAIN"
[106] "SNOW AND WIND" "HEAVY SURF COASTAL FLOODING" "HEAVY SURF"
[109] "HEAVY PRECIPATATION" "URBAN FLOODING" "HIGH SURF"
[112] "BLOWING DUST" "URBAN/SMALL" "WILD FIRES"
[115] "HIGH" "URBAN/SMALL FLOODING" "WATER SPOUT"
[118] "HIGH WINDS DUST STORM" "WINTER STORM HIGH WINDS" "LOCAL FLOOD"
[121] "WINTER STORMS" "MUDSLIDES" "RAINSTORM"
[124] "SEVERE THUNDERSTORM" "SEVERE THUNDERSTORMS" "SEVERE THUNDERSTORM WINDS"
[127] "THUNDERSTORMS WINDS" "DRY MICROBURST" "FLOOD/FLASH FLOOD"
[130] "FLOOD/RAIN/WINDS" "DRY MICROBURST 61" "THUNDERSTORMS"
[133] "FLASH FLOOD WINDS" "URBAN/SMALL STREAM FLOODING" "MICROBURST"
[136] "STRONG WIND" "HIGH WIND DAMAGE" "STREAM FLOODING"
[139] "URBAN AND SMALL" "HEAVY SNOWPACK" "ICE"
[142] "FLASH FLOOD/" "DOWNBURST" "GUSTNADO AND"
[145] "FLOOD/RAIN/WIND" "WET MICROBURST" "DOWNBURST WINDS"
[148] "DRY MICROBURST WINDS" "DRY MIRCOBURST WINDS" "DRY MICROBURST 53"
[151] "SMALL STREAM URBAN FLOOD" "MICROBURST WINDS" "HIGH WINDS 57"
[154] "DRY MICROBURST 50" "HIGH WINDS 66" "HIGH WINDS 76"
[157] "HIGH WINDS 63" "HIGH WINDS 67" "BLIZZARD/HEAVY SNOW"
[160] "HEAVY SNOW/HIGH WINDS" "BLOWING SNOW" "HIGH WINDS 82"
[163] "HIGH WINDS 80" "HIGH WINDS 58" "FREEZING DRIZZLE"
[166] "LIGHTNING THUNDERSTORM WINDSS" "DRY MICROBURST 58" "HAIL 75"
[169] "HIGH WINDS 73" "HIGH WINDS 55" "LIGHT SNOW AND SLEET"
[172] "URBAN FLOOD" "DRY MICROBURST 84" "THUNDERSTORM WINDS 60"
[175] "HEAVY RAIN/FLOODING" "THUNDERSTORM WINDSS" "TORNADOS"
[178] "GLAZE" "RECORD HEAT" "COASTAL FLOODING"
[181] "HEAT WAVE" "FIRST SNOW" "FREEZING RAIN AND SLEET"
[184] "UNSEASONABLY DRY" "UNSEASONABLY WET" "WINTRY MIX"
[187] "WINTER WEATHER" "UNSEASONABLY COLD" "EXTREME/RECORD COLD"
[190] "RIP CURRENTS HEAVY SURF" "SLEET/RAIN/SNOW" "UNSEASONABLY WARM"
[193] "DROUGHT" "NORMAL PRECIPITATION" "HIGH WINDS/FLOODING"
[196] "DRY" "RAIN/SNOW" "SNOW/RAIN/SLEET"
[199] "WATERSPOUT/TORNADO" "WATERSPOUTS" "WATERSPOUT TORNADO"
[202] "URBAN/SMALL STREAM FLOOD" "STORM SURGE" "WATERSPOUT-TORNADO"
[205] "WATERSPOUT-" "TORNADOES, TSTM WIND, HAIL" "TROPICAL STORM ALBERTO"
[208] "TROPICAL STORM" "TROPICAL STORM GORDON" "TROPICAL STORM JERRY"
[211] "LIGHTNING THUNDERSTORM WINDS" "WAYTERSPOUT" "MINOR FLOODING"
[214] "LIGHTNING INJURY" "URBAN/SMALL STREAM FLOOD" "LIGHTNING AND THUNDERSTORM WIN"
[217] "THUNDERSTORM WINDS53" "URBAN AND SMALL STREAM FLOOD" "URBAN AND SMALL STREAM"
[220] "WILDFIRE" "DAMAGING FREEZE" "THUNDERSTORM WINDS 13"
[223] "SMALL HAIL" "HEAVY SNOW/HIGH WIND" "HURRICANE"
[226] "WILD/FOREST FIRE" "SMALL STREAM FLOODING" "MUD SLIDE"
[229] "LIGNTNING" "FROST" "FREEZING RAIN/SNOW"
[232] "HIGH WINDS/" "THUNDERSNOW" "FLOODS"
[235] "EXTREME WIND CHILLS" "COOL AND WET" "HEAVY RAIN/SNOW"
[238] "SMALL STREAM AND URBAN FLOODIN" "SMALL STREAM/URBAN FLOOD" "SNOW/SLEET/FREEZING RAIN"
[241] "SEVERE COLD" "GLAZE ICE" "COLD WAVE"
[244] "EARLY SNOW" "SMALL STREAM AND URBAN FLOOD" "HIGH WINDS"
[247] "RURAL FLOOD" "SMALL STREAM AND" "MUD SLIDES"
[250] "HAIL 80" "EXTREME WIND CHILL" "COLD AND WET CONDITIONS"
[253] "EXCESSIVE WETNESS" "GRADIENT WINDS" "HEAVY SNOW/BLOWING SNOW"
[256] "SLEET/ICE STORM" "THUNDERSTORM WINDS URBAN FLOOD" "THUNDERSTORM WINDS SMALL STREA"
[259] "ROTATING WALL CLOUD" "LARGE WALL CLOUD" "COLD AIR FUNNEL"
[262] "GUSTNADO" "COLD AIR FUNNELS" "BLOWING SNOW- EXTREME WIND CHI"
[265] "SNOW AND HEAVY SNOW" "GROUND BLIZZARD" "MAJOR FLOOD"
[268] "SNOW/HEAVY SNOW" "FREEZING RAIN/SLEET" "ICE JAM FLOODING"
[271] "SNOW- HIGH WIND- WIND CHILL" "STREET FLOOD" "COLD AIR TORNADO"
[274] "SMALL STREAM FLOOD" "FOG" "THUNDERSTORM WINDS 2"
[277] "FUNNEL CLOUD/HAIL" "ICE/SNOW" "TSTM WIND 51"
[280] "TSTM WIND 50" "TSTM WIND 52" "TSTM WIND 55"
[283] "HEAVY SNOW/BLIZZARD" "THUNDERSTORM WINDS 61" "HAIL 0.75"
[286] "THUNDERSTORM DAMAGE" "THUNDERTORM WINDS" "HAIL 1.00"
[289] "HAIL/WINDS" "SNOW AND ICE" "WIND STORM"
[292] "SNOWSTORM" "GRASS FIRES" "LAKE FLOOD"
[295] "PROLONG COLD" "HAIL/WIND" "HAIL 1.75"
[298] "THUNDERSTORMW 50" "WIND/HAIL" "SNOW AND ICE STORM"
[301] "URBAN AND SMALL STREAM FLOODIN" "THUNDERSTORMS WIND" "THUNDERSTORM WINDS"
[304] "HEAVY SNOW/SLEET" "AGRICULTURAL FREEZE" "DROUGHT/EXCESSIVE HEAT"
[307] "TUNDERSTORM WIND" "TROPICAL STORM DEAN" "THUNDERTSORM WIND"
[310] "THUNDERSTORM WINDS/ HAIL" "THUNDERSTORM WIND/LIGHTNING" "HEAVY RAIN/SEVERE WEATHER"
[313] "THUNDESTORM WINDS" "WATERSPOUT/ TORNADO" "LIGHTNING."
[316] "WARM DRY CONDITIONS" "HURRICANE-GENERATED SWELLS" "HEAVY SNOW/ICE STORM"
[319] "RIVER AND STREAM FLOOD" "HIGH WIND 63" "COASTAL SURGE"
[322] "HEAVY SNOW AND ICE STORM" "MINOR FLOOD" "HIGH WINDS/COASTAL FLOOD"
[325] "RAIN" "RIVER FLOODING" "SNOW/RAIN"
[328] "ICE FLOES" "HIGH WAVES" "SNOW SQUALLS"
[331] "SNOW SQUALL" "THUNDERSTORM WIND G50" "LIGHTNING FIRE"
[334] "BLIZZARD/FREEZING RAIN" "HEAVY LAKE SNOW" "HEAVY SNOW/FREEZING RAIN"
[337] "LAKE EFFECT SNOW" "HEAVY WET SNOW" "DUST DEVIL WATERSPOUT"
[340] "THUNDERSTORM WINDS/HEAVY RAIN" "THUNDERSTROM WINDS" "THUNDERSTORM WINDS LE CEN"
[343] "HAIL 225" "BLIZZARD AND HEAVY SNOW" "HEAVY SNOW AND ICE"
[346] "ICE STORM AND SNOW" "HEAVY SNOW ANDBLOWING SNOW" "HEAVY SNOW/ICE"
[349] "BLIZZARD AND EXTREME WIND CHIL" "LOW WIND CHILL" "BLOWING SNOW & EXTREME WIND CH"
[352] "WATERSPOUT/" "URBAN/SMALL STREAM" "TORNADO F3"
[355] "FUNNEL CLOUD." "TORNDAO" "HAIL 0.88"
[358] "FLOOD/RIVER FLOOD" "MUD SLIDES URBAN FLOODING" "TORNADO F1"
[361] "THUNDERSTORM WINDS G" "DEEP HAIL" "GLAZE/ICE STORM"
[364] "HEAVY SNOW/WINTER STORM" "AVALANCE" "BLIZZARD/WINTER STORM"
[367] "DUST STORM/HIGH WINDS" "ICE JAM" "FOREST FIRES"
[370] "THUNDERSTORM WIND G60" "FROST\\FREEZE" "THUNDERSTORM WINDS."
[373] "HAIL 88" "HAIL 175" "HVY RAIN"
[376] "HAIL 100" "HAIL 150" "HAIL 075"
[379] "THUNDERSTORM WIND G55" "HAIL 125" "THUNDERSTORM WINDS G60"
[382] "HARD FREEZE" "HAIL 200" "THUNDERSTORM WINDS FUNNEL CLOU"
[385] "THUNDERSTORM WINDS 62" "WILDFIRES" "RECORD HEAT WAVE"
[388] "HEAVY SNOW AND HIGH WINDS" "HEAVY SNOW/HIGH WINDS & FLOOD" "HAIL FLOODING"
[391] "THUNDERSTORM WINDS/FLASH FLOOD" "HIGH WIND 70" "WET SNOW"
[394] "HEAVY RAIN AND FLOOD" "LOCAL FLASH FLOOD" "THUNDERSTORM WINDS 53"
[397] "FLOOD/FLASH FLOODING" "TORNADO/WATERSPOUT" "RAIN AND WIND"
[400] "THUNDERSTORM WIND 59" "THUNDERSTORM WIND 52" "COASTAL/TIDAL FLOOD"
[403] "SNOW/ICE STORM" "BELOW NORMAL PRECIPITATION" "RIP CURRENTS/HEAVY SURF"
[406] "FLASH FLOOD/FLOOD" "EXCESSIVE RAIN" "RECORD/EXCESSIVE HEAT"
[409] "HEAT WAVES" "LIGHT SNOW" "THUNDERSTORM WIND 69"
[412] "HAIL DAMAGE" "LIGHTNING DAMAGE" "RECORD TEMPERATURES"
[415] "LIGHTNING AND WINDS" "FOG AND COLD TEMPERATURES" "OTHER"
[418] "RECORD SNOW" "SNOW/COLD" "FLASH FLOOD FROM ICE JAMS"
[421] "TSTM WIND G58" "MUDSLIDE" "HEAVY SNOW SQUALLS"
[424] "HEAVY SNOW/SQUALLS" "HEAVY SNOW-SQUALLS" "ICY ROADS"
[427] "HEAVY MIX" "SNOW FREEZING RAIN" "LACK OF SNOW"
[430] "SNOW/SLEET" "SNOW/FREEZING RAIN" "SNOW DROUGHT"
[433] "THUNDERSTORMW WINDS" "THUNDERSTORM WIND 60 MPH" "THUNDERSTORM WIND 65MPH"
[436] "THUNDERSTORM WIND/ TREES" "THUNDERSTORM WIND/AWNING" "THUNDERSTORM WIND 98 MPH"
[439] "THUNDERSTORM WIND TREES" "TORRENTIAL RAIN" "TORNADO F2"
[442] "RIP CURRENTS" "HURRICANE EMILY" "HURRICANE GORDON"
[445] "HURRICANE FELIX" "THUNDERSTORM WIND 59 MPH" "THUNDERSTORM WINDS 63 MPH"
[448] "THUNDERSTORM WIND/ TREE" "THUNDERSTORM DAMAGE TO" "THUNDERSTORM WIND 65 MPH"
[451] "FLASH FLOOD - HEAVY RAIN" "THUNDERSTORM WIND." "FLASH FLOOD/ STREET"
[454] "THUNDERSTORM WIND 59 MPH." "HEAVY SNOW FREEZING RAIN" "DAM FAILURE"
[457] "THUNDERSTORM HAIL" "HAIL 088" "THUNDERSTORM WINDSHAIL"
[460] "LIGHTNING WAUSEON" "THUDERSTORM WINDS" "ICE AND SNOW"
[463] "RECORD COLD/FROST" "STORM FORCE WINDS" "FREEZING RAIN AND SNOW"
[466] "FREEZING RAIN SLEET AND" "SOUTHEAST" "HEAVY SNOW & ICE"
[469] "FREEZING DRIZZLE AND FREEZING" "THUNDERSTORM WINDS AND" "HAIL/ICY ROADS"
[472] "FLASH FLOOD/HEAVY RAIN" "HEAVY RAIN; URBAN FLOOD WINDS;" "HEAVY PRECIPITATION"
[475] "TSTM WIND DAMAGE" "HIGH WATER" "FLOOD FLASH"
[478] "RAIN/WIND" "THUNDERSTORM WINDS 50" "THUNDERSTORM WIND G52"
[481] "FLOOD FLOOD/FLASH" "THUNDERSTORM WINDS 52" "SNOW SHOWERS"
[484] "THUNDERSTORM WIND G51" "HEAT WAVE DROUGHT" "HEAVY SNOW/BLIZZARD/AVALANCHE"
[487] "RECORD SNOW/COLD" "WET WEATHER" "UNSEASONABLY WARM AND DRY"
[490] "FREEZING RAIN SLEET AND LIGHT" "RECORD/EXCESSIVE RAINFALL" "TIDAL FLOOD"
[493] "BEACH EROSIN" "THUNDERSTORM WIND G61" "FLOOD/FLASH"
[496] "LOW TEMPERATURE" "SLEET & FREEZING RAIN" "HEAVY RAINS/FLOODING"
[499] "THUNDERESTORM WINDS" "THUNDERSTORM WINDS/FLOODING" "THUNDEERSTORM WINDS"
[502] "HIGHWAY FLOODING" "THUNDERSTORM W INDS" "HYPOTHERMIA"
[505] "FLASH FLOOD/ FLOOD" "THUNDERSTORM WIND 50" "THUNERSTORM WINDS"
[508] "HEAVY RAIN/MUDSLIDES/FLOOD" "MUD/ROCK SLIDE" "HIGH WINDS/COLD"
[511] "BEACH EROSION/COASTAL FLOOD" "COLD/WINDS" "SNOW/ BITTER COLD"
[514] "THUNDERSTORM WIND 56" "SNOW SLEET" "DRY HOT WEATHER"
[517] "COLD WEATHER" "RAPIDLY RISING WATER" "HAIL ALOFT"
[520] "EARLY FREEZE" "ICE/STRONG WINDS" "EXTREME WIND CHILL/BLOWING SNO"
[523] "SNOW/HIGH WINDS" "HIGH WINDS/SNOW" "EARLY FROST"
[526] "SNOWMELT FLOODING" "HEAVY SNOW AND STRONG WINDS" "SNOW ACCUMULATION"
[529] "BLOWING SNOW/EXTREME WIND CHIL" "SNOW/ ICE" "SNOW/BLOWING SNOW"
[532] "TORNADOES" "THUNDERSTORM WIND/HAIL" "FLASH FLOODING/FLOOD"
[535] "HAIL 275" "HAIL 450" "FLASH FLOOODING"
[538] "EXCESSIVE RAINFALL" "THUNDERSTORMW" "HAILSTORM"
[541] "TSTM WINDS" "BEACH FLOOD" "HAILSTORMS"
[544] "TSTMW" "FUNNELS" "TSTM WIND 65)"
[547] "THUNDERSTORM WINDS/ FLOOD" "HEAVY RAINFALL" "HEAT/DROUGHT"
[550] "HEAT DROUGHT" "NEAR RECORD SNOW" "LANDSLIDE"
[553] "HIGH WIND AND SEAS" "THUNDERSTORMWINDS" "THUNDERSTORM WINDS HEAVY RAIN"
[556] "SLEET/SNOW" "EXCESSIVE" "SNOW/SLEET/RAIN"
[559] "WILD/FOREST FIRES" "HEAVY SEAS" "DUSTSTORM"
[562] "FLOOD & HEAVY RAIN" "?" "THUNDERSTROM WIND"
[565] "FLOOD/FLASHFLOOD" "SNOW AND COLD" "HOT PATTERN"
[568] "PROLONG COLD/SNOW" "BRUSH FIRES" "SNOW\\COLD"
[571] "WINTER MIX" "EXCESSIVE PRECIPITATION" "SNOWFALL RECORD"
[574] "HOT/DRY PATTERN" "DRY PATTERN" "MILD/DRY PATTERN"
[577] "MILD PATTERN" "LANDSLIDES" "HEAVY SHOWERS"
[580] "HEAVY SNOW AND" "HIGH WIND 48" "LAKE-EFFECT SNOW"
[583] "BRUSH FIRE" "WATERSPOUT FUNNEL CLOUD" "URBAN SMALL STREAM FLOOD"
[586] "SAHARAN DUST" "HEAVY SHOWER" "URBAN FLOOD LANDSLIDE"
[589] "HEAVY SWELLS" "URBAN SMALL" "URBAN FLOODS"
[592] "SMALL STREAM" "HEAVY RAIN/URBAN FLOOD" "FLASH FLOOD/LANDSLIDE"
[595] "LANDSLIDE/URBAN FLOOD" "HEAVY RAIN/SMALL STREAM URBAN" "FLASH FLOOD LANDSLIDES"
[598] "EXTREME WINDCHILL" "URBAN/SML STREAM FLD" "TSTM WIND/HAIL"
[601] "RECORD DRY MONTH" "TEMPERATURE RECORD" "ICE JAM FLOOD (MINOR"
[604] "ROUGH SURF" "MARINE ACCIDENT" "COASTAL STORM"
[607] "COASTALFLOOD" "EROSION/CSTL FLOOD" "HEAVY RAIN AND WIND"
[610] "LIGHT SNOW/FLURRIES" "WET MONTH" "WET YEAR"
[613] "TIDAL FLOODING" "BEACH EROSION" "HOT AND DRY"
[616] "HEAVY RAIN/HIGH SURF" "RAIN DAMAGE" "UNSEASONABLE COLD"
[619] "STREET FLOODING" "ICE FOG" "EXCESSIVE COLD"
[622] "TORRENTIAL RAINFALL" "LANDSLUMP" "LATE-SEASON SNOWFALL"
[625] "HURRICANE EDOUARD" "HEAVY RAIN/WIND" "RECORD WARM TEMPS."
[628] "EXTENDED COLD" "FREEZING FOG" "DRIFTING SNOW"
[631] "WHIRLWIND" "HEAVY SNOW SHOWER" "LATE SNOW"
[634] "RECORD MAY SNOW" "RECORD WINTER SNOW" "RECORD TEMPERATURE"
[637] "LATE SEASON SNOWFALL" "GUSTY WIND" "MIXED PRECIP"
[640] "BLACK ICE" "GRADIENT WIND" "FREEZING SPRAY"
[643] "SUMMARY JAN 17" "SUMMARY OF MARCH 14" "SUMMARY OF MARCH 23"
[646] "SUMMARY OF MARCH 24" "SUMMARY OF APRIL 3RD" "SUMMARY OF APRIL 12"
[649] "SUMMARY OF APRIL 13" "SUMMARY OF APRIL 21" "SUMMARY AUGUST 11"
[652] "SUMMARY OF APRIL 27" "SUMMARY OF MAY 9-10" "SUMMARY OF MAY 10"
[655] "SUMMARY OF MAY 13" "SUMMARY OF MAY 14" "SUMMARY OF MAY 22 AM"
[658] "SUMMARY OF MAY 22 PM" "HEATBURST" "SUMMARY OF MAY 26 AM"
[661] "SUMMARY OF MAY 26 PM" "METRO STORM, MAY 26" "SUMMARY OF MAY 31 AM"
[664] "SUMMARY OF MAY 31 PM" "SUMMARY OF JUNE 3" "SUMMARY OF JUNE 4"
[667] "SUMMARY JUNE 5-6" "SUMMARY JUNE 6" "SUMMARY OF JUNE 11"
[670] "SUMMARY OF JUNE 12" "SUMMARY OF JUNE 13" "SUMMARY OF JUNE 15"
[673] "SUMMARY OF JUNE 16" "SUMMARY JUNE 18-19" "SUMMARY OF JUNE 23"
[676] "SUMMARY OF JUNE 24" "SUMMARY OF JUNE 30" "SUMMARY OF JULY 2"
[679] "SUMMARY OF JULY 3" "SUMMARY OF JULY 11" "SUMMARY OF JULY 22"
[682] "SUMMARY JULY 23-24" "SUMMARY OF JULY 26" "SUMMARY OF JULY 29"
[685] "SUMMARY OF AUGUST 1" "SUMMARY AUGUST 2-3" "SUMMARY AUGUST 7"
[688] "SUMMARY AUGUST 9" "SUMMARY AUGUST 10" "SUMMARY AUGUST 17"
[691] "SUMMARY AUGUST 21" "SUMMARY AUGUST 28" "SUMMARY SEPTEMBER 4"
[694] "SUMMARY SEPTEMBER 20" "SUMMARY SEPTEMBER 23" "SUMMARY SEPT. 25-26"
[697] "SUMMARY: OCT. 20-21" "SUMMARY: OCTOBER 31" "SUMMARY: NOV. 6-7"
[700] "SUMMARY: NOV. 16" "WET MICOBURST" "HAIL(0.75)"
[703] "NO SEVERE WEATHER" "SUMMARY OF MAY 22" "SUMMARY OF JUNE 6"
[706] "SUMMARY AUGUST 4" "SUMMARY OF JUNE 10" "SUMMARY OF JUNE 18"
[709] "SUMMARY SEPTEMBER 3" "SUMMARY: SEPT. 18" "LIGHT SNOWFALL"
[712] "GUSTY WIND/RAIN" "GUSTY WIND/HVY RAIN" "EARLY SNOWFALL"
[715] "MONTHLY SNOWFALL" "SEASONAL SNOWFALL" "MONTHLY RAINFALL"
[718] "COLD TEMPERATURE" "SML STREAM FLD" "MUDSLIDE/LANDSLIDE"
[721] "VOLCANIC ASH" "VOLCANIC ASH PLUME" "THUNDERSNOW SHOWER"
[724] "NONE" "COLD AND SNOW" "DAM BREAK"
[727] "TSTM WIND (G45)" "SLEET/FREEZING RAIN" "BLOW-OUT TIDES"
[730] "UNSEASONABLY COOL" "TSTM HEAVY RAIN" "TSTM WIND 40"
[733] "TSTM WIND 45" "TSTM WIND (41)" "TSTM WIND (G40)"
[736] "TSTM WND" "FROST/FREEZE" "RAIN (HEAVY)"
[739] "COLD AND FROST" "URBAN/SML STREAM FLDG" "STRONG WIND GUST"
[742] "LATE FREEZE" "BLOW-OUT TIDE" "HYPOTHERMIA/EXPOSURE"
[745] "MIXED PRECIPITATION" "COASTALSTORM" "SNOW AND SLEET"
[748] "BLIZZARD SUMMARY" "SUMMARY OF MARCH 24-25" "SUMMARY OF MARCH 27"
[751] "SUMMARY OF MARCH 29" "ICESTORM/BLIZZARD" "FLOOD/STRONG WIND"
[754] "TSTM WIND AND LIGHTNING" "MOUNTAIN SNOWS" "URBAN/SMALL STRM FLDG"
[757] "HEAVY SURF AND WIND" "MILD AND DRY PATTERN" "TYPHOON"
[760] "HIGH SWELLS" "HIGH SWELLS" "DRY SPELL"
[763] "UNSEASONAL RAIN" "EARLY RAIN" "PROLONGED RAIN"
[766] "WINTERY MIX" "COASTAL FLOODING/EROSION" "HOT SPELL"
[769] "UNSEASONABLY HOT" "TSTM WIND (G45)" "HIGH WIND (G40)"
[772] "TSTM WIND (G35)" "DRY WEATHER" "ABNORMAL WARMTH"
[775] "UNUSUAL WARMTH" "WAKE LOW WIND" "COLD TEMPERATURES"
[778] "COLD WIND CHILL TEMPERATURES" "MODERATE SNOW" "MODERATE SNOWFALL"
[781] "URBAN/STREET FLOODING" "COASTAL EROSION" "UNUSUAL/RECORD WARMTH"
[784] "BITTER WIND CHILL" "BITTER WIND CHILL TEMPERATURES" "SEICHE"
[787] "TSTM" "COASTAL FLOODING/EROSION" "UNSEASONABLY WARM YEAR"
[790] "HYPERTHERMIA/EXPOSURE" "ROCK SLIDE" "ICE PELLETS"
[793] "PATCHY DENSE FOG" "RECORD COOL" "RECORD WARM"
[796] "HOT WEATHER" "TROPICAL DEPRESSION" "VOLCANIC ERUPTION"
[799] "COOL SPELL" "WIND ADVISORY" "GUSTY WIND/HAIL"
[802] "RED FLAG FIRE WX" "FIRST FROST" "EXCESSIVELY DRY"
[805] "LIGHT SNOW/FREEZING PRECIP" "VOG" "MONTHLY PRECIPITATION"
[808] "MONTHLY TEMPERATURE" "RECORD DRYNESS" "EXTREME WINDCHILL TEMPERATURES"
[811] "DRY CONDITIONS" "REMNANTS OF FLOYD" "LANDSPOUT"
[814] "DRIEST MONTH" "RECORD COLD" "LATE SEASON HAIL"
[817] "EXCESSIVE SNOW" "DRYNESS" "FLOOD/FLASH/FLOOD"
[820] "WIND AND WAVE" "LIGHT FREEZING RAIN" "RECORD PRECIPITATION"
[823] "ICE ROADS" "ROUGH SEAS" "UNSEASONABLY WARM/WET"
[826] "UNSEASONABLY COOL & WET" "UNUSUALLY WARM" "TSTM WIND G45"
[829] "NON SEVERE HAIL" "NON-SEVERE WIND DAMAGE" "UNUSUALLY COLD"
[832] "WARM WEATHER" "THUNDERSTORM WIND (G40)" "UNSEASONABLY WARM & WET"
[835] "LOCALLY HEAVY RAIN" "WIND GUSTS" "UNSEASONAL LOW TEMP"
[838] "HIGH SURF ADVISORY" "LATE SEASON SNOW" "GUSTY LAKE WIND"
[841] "ABNORMALLY DRY" "WINTER WEATHER MIX" "RED FLAG CRITERIA"
[844] "CSTL FLOODING/EROSION" "SMOKE" "SNOW ADVISORY"
[847] "EXTREMELY WET" "UNUSUALLY LATE SNOW" "VERY DRY"
[850] "RECORD LOW RAINFALL" "ROGUE WAVE" "PROLONG WARMTH"
[853] "ACCUMULATED SNOWFALL" "FALLING SNOW/ICE" "DUST DEVEL"
[856] "NON-TSTM WIND" "NON TSTM WIND" "GUSTY THUNDERSTORM WINDS"
[859] "PATCHY ICE" "HEAVY RAIN EFFECTS" "EXCESSIVE HEAT/DROUGHT"
[862] "NORTHERN LIGHTS" "MARINE TSTM WIND" "HAZARDOUS SURF"
[865] "WINTER WEATHER/MIX" "ASTRONOMICAL HIGH TIDE" "VERY WARM"
[868] "ABNORMALLY WET" "TORNADO DEBRIS" "EXTREME COLD/WIND CHILL"
[871] "ICE ON ROAD" "DROWNING" "GUSTY THUNDERSTORM WIND"
[874] "MARINE HAIL" "HIGH SURF ADVISORIES" "HURRICANE/TYPHOON"
[877] "HEAVY SURF/HIGH SURF" "SLEET STORM" "STORM SURGE/TIDE"
[880] "COLD/WIND CHILL" "MARINE HIGH WIND" "TSUNAMI"
[883] "DENSE SMOKE" "LAKESHORE FLOOD" "MARINE THUNDERSTORM WIND"
[886] "MARINE STRONG WIND" "ASTRONOMICAL LOW TIDE" "VOLCANIC ASHFALL" There are some abbreviations. TSTM, CSTL, HVY, FLD. Let’s replace them with proper words: THUNDERSTROM, COASTAL, HEAVY and FLOOD respectively.
data$EVTYPE <- gsub("TSTM*","THUNDERSTORM", data$EVTYPE)
data$EVTYPE <- gsub("CSTL*","COASTAL", data$EVTYPE)
data$EVTYPE <- gsub("HVY*","HEAVY", data$EVTYPE)
data$EVTYPE <- gsub("FLD*","FLOOD", data$EVTYPE)sort(unique(data$EVTYPE)) [1] "?" "ABNORMAL WARMTH"
[3] "ABNORMALLY DRY" "ABNORMALLY WET"
[5] "ACCUMULATED SNOWFALL" "AGRICULTURAL FREEZE"
[7] "APACHE COUNTY" "ASTRONOMICAL HIGH TIDE"
[9] "ASTRONOMICAL LOW TIDE" "AVALANCE"
[11] "AVALANCHE" "BEACH EROSIN"
[13] "BEACH EROSION" "BEACH EROSION/COASTAL FLOODOOD"
[15] "BEACH FLOODOOD" "BELOW NORMAL PRECIPITATION"
[17] "BITTER WIND CHILL" "BITTER WIND CHILL TEMPERATURES"
[19] "BLACK ICE" "BLIZZARD"
[21] "BLIZZARD AND EXTREME WIND CHIL" "BLIZZARD AND HEAVY SNOW"
[23] "BLIZZARD SUMMARY" "BLIZZARD WEATHER"
[25] "BLIZZARD/FREEZING RAIN" "BLIZZARD/HEAVY SNOW"
[27] "BLIZZARD/HIGH WIND" "BLIZZARD/WINTER STORM"
[29] "BLOW-OUT TIDE" "BLOW-OUT TIDES"
[31] "BLOWING DUST" "BLOWING SNOW"
[33] "BLOWING SNOW- EXTREME WIND CHI" "BLOWING SNOW & EXTREME WIND CH"
[35] "BLOWING SNOW/EXTREME WIND CHIL" "BREAKUP FLOODOODING"
[37] "BRUSH FIRE" "BRUSH FIRES"
[39] "COASTAL FLOODOODING/EROSION" "COASTAL EROSION"
[41] "COASTAL FLOODOOD" "COASTAL FLOODOODING"
[43] "COASTAL FLOODOODING/EROSION" "COASTAL STORM"
[45] "COASTAL SURGE" "COASTAL/TIDAL FLOODOOD"
[47] "COASTALFLOODOOD" "COASTALSTORM"
[49] "COLD" "COLD AIR FUNNEL"
[51] "COLD AIR FUNNELS" "COLD AIR TORNADO"
[53] "COLD AND FROST" "COLD AND SNOW"
[55] "COLD AND WET CONDITIONS" "COLD TEMPERATURE"
[57] "COLD TEMPERATURES" "COLD WAVE"
[59] "COLD WEATHER" "COLD WIND CHILL TEMPERATURES"
[61] "COLD/WIND CHILL" "COLD/WINDS"
[63] "COOL AND WET" "COOL SPELL"
[65] "DAM BREAK" "DAM FAILURE"
[67] "DAMAGING FREEZE" "DEEP HAIL"
[69] "DENSE FOG" "DENSE SMOKE"
[71] "DOWNBURST" "DOWNBURST WINDS"
[73] "DRIEST MONTH" "DRIFTING SNOW"
[75] "DROUGHT" "DROUGHT/EXCESSIVE HEAT"
[77] "DROWNING" "DRY"
[79] "DRY CONDITIONS" "DRY HOT WEATHER"
[81] "DRY MICROBURST" "DRY MICROBURST 50"
[83] "DRY MICROBURST 53" "DRY MICROBURST 58"
[85] "DRY MICROBURST 61" "DRY MICROBURST 84"
[87] "DRY MICROBURST WINDS" "DRY MIRCOBURST WINDS"
[89] "DRY PATTERN" "DRY SPELL"
[91] "DRY WEATHER" "DRYNESS"
[93] "DUST DEVEL" "DUST DEVIL"
[95] "DUST DEVIL WATERSPOUT" "DUST STORM"
[97] "DUST STORM/HIGH WINDS" "DUSTHUNDERSTORMORM"
[99] "EARLY FREEZE" "EARLY FROST"
[101] "EARLY RAIN" "EARLY SNOW"
[103] "EARLY SNOWFALL" "EROSION/COASTAL FLOODOOD"
[105] "EXCESSIVE" "EXCESSIVE COLD"
[107] "EXCESSIVE HEAT" "EXCESSIVE HEAT/DROUGHT"
[109] "EXCESSIVE PRECIPITATION" "EXCESSIVE RAIN"
[111] "EXCESSIVE RAINFALL" "EXCESSIVE SNOW"
[113] "EXCESSIVE WETNESS" "EXCESSIVELY DRY"
[115] "EXTENDED COLD" "EXTREME COLD"
[117] "EXTREME COLD/WIND CHILL" "EXTREME HEAT"
[119] "EXTREME WIND CHILL" "EXTREME WIND CHILL/BLOWING SNO"
[121] "EXTREME WIND CHILLS" "EXTREME WINDCHILL"
[123] "EXTREME WINDCHILL TEMPERATURES" "EXTREME/RECORD COLD"
[125] "EXTREMELY WET" "FALLING SNOW/ICE"
[127] "FIRST FROST" "FIRST SNOW"
[129] "FLOODASH FLOODOOD" "FLOODASH FLOODOOD - HEAVY RAIN"
[131] "FLOODASH FLOODOOD FROM ICE JAMS" "FLOODASH FLOODOOD LANDSLIDES"
[133] "FLOODASH FLOODOOD WINDS" "FLOODASH FLOODOOD/"
[135] "FLOODASH FLOODOOD/ FLOODOOD" "FLOODASH FLOODOOD/ STREET"
[137] "FLOODASH FLOODOOD/FLOODOOD" "FLOODASH FLOODOOD/HEAVY RAIN"
[139] "FLOODASH FLOODOOD/LANDSLIDE" "FLOODASH FLOODOODING"
[141] "FLOODASH FLOODOODING/FLOODOOD" "FLOODASH FLOODOODING/THUNDERSTORM WI"
[143] "FLOODASH FLOODOODS" "FLOODASH FLOODOOODING"
[145] "FLOODOOD" "FLOODOOD & HEAVY RAIN"
[147] "FLOODOOD FLOODASH" "FLOODOOD FLOODOOD/FLOODASH"
[149] "FLOODOOD WATCH/" "FLOODOOD/FLOODASH"
[151] "FLOODOOD/FLOODASH FLOODOOD" "FLOODOOD/FLOODASH FLOODOODING"
[153] "FLOODOOD/FLOODASH/FLOODOOD" "FLOODOOD/FLOODASHFLOODOOD"
[155] "FLOODOOD/RAIN/WIND" "FLOODOOD/RAIN/WINDS"
[157] "FLOODOOD/RIVER FLOODOOD" "FLOODOOD/STRONG WIND"
[159] "FLOODOODING" "FLOODOODING/HEAVY RAIN"
[161] "FLOODOODS" "FOG"
[163] "FOG AND COLD TEMPERATURES" "FOREST FIRES"
[165] "FREEZE" "FREEZING DRIZZLE"
[167] "FREEZING DRIZZLE AND FREEZING" "FREEZING FOG"
[169] "FREEZING RAIN" "FREEZING RAIN AND SLEET"
[171] "FREEZING RAIN AND SNOW" "FREEZING RAIN SLEET AND"
[173] "FREEZING RAIN SLEET AND LIGHT" "FREEZING RAIN/SLEET"
[175] "FREEZING RAIN/SNOW" "FREEZING SPRAY"
[177] "FROST" "FROST/FREEZE"
[179] "FROST\\FREEZE" "FUNNEL"
[181] "FUNNEL CLOUD" "FUNNEL CLOUD."
[183] "FUNNEL CLOUD/HAIL" "FUNNEL CLOUDS"
[185] "FUNNELS" "GLAZE"
[187] "GLAZE ICE" "GLAZE/ICE STORM"
[189] "GRADIENT WIND" "GRADIENT WINDS"
[191] "GRASS FIRES" "GROUND BLIZZARD"
[193] "GUSTNADO" "GUSTNADO AND"
[195] "GUSTY LAKE WIND" "GUSTY THUNDERSTORM WIND"
[197] "GUSTY THUNDERSTORM WINDS" "GUSTY WIND"
[199] "GUSTY WIND/HAIL" "GUSTY WIND/HEAVY RAIN"
[201] "GUSTY WIND/RAIN" "GUSTY WINDS"
[203] "HAIL" "HAIL 0.75"
[205] "HAIL 0.88" "HAIL 075"
[207] "HAIL 088" "HAIL 1.00"
[209] "HAIL 1.75" "HAIL 1.75)"
[211] "HAIL 100" "HAIL 125"
[213] "HAIL 150" "HAIL 175"
[215] "HAIL 200" "HAIL 225"
[217] "HAIL 275" "HAIL 450"
[219] "HAIL 75" "HAIL 80"
[221] "HAIL 88" "HAIL ALOFT"
[223] "HAIL DAMAGE" "HAIL FLOODOODING"
[225] "HAIL STORM" "HAIL(0.75)"
[227] "HAIL/ICY ROADS" "HAIL/WIND"
[229] "HAIL/WINDS" "HAILSTORM"
[231] "HAILSTORMS" "HARD FREEZE"
[233] "HAZARDOUS SURF" "HEAT"
[235] "HEAT DROUGHT" "HEAT WAVE"
[237] "HEAT WAVE DROUGHT" "HEAT WAVES"
[239] "HEAT/DROUGHT" "HEATBURST"
[241] "HEAVY LAKE SNOW" "HEAVY MIX"
[243] "HEAVY PRECIPATATION" "HEAVY PRECIPITATION"
[245] "HEAVY RAIN" "HEAVY RAIN AND FLOODOOD"
[247] "HEAVY RAIN AND WIND" "HEAVY RAIN EFFECTS"
[249] "HEAVY RAIN/FLOODOODING" "HEAVY RAIN/HIGH SURF"
[251] "HEAVY RAIN/LIGHTNING" "HEAVY RAIN/MUDSLIDES/FLOODOOD"
[253] "HEAVY RAIN/SEVERE WEATHER" "HEAVY RAIN/SMALL STREAM URBAN"
[255] "HEAVY RAIN/SNOW" "HEAVY RAIN/URBAN FLOODOOD"
[257] "HEAVY RAIN/WIND" "HEAVY RAIN; URBAN FLOODOOD WINDS;"
[259] "HEAVY RAINFALL" "HEAVY RAINS"
[261] "HEAVY RAINS/FLOODOODING" "HEAVY SEAS"
[263] "HEAVY SHOWER" "HEAVY SHOWERS"
[265] "HEAVY SNOW" "HEAVY SNOW-SQUALLS"
[267] "HEAVY SNOW FREEZING RAIN" "HEAVY SNOW & ICE"
[269] "HEAVY SNOW AND" "HEAVY SNOW AND HIGH WINDS"
[271] "HEAVY SNOW AND ICE" "HEAVY SNOW AND ICE STORM"
[273] "HEAVY SNOW AND STRONG WINDS" "HEAVY SNOW ANDBLOWING SNOW"
[275] "HEAVY SNOW SHOWER" "HEAVY SNOW SQUALLS"
[277] "HEAVY SNOW/BLIZZARD" "HEAVY SNOW/BLIZZARD/AVALANCHE"
[279] "HEAVY SNOW/BLOWING SNOW" "HEAVY SNOW/FREEZING RAIN"
[281] "HEAVY SNOW/HIGH" "HEAVY SNOW/HIGH WIND"
[283] "HEAVY SNOW/HIGH WINDS" "HEAVY SNOW/HIGH WINDS & FLOODOOD"
[285] "HEAVY SNOW/HIGH WINDS/FREEZING" "HEAVY SNOW/ICE"
[287] "HEAVY SNOW/ICE STORM" "HEAVY SNOW/SLEET"
[289] "HEAVY SNOW/SQUALLS" "HEAVY SNOW/WIND"
[291] "HEAVY SNOW/WINTER STORM" "HEAVY SNOWPACK"
[293] "HEAVY SURF" "HEAVY SURF AND WIND"
[295] "HEAVY SURF COASTAL FLOODOODING" "HEAVY SURF/HIGH SURF"
[297] "HEAVY SWELLS" "HEAVY WET SNOW"
[299] "HIGH" "HIGH SWELLS"
[301] "HIGH WINDS" "HIGH SEAS"
[303] "HIGH SURF" "HIGH SURF ADVISORIES"
[305] "HIGH SURF ADVISORY" "HIGH SWELLS"
[307] "HIGH TEMPERATURE RECORD" "HIGH TIDES"
[309] "HIGH WATER" "HIGH WAVES"
[311] "HIGH WIND" "HIGH WIND (G40)"
[313] "HIGH WIND 48" "HIGH WIND 63"
[315] "HIGH WIND 70" "HIGH WIND AND HEAVY SNOW"
[317] "HIGH WIND AND HIGH TIDES" "HIGH WIND AND SEAS"
[319] "HIGH WIND DAMAGE" "HIGH WIND/ BLIZZARD"
[321] "HIGH WIND/BLIZZARD" "HIGH WIND/BLIZZARD/FREEZING RA"
[323] "HIGH WIND/HEAVY SNOW" "HIGH WIND/LOW WIND CHILL"
[325] "HIGH WIND/SEAS" "HIGH WIND/WIND CHILL"
[327] "HIGH WIND/WIND CHILL/BLIZZARD" "HIGH WINDS"
[329] "HIGH WINDS 55" "HIGH WINDS 57"
[331] "HIGH WINDS 58" "HIGH WINDS 63"
[333] "HIGH WINDS 66" "HIGH WINDS 67"
[335] "HIGH WINDS 73" "HIGH WINDS 76"
[337] "HIGH WINDS 80" "HIGH WINDS 82"
[339] "HIGH WINDS AND WIND CHILL" "HIGH WINDS DUST STORM"
[341] "HIGH WINDS HEAVY RAINS" "HIGH WINDS/"
[343] "HIGH WINDS/COASTAL FLOODOOD" "HIGH WINDS/COLD"
[345] "HIGH WINDS/FLOODOODING" "HIGH WINDS/HEAVY RAIN"
[347] "HIGH WINDS/SNOW" "HIGHWAY FLOODOODING"
[349] "HOT AND DRY" "HOT PATTERN"
[351] "HOT SPELL" "HOT WEATHER"
[353] "HOT/DRY PATTERN" "HURRICANE"
[355] "HURRICANE-GENERATED SWELLS" "HURRICANE EDOUARD"
[357] "HURRICANE EMILY" "HURRICANE ERIN"
[359] "HURRICANE FELIX" "HURRICANE GORDON"
[361] "HURRICANE OPAL" "HURRICANE OPAL/HIGH WINDS"
[363] "HURRICANE/TYPHOON" "HYPERTHERMIA/EXPOSURE"
[365] "HYPOTHERMIA" "HYPOTHERMIA/EXPOSURE"
[367] "ICE" "ICE AND SNOW"
[369] "ICE FLOODOES" "ICE FOG"
[371] "ICE JAM" "ICE JAM FLOODOOD (MINOR"
[373] "ICE JAM FLOODOODING" "ICE ON ROAD"
[375] "ICE PELLETS" "ICE ROADS"
[377] "ICE STORM" "ICE STORM AND SNOW"
[379] "ICE STORM/FLOODASH FLOODOOD" "ICE/SNOW"
[381] "ICE/STRONG WINDS" "ICESTORM/BLIZZARD"
[383] "ICY ROADS" "LACK OF SNOW"
[385] "LAKE-EFFECT SNOW" "LAKE EFFECT SNOW"
[387] "LAKE FLOODOOD" "LAKESHORE FLOODOOD"
[389] "LANDSLIDE" "LANDSLIDE/URBAN FLOODOOD"
[391] "LANDSLIDES" "LANDSLUMP"
[393] "LANDSPOUT" "LARGE WALL CLOUD"
[395] "LATE-SEASON SNOWFALL" "LATE FREEZE"
[397] "LATE SEASON HAIL" "LATE SEASON SNOW"
[399] "LATE SEASON SNOWFALL" "LATE SNOW"
[401] "LIGHT FREEZING RAIN" "LIGHT SNOW"
[403] "LIGHT SNOW AND SLEET" "LIGHT SNOW/FLOODURRIES"
[405] "LIGHT SNOW/FREEZING PRECIP" "LIGHT SNOWFALL"
[407] "LIGHTING" "LIGHTNING"
[409] "LIGHTNING WAUSEON" "LIGHTNING AND HEAVY RAIN"
[411] "LIGHTNING AND THUNDERSTORM WIN" "LIGHTNING AND WINDS"
[413] "LIGHTNING DAMAGE" "LIGHTNING FIRE"
[415] "LIGHTNING INJURY" "LIGHTNING THUNDERSTORM WINDS"
[417] "LIGHTNING THUNDERSTORM WINDSS" "LIGHTNING."
[419] "LIGHTNING/HEAVY RAIN" "LIGNTNING"
[421] "LOCAL FLOODASH FLOODOOD" "LOCAL FLOODOOD"
[423] "LOCALLY HEAVY RAIN" "LOW TEMPERATURE"
[425] "LOW TEMPERATURE RECORD" "LOW WIND CHILL"
[427] "MAJOR FLOODOOD" "MARINE ACCIDENT"
[429] "MARINE HAIL" "MARINE HIGH WIND"
[431] "MARINE MISHAP" "MARINE STRONG WIND"
[433] "MARINE THUNDERSTORM WIND" "METRO STORM, MAY 26"
[435] "MICROBURST" "MICROBURST WINDS"
[437] "MILD AND DRY PATTERN" "MILD PATTERN"
[439] "MILD/DRY PATTERN" "MINOR FLOODOOD"
[441] "MINOR FLOODOODING" "MIXED PRECIP"
[443] "MIXED PRECIPITATION" "MODERATE SNOW"
[445] "MODERATE SNOWFALL" "MONTHLY PRECIPITATION"
[447] "MONTHLY RAINFALL" "MONTHLY SNOWFALL"
[449] "MONTHLY TEMPERATURE" "MOUNTAIN SNOWS"
[451] "MUD SLIDE" "MUD SLIDES"
[453] "MUD SLIDES URBAN FLOODOODING" "MUD/ROCK SLIDE"
[455] "MUDSLIDE" "MUDSLIDE/LANDSLIDE"
[457] "MUDSLIDES" "NEAR RECORD SNOW"
[459] "NO SEVERE WEATHER" "NON-SEVERE WIND DAMAGE"
[461] "NON-THUNDERSTORM WIND" "NON SEVERE HAIL"
[463] "NON THUNDERSTORM WIND" "NONE"
[465] "NORMAL PRECIPITATION" "NORTHERN LIGHTS"
[467] "OTHER" "PATCHY DENSE FOG"
[469] "PATCHY ICE" "PROLONG COLD"
[471] "PROLONG COLD/SNOW" "PROLONG WARMTH"
[473] "PROLONGED RAIN" "RAIN"
[475] "RAIN (HEAVY)" "RAIN AND WIND"
[477] "RAIN DAMAGE" "RAIN/SNOW"
[479] "RAIN/WIND" "RAINSTORM"
[481] "RAPIDLY RISING WATER" "RECORD COLD"
[483] "RECORD COLD" "RECORD COLD AND HIGH WIND"
[485] "RECORD COLD/FROST" "RECORD COOL"
[487] "RECORD DRY MONTH" "RECORD DRYNESS"
[489] "RECORD HEAT" "RECORD HEAT WAVE"
[491] "RECORD HIGH" "RECORD HIGH TEMPERATURE"
[493] "RECORD HIGH TEMPERATURES" "RECORD LOW"
[495] "RECORD LOW RAINFALL" "RECORD MAY SNOW"
[497] "RECORD PRECIPITATION" "RECORD RAINFALL"
[499] "RECORD SNOW" "RECORD SNOW/COLD"
[501] "RECORD SNOWFALL" "RECORD TEMPERATURE"
[503] "RECORD TEMPERATURES" "RECORD WARM"
[505] "RECORD WARM TEMPS." "RECORD WARMTH"
[507] "RECORD WINTER SNOW" "RECORD/EXCESSIVE HEAT"
[509] "RECORD/EXCESSIVE RAINFALL" "RED FLOODAG CRITERIA"
[511] "RED FLOODAG FIRE WX" "REMNANTS OF FLOODOYD"
[513] "RIP CURRENT" "RIP CURRENTS"
[515] "RIP CURRENTS HEAVY SURF" "RIP CURRENTS/HEAVY SURF"
[517] "RIVER AND STREAM FLOODOOD" "RIVER FLOODOOD"
[519] "RIVER FLOODOODING" "ROCK SLIDE"
[521] "ROGUE WAVE" "ROTATING WALL CLOUD"
[523] "ROUGH SEAS" "ROUGH SURF"
[525] "RURAL FLOODOOD" "SAHARAN DUST"
[527] "SEASONAL SNOWFALL" "SEICHE"
[529] "SEVERE COLD" "SEVERE THUNDERSTORM"
[531] "SEVERE THUNDERSTORM WINDS" "SEVERE THUNDERSTORMS"
[533] "SEVERE TURBULENCE" "SLEET"
[535] "SLEET & FREEZING RAIN" "SLEET STORM"
[537] "SLEET/FREEZING RAIN" "SLEET/ICE STORM"
[539] "SLEET/RAIN/SNOW" "SLEET/SNOW"
[541] "SMALL HAIL" "SMALL STREAM"
[543] "SMALL STREAM AND" "SMALL STREAM AND URBAN FLOODOOD"
[545] "SMALL STREAM AND URBAN FLOODOODIN" "SMALL STREAM FLOODOOD"
[547] "SMALL STREAM FLOODOODING" "SMALL STREAM URBAN FLOODOOD"
[549] "SMALL STREAM/URBAN FLOODOOD" "SML STREAM FLOOD"
[551] "SMOKE" "SNOW"
[553] "SNOW- HIGH WIND- WIND CHILL" "SNOW ACCUMULATION"
[555] "SNOW ADVISORY" "SNOW AND COLD"
[557] "SNOW AND HEAVY SNOW" "SNOW AND ICE"
[559] "SNOW AND ICE STORM" "SNOW AND SLEET"
[561] "SNOW AND WIND" "SNOW DROUGHT"
[563] "SNOW FREEZING RAIN" "SNOW SHOWERS"
[565] "SNOW SLEET" "SNOW SQUALL"
[567] "SNOW SQUALLS" "SNOW/ BITTER COLD"
[569] "SNOW/ ICE" "SNOW/BLOWING SNOW"
[571] "SNOW/COLD" "SNOW/FREEZING RAIN"
[573] "SNOW/HEAVY SNOW" "SNOW/HIGH WINDS"
[575] "SNOW/ICE" "SNOW/ICE STORM"
[577] "SNOW/RAIN" "SNOW/RAIN/SLEET"
[579] "SNOW/SLEET" "SNOW/SLEET/FREEZING RAIN"
[581] "SNOW/SLEET/RAIN" "SNOW\\COLD"
[583] "SNOWFALL RECORD" "SNOWMELT FLOODOODING"
[585] "SNOWSTORM" "SOUTHEAST"
[587] "STORM FORCE WINDS" "STORM SURGE"
[589] "STORM SURGE/TIDE" "STREAM FLOODOODING"
[591] "STREET FLOODOOD" "STREET FLOODOODING"
[593] "STRONG WIND" "STRONG WIND GUST"
[595] "STRONG WINDS" "SUMMARY AUGUST 10"
[597] "SUMMARY AUGUST 11" "SUMMARY AUGUST 17"
[599] "SUMMARY AUGUST 2-3" "SUMMARY AUGUST 21"
[601] "SUMMARY AUGUST 28" "SUMMARY AUGUST 4"
[603] "SUMMARY AUGUST 7" "SUMMARY AUGUST 9"
[605] "SUMMARY JAN 17" "SUMMARY JULY 23-24"
[607] "SUMMARY JUNE 18-19" "SUMMARY JUNE 5-6"
[609] "SUMMARY JUNE 6" "SUMMARY OF APRIL 12"
[611] "SUMMARY OF APRIL 13" "SUMMARY OF APRIL 21"
[613] "SUMMARY OF APRIL 27" "SUMMARY OF APRIL 3RD"
[615] "SUMMARY OF AUGUST 1" "SUMMARY OF JULY 11"
[617] "SUMMARY OF JULY 2" "SUMMARY OF JULY 22"
[619] "SUMMARY OF JULY 26" "SUMMARY OF JULY 29"
[621] "SUMMARY OF JULY 3" "SUMMARY OF JUNE 10"
[623] "SUMMARY OF JUNE 11" "SUMMARY OF JUNE 12"
[625] "SUMMARY OF JUNE 13" "SUMMARY OF JUNE 15"
[627] "SUMMARY OF JUNE 16" "SUMMARY OF JUNE 18"
[629] "SUMMARY OF JUNE 23" "SUMMARY OF JUNE 24"
[631] "SUMMARY OF JUNE 3" "SUMMARY OF JUNE 30"
[633] "SUMMARY OF JUNE 4" "SUMMARY OF JUNE 6"
[635] "SUMMARY OF MARCH 14" "SUMMARY OF MARCH 23"
[637] "SUMMARY OF MARCH 24" "SUMMARY OF MARCH 24-25"
[639] "SUMMARY OF MARCH 27" "SUMMARY OF MARCH 29"
[641] "SUMMARY OF MAY 10" "SUMMARY OF MAY 13"
[643] "SUMMARY OF MAY 14" "SUMMARY OF MAY 22"
[645] "SUMMARY OF MAY 22 AM" "SUMMARY OF MAY 22 PM"
[647] "SUMMARY OF MAY 26 AM" "SUMMARY OF MAY 26 PM"
[649] "SUMMARY OF MAY 31 AM" "SUMMARY OF MAY 31 PM"
[651] "SUMMARY OF MAY 9-10" "SUMMARY SEPT. 25-26"
[653] "SUMMARY SEPTEMBER 20" "SUMMARY SEPTEMBER 23"
[655] "SUMMARY SEPTEMBER 3" "SUMMARY SEPTEMBER 4"
[657] "SUMMARY: NOV. 16" "SUMMARY: NOV. 6-7"
[659] "SUMMARY: OCT. 20-21" "SUMMARY: OCTOBER 31"
[661] "SUMMARY: SEPT. 18" "TEMPERATURE RECORD"
[663] "THUDERSTORM WINDS" "THUNDEERSTORM WINDS"
[665] "THUNDERESTORM WINDS" "THUNDERSNOW"
[667] "THUNDERSNOW SHOWER" "THUNDERSTORM"
[669] "THUNDERSTORM WINDS" "THUNDERSTORM DAMAGE"
[671] "THUNDERSTORM DAMAGE TO" "THUNDERSTORM HAIL"
[673] "THUNDERSTORM HEAVY RAIN" "THUNDERSTORM W INDS"
[675] "THUNDERSTORM WIND" "THUNDERSTORM WIND (G45)"
[677] "THUNDERSTORM WIND (41)" "THUNDERSTORM WIND (G35)"
[679] "THUNDERSTORM WIND (G40)" "THUNDERSTORM WIND (G45)"
[681] "THUNDERSTORM WIND 40" "THUNDERSTORM WIND 45"
[683] "THUNDERSTORM WIND 50" "THUNDERSTORM WIND 51"
[685] "THUNDERSTORM WIND 52" "THUNDERSTORM WIND 55"
[687] "THUNDERSTORM WIND 56" "THUNDERSTORM WIND 59"
[689] "THUNDERSTORM WIND 59 MPH" "THUNDERSTORM WIND 59 MPH."
[691] "THUNDERSTORM WIND 60 MPH" "THUNDERSTORM WIND 65 MPH"
[693] "THUNDERSTORM WIND 65)" "THUNDERSTORM WIND 65MPH"
[695] "THUNDERSTORM WIND 69" "THUNDERSTORM WIND 98 MPH"
[697] "THUNDERSTORM WIND AND LIGHTNING" "THUNDERSTORM WIND DAMAGE"
[699] "THUNDERSTORM WIND G45" "THUNDERSTORM WIND G50"
[701] "THUNDERSTORM WIND G51" "THUNDERSTORM WIND G52"
[703] "THUNDERSTORM WIND G55" "THUNDERSTORM WIND G58"
[705] "THUNDERSTORM WIND G60" "THUNDERSTORM WIND G61"
[707] "THUNDERSTORM WIND TREES" "THUNDERSTORM WIND."
[709] "THUNDERSTORM WIND/ TREE" "THUNDERSTORM WIND/ TREES"
[711] "THUNDERSTORM WIND/AWNING" "THUNDERSTORM WIND/HAIL"
[713] "THUNDERSTORM WIND/LIGHTNING" "THUNDERSTORM WINDS"
[715] "THUNDERSTORM WINDS LE CEN" "THUNDERSTORM WINDS 13"
[717] "THUNDERSTORM WINDS 2" "THUNDERSTORM WINDS 50"
[719] "THUNDERSTORM WINDS 52" "THUNDERSTORM WINDS 53"
[721] "THUNDERSTORM WINDS 60" "THUNDERSTORM WINDS 61"
[723] "THUNDERSTORM WINDS 62" "THUNDERSTORM WINDS 63 MPH"
[725] "THUNDERSTORM WINDS AND" "THUNDERSTORM WINDS FUNNEL CLOU"
[727] "THUNDERSTORM WINDS G" "THUNDERSTORM WINDS G60"
[729] "THUNDERSTORM WINDS HAIL" "THUNDERSTORM WINDS HEAVY RAIN"
[731] "THUNDERSTORM WINDS LIGHTNING" "THUNDERSTORM WINDS SMALL STREA"
[733] "THUNDERSTORM WINDS URBAN FLOODOOD" "THUNDERSTORM WINDS."
[735] "THUNDERSTORM WINDS/ FLOODOOD" "THUNDERSTORM WINDS/ HAIL"
[737] "THUNDERSTORM WINDS/FLOODASH FLOODOOD" "THUNDERSTORM WINDS/FLOODOODING"
[739] "THUNDERSTORM WINDS/FUNNEL CLOU" "THUNDERSTORM WINDS/HAIL"
[741] "THUNDERSTORM WINDS/HEAVY RAIN" "THUNDERSTORM WINDS53"
[743] "THUNDERSTORM WINDSHAIL" "THUNDERSTORM WINDSS"
[745] "THUNDERSTORM WINS" "THUNDERSTORM WND"
[747] "THUNDERSTORMS" "THUNDERSTORMS WIND"
[749] "THUNDERSTORMS WINDS" "THUNDERSTORMW"
[751] "THUNDERSTORMW 50" "THUNDERSTORMW WINDS"
[753] "THUNDERSTORMWINDS" "THUNDERSTROM WIND"
[755] "THUNDERSTROM WINDS" "THUNDERTORM WINDS"
[757] "THUNDERTSORM WIND" "THUNDESTORM WINDS"
[759] "THUNERSTORM WINDS" "TIDAL FLOODOOD"
[761] "TIDAL FLOODOODING" "TORNADO"
[763] "TORNADO DEBRIS" "TORNADO F0"
[765] "TORNADO F1" "TORNADO F2"
[767] "TORNADO F3" "TORNADO/WATERSPOUT"
[769] "TORNADOES" "TORNADOES, THUNDERSTORM WIND, HAIL"
[771] "TORNADOS" "TORNDAO"
[773] "TORRENTIAL RAIN" "TORRENTIAL RAINFALL"
[775] "TROPICAL DEPRESSION" "TROPICAL STORM"
[777] "TROPICAL STORM ALBERTO" "TROPICAL STORM DEAN"
[779] "TROPICAL STORM GORDON" "TROPICAL STORM JERRY"
[781] "TSUNAMI" "TUNDERSTORM WIND"
[783] "TYPHOON" "UNSEASONABLE COLD"
[785] "UNSEASONABLY COLD" "UNSEASONABLY COOL"
[787] "UNSEASONABLY COOL & WET" "UNSEASONABLY DRY"
[789] "UNSEASONABLY HOT" "UNSEASONABLY WARM"
[791] "UNSEASONABLY WARM & WET" "UNSEASONABLY WARM AND DRY"
[793] "UNSEASONABLY WARM YEAR" "UNSEASONABLY WARM/WET"
[795] "UNSEASONABLY WET" "UNSEASONAL LOW TEMP"
[797] "UNSEASONAL RAIN" "UNUSUAL WARMTH"
[799] "UNUSUAL/RECORD WARMTH" "UNUSUALLY COLD"
[801] "UNUSUALLY LATE SNOW" "UNUSUALLY WARM"
[803] "URBAN AND SMALL" "URBAN AND SMALL STREAM"
[805] "URBAN AND SMALL STREAM FLOODOOD" "URBAN AND SMALL STREAM FLOODOODIN"
[807] "URBAN FLOODOOD" "URBAN FLOODOOD LANDSLIDE"
[809] "URBAN FLOODOODING" "URBAN FLOODOODS"
[811] "URBAN SMALL" "URBAN SMALL STREAM FLOODOOD"
[813] "URBAN/SMALL" "URBAN/SMALL FLOODOODING"
[815] "URBAN/SMALL STREAM" "URBAN/SMALL STREAM FLOODOOD"
[817] "URBAN/SMALL STREAM FLOODOOD" "URBAN/SMALL STREAM FLOODOODING"
[819] "URBAN/SMALL STRM FLOODG" "URBAN/SML STREAM FLOOD"
[821] "URBAN/SML STREAM FLOODG" "URBAN/STREET FLOODOODING"
[823] "VERY DRY" "VERY WARM"
[825] "VOG" "VOLCANIC ASH"
[827] "VOLCANIC ASH PLUME" "VOLCANIC ASHFALL"
[829] "VOLCANIC ERUPTION" "WAKE LOW WIND"
[831] "WALL CLOUD" "WALL CLOUD/FUNNEL CLOUD"
[833] "WARM DRY CONDITIONS" "WARM WEATHER"
[835] "WATER SPOUT" "WATERSPOUT"
[837] "WATERSPOUT-" "WATERSPOUT-TORNADO"
[839] "WATERSPOUT FUNNEL CLOUD" "WATERSPOUT TORNADO"
[841] "WATERSPOUT/" "WATERSPOUT/ TORNADO"
[843] "WATERSPOUT/TORNADO" "WATERSPOUTS"
[845] "WAYTERSPOUT" "WET MICOBURST"
[847] "WET MICROBURST" "WET MONTH"
[849] "WET SNOW" "WET WEATHER"
[851] "WET YEAR" "WHIRLWIND"
[853] "WILD FIRES" "WILD/FOREST FIRE"
[855] "WILD/FOREST FIRES" "WILDFIRE"
[857] "WILDFIRES" "WIND"
[859] "WIND ADVISORY" "WIND AND WAVE"
[861] "WIND CHILL" "WIND CHILL/HIGH WIND"
[863] "WIND DAMAGE" "WIND GUSTS"
[865] "WIND STORM" "WIND/HAIL"
[867] "WINTER MIX" "WINTER STORM"
[869] "WINTER STORM HIGH WINDS" "WINTER STORM/HIGH WIND"
[871] "WINTER STORM/HIGH WINDS" "WINTER STORMS"
[873] "WINTER WEATHER" "WINTER WEATHER MIX"
[875] "WINTER WEATHER/MIX" "WINTERY MIX"
[877] "WINTRY MIX" Let’s have a look some of the summaries as event type:
data[data$EVTYPE=="SUMMARY SEPT. 25-26",]data[data$EVTYPE=="SUMMARY OF MARCH 24-25",]Let’s group these summaries and see if any injury or damage has recorded.
summary(data[grepl("^SUMMARY", data$EVTYPE),]) STATE__ BGN_DATE BGN_TIME TIME_ZONE COUNTY
Min. :40.00 Min. :1996-01-17 Length:75 Length:75 Min. : 4.00
1st Qu.:40.00 1st Qu.:1996-05-24 Class :character Class :character 1st Qu.: 7.50
Median :40.00 Median :1996-06-18 Mode :character Mode :character Median :17.00
Mean :41.71 Mean :1996-07-10 Mean :30.39
3rd Qu.:40.00 3rd Qu.:1996-08-11 3rd Qu.:43.50
Max. :48.00 Max. :1997-03-29 Max. :89.00
COUNTYNAME STATE EVTYPE BGN_RANGE BGN_AZI BGN_LOCATI
Length:75 Length:75 Length:75 Min. :0 Length:75 Length:75
Class :character Class :character Class :character 1st Qu.:0 Class :character Class :character
Mode :character Mode :character Mode :character Median :0 Mode :character Mode :character
Mean :0
3rd Qu.:0
Max. :0
END_DATE END_TIME COUNTY_END COUNTYENDN END_RANGE END_AZI
Length:75 Length:75 Min. :0 Mode:logical Min. :0 Length:75
Class :character Class :character 1st Qu.:0 NA's:75 1st Qu.:0 Class :character
Mode :character Mode :character Median :0 Median :0 Mode :character
Mean :0 Mean :0
3rd Qu.:0 3rd Qu.:0
Max. :0 Max. :0
END_LOCATI LENGTH WIDTH F MAG FATALITIES INJURIES PROPDMG
Length:75 Min. :0 Min. :0 Min. : NA Min. :0 Min. :0 Min. :0 Min. :0
Class :character 1st Qu.:0 1st Qu.:0 1st Qu.: NA 1st Qu.:0 1st Qu.:0 1st Qu.:0 1st Qu.:0
Mode :character Median :0 Median :0 Median : NA Median :0 Median :0 Median :0 Median :0
Mean :0 Mean :0 Mean :NaN Mean :0 Mean :0 Mean :0 Mean :0
3rd Qu.:0 3rd Qu.:0 3rd Qu.: NA 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0
Max. :0 Max. :0 Max. : NA Max. :0 Max. :0 Max. :0 Max. :0
NA's :75
PROPDMGEXP CROPDMG CROPDMGEXP WFO STATEOFFIC ZONENAMES
Length:75 Min. :0 Length:75 Length:75 Length:75 Length:75
Class :character 1st Qu.:0 Class :character Class :character Class :character Class :character
Mode :character Median :0 Mode :character Mode :character Mode :character Mode :character
Mean :0
3rd Qu.:0
Max. :0
LATITUDE LONGITUDE LATITUDE_E LONGITUDE_ REMARKS REFNUM date_time
Min. :0 Min. :0 Min. :0 Min. :0 Length:75 Min. :269437 Length:75
1st Qu.:0 1st Qu.:0 1st Qu.:0 1st Qu.:0 Class :character 1st Qu.:270457 Class :character
Median :0 Median :0 Median :0 Median :0 Mode :character Median :270931 Mode :character
Mean :0 Mean :0 Mean :0 Mean :0 Mean :273038
3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:273196
Max. :0 Max. :0 Max. :0 Max. :0 Max. :299496
So those rows doesn’t contain any injury or damage report. Those rows are kind of summary of some down rows and only contains the locations and it is not important for us. Because at down rows we can see details. SO let’s drop these rows from our data sets.
data <- data[!grepl("^SUMMARY", data$EVTYPE),]dim(data)[1] 902222 38So we dropped 902297 - 902222 = 75 rows.
str(data)'data.frame': 902222 obs. of 38 variables:
$ STATE__ : num 1 1 1 1 1 1 1 1 1 1 ...
$ BGN_DATE : Date, format: "1950-04-18" "1950-04-18" "1951-02-20" ...
$ 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 ...
$ date_time : chr "1950-04-18 0130 CST" "1950-04-18 0145 CST" "1951-02-20 1600 CST" "1951-06-08 0900 CST" ...Let’s take a look at F (Force of the event) column:
table(data$F)
0 1 2 3 4 5
24993 19475 9878 3179 1072 137 It seems this columns is being used for tornados especially.
data$F[data$EVTYPE=="TORNADO"][1:10]
[1] 3 2 2 2 2 2 2 1 3 3Fatalities and injuries are human related damages, PROPDMG looks like a property numbers that effected from the event:
unique(data$PROPDMG)[1:10]
[1] 2.5e+04 2.5e+03 2.5e+06 2.5e+05 0.0e+00 3.0e+01 2.5e+02 2.5e+07 2.5e+08 5.0e+09PROPDMGEXP seems like a categorical variable and it is a measurement of the property damage as dollars. K for Thousand dollars, M for Million dollars and B for Billion dollars.
unique(data$PROPDMGEXP)
[1] "K" "M" "" "B" "m" "+" "0" "5" "6" "?" "4" "2" "3" "h" "7" "H" "-" "1" "8"data$PROPDMG[data$PROPDMGEXP=="h"]
[1] 2So we should change the PROPDMG according to PROPDMGEXP. But there are numbers as characters and symbols +,- in PROPDMGEXP. Since those unknown categorizes are low numbered we will ignore them.
dim(data)
[1] 902222 38Now let’s have a look again to our PROPDMG column:
sort(unique(data$PROPDMG), decreasing =T)[1:15]
[1] 1.150e+11 3.130e+10 1.693e+10 1.126e+10 1.000e+10 7.350e+09 5.880e+09 5.420e+09 5.150e+09 5.000e+09
[11] 4.830e+09 4.000e+09 3.000e+09 2.800e+09 2.500e+09CROPDMG column describes the agricultural damages of the event.
unique(data$CROPDMG)
[1] 0.00 10.00 500.00 1.00 4.00 50.00 5.00 15.00 0.50 0.40 0.05 21.00 7.00 17.00
[15] 26.00 22.00 3.00 0.80 39.00 20.00 300.00 0.90 48.00 0.20 1.50 2.50 2.00 200.00
[29] 25.00 130.00 37.00 9.00 45.00 185.00 35.00 2.20 12.00 0.30 90.00 0.15 100.00 66.00
[43] 142.00 1.10 0.70 330.00 750.00 6.00 43.00 60.00 150.00 1.80 250.00 40.00 0.02 1.30
[57] 30.00 70.00 0.01 80.00 350.00 400.00 8.00 75.00 3.50 63.00 18.00 0.28 0.10 1.70
[71] 0.75 4.70 16.00 170.00 600.00 125.00 6.70 2.10 675.00 0.60 262.00 332.00 220.00 56.00
[85] 0.03 353.00 177.00 36.00 373.00 430.00 160.00 123.00 13.00 140.00 38.00 52.00 0.24 320.00
[99] 7.70 3.70 6.80 1.20 380.00 6.50 5.60 74.90 34.10 15.30 24.00 5.10 27.00 42.00
[113] 800.00 650.00 230.00 10.50 55.00 1.58 5.99 1.25 3.60 5.20 3.25 5.25 3.22 204.00
[127] 2.40 127.00 7.50 46.00 33.00 900.00 120.00 700.00 2.25 19.80 4.50 189.68 1.05 81.00
[141] 225.00 37.50 5.40 7.55 1.40 26.84 5.70 500.10 950.00 15.70 11.00 17.50 110.00 1.12
[155] 55.70 1.60 12.90 20.04 46.50 65.00 4.80 1.48 43.68 613.00 14.00 19.00 3.40 850.00
[169] 450.00 240.00 1.27 2.80 34.48 13.40 23.00 17.96 63.77 9.38 12.40 9.90 1.21 12.50
[183] 7.80 159.00 242.00 280.00 14.10 4.20 6.90 4.97 540.00 713.00 7.20 5.90 73.60 7.10
[197] 10.20 5.30 17.10 596.00 74.30 470.00 655.00 460.00 180.00 2.90 260.10 145.00 5.50 3.80
[211] 1.75 978.00 137.90 77.48 28.00 41.50 190.00 0.25 6.21 68.00 11.70 85.00 117.00 64.00
[225] 6.10 2.60 97.00 3.75 150.20 167.90 135.00 1.55 11.50 3.11 38.80 550.00 310.00 186.00
[239] 88.00 105.00 1.77 149.70 301.00 4.66 22.70 3.39 15.65 131.01 8.80 29.10 475.00 338.00
[253] 12.30 8.30 11.80 875.00 2.70 465.00 109.92 154.00 575.00 660.00 39.85 413.60 63.40 20.30
[267] 4.91 640.00 22.60 83.00 41.66 42.30 420.00 61.00 865.00 306.72 210.00 13.50 325.00 975.00
[281] 150.08 160.96 1.85 169.60 80.85 8.50 29.00 605.00 399.84 44.00 32.00 175.00 1.90 102.30
[295] 515.00 1.56 8.40 151.00 31.90 10.45 1.96 6.03 6.85 78.00 1.65 578.85 25.01 24.27
[309] 256.00 6.63 53.00 115.00 4.40 510.00 168.00 480.00 25.20 65.05 24.50 4.43 275.00 8.90
[323] 13.20 9.60 7.81 10.80 1.93 312.48 261.00 270.00 4.81 8.55 156.50 335.00 14.25 10.92
[337] 7.14 1.33 11.96 290.00 31.00 285.00 93.20 82.50 8.70 48.40 26.50 15.20 21.60 4.60
[351] 500.80 990.00 2.85 576.00 920.00 890.00 216.00 101.50 49.00 47.00 21.94 671.00 8.60 32.50
[365] 423.00 66.50 26.36 180.11 48.46 10.19 1.35 154.69 630.00 42.65 1.47 415.00 5.80 2.15
[379] 1.51 2.33 2.65 8.49 11.68 34.50 113.90 22.32 193.90 11.94 112.50 16.60 9.10 492.40
[393] 77.00 15.10 2.30 76.50 22.20 985.00 45.40 9.40 4.16 26.32 5.92 2.47 73.00 155.00
[407] 344.00 620.00 390.00 316.00 153.00 523.00 67.00 387.00 243.00 213.00 610.00 99.00 625.00 133.00
[421] 169.00 588.00 512.00 375.00 112.00 425.00 286.00 281.00 165.00 107.00 91.00 41.00And as in the property damage we have also a column named CROPDMGEXP.
unique(data$CROPDMGEXP)
[1] "" "M" "K" "m" "B" "?" "0" "k" "2"So let’s reassign our CROPDMG column like we did in PROPDMG:
OK. Now let’s look at other columns:
str(data)
'data.frame': 902222 obs. of 40 variables:
$ STATE__ : num 1 1 1 1 1 1 1 1 1 1 ...
$ BGN_DATE : Date, format: "1950-04-18" "1950-04-18" "1951-02-20" ...
$ 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 : Date, format: NA NA NA ...
$ 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 25000 2500 25000 2500 2500 2500 2500 2500 25000 25000 ...
$ 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 ...
$ date_time : chr "1950-04-18 0130 CST" "1950-04-18 0145 CST" "1951-02-20 1600 CST" "1951-06-08 0900 CST" ...
$ end_date_time : chr "NA CST" "NA CST" "NA CST" "NA CST" ...
$ event_interval: num 0.0591 0.0591 0.0591 0.0591 0.0591 ...WFO, STATEOFFIC, ZONENAMES, LATITUDE, LONGITUDE, LATITUDE_E ,LONGITUDE_ are seems deployed with localization knowledge. And REFNUM is reference number for the events.
RESULTS
We have explored our columns and have some knowledge about the data set. Now let’s think about it. In this dataset we would like to know which event type is more dangerous for humans or environment. That is going to be the first question.
library(dplyr)So FLOODOOD has the most damage impact over the properties. But as you could see there are so many similar event types like : FLOODASH FLOODOOD, RIVER FLOODOOD, FLOODASH FLOODOODING etc… So we can grepl those event types and sum of them but we should do the same to rest of the event types. Or we can try to categorize by guessing. What kind of events could have been done? Floods, Rains, Winds, Temperature related events, Snowing, Tornados, Erosion, etc…
We can sum the property damages of the winds for sure. But how are we going to manage when two different types are combined like : RAIN/WIND, HIGH WINDS/SNOW, HEAVY SNOW AND STRONG WINDS ? So in this analysis we are going to consider unique events and won’t categorize the data. Let’s look at fatalities in events:
TORNADO is in the top of the list with a big gap to other events in the list. And let’s look at the INJURIES:
As expected tornados are the biggest threat for the human life.
And lastly let’s look at CROPDMG.
For agriculture DROUGHT is the biggest threat.
PLOTTING SOME DATA
library(ggplot2)
*** recursive gc invocation
*** recursive gc invocation
*** recursive gc invocation
*** recursive gc invocation
*** recursive gc invocation
*** recursive gc invocation
*** recursive gc invocation
*** recursive gc invocation
It seems Floodood has the biggest impact on property damages. We plotted the data we have already discussed and it is obvious that tornados are the biggest danger for the human life but for agriculture drought is the biggest threat as we can see. Now let’s investigate these events from different perspectives. Take a look at events from years:
Grouping the data based on crop damage, injuries and fatalities on years:
library(lattice)
year_groups <- data %>% group_by(YEAR) %>% summarise(CROPDAMAGE = sum(CROPDMG), INJURIES = sum(INJURIES), FATALITIES = sum(FATALITIES))
Injuries most numbers are observed in 1998,2011 and 1974. Fatalities highest numbers are observed in 1995, 2011, 1999. So let’s compare these two variable in 1974,1995,1998,1999 and in 2011 (both have high numbers in 2011)
We could assume fatalities and injuries can be related but this doesn’t seem to be so true. Only 2011 both variables are high. For ex in 1974 injuries are 6824 but fatalities are 366.
Let’s do a similar comparison for crop damage and injuries:
Let’s take a look at some event types damages:
Let’s take a look at events monthly. First We need to create a new column by mutating BGN_DATE column:
And we will group the event damages by months.
Let’s have a look at our new grouped data:
month_injury <- ggplot(monthly_events, aes(MONTH,INJURIES, fill=MONTH))
month_injury + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("TOTAL INJURIES BETWEEN 1950-2011 BASED ON MONTH")
And fatalities by months:
month_fatality <- ggplot(monthly_events, aes(MONTH,FATALITIES, fill=MONTH))
month_fatality + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("TOTAL FATALITIES BETWEEN 1950-2011 BASED ON MONTH")
Property damages by months:
month_prop <- ggplot(monthly_events, aes(MONTH,PROPERTY_DAMAGE, fill=MONTH))
month_prop + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("MONTHLY TOTAL PROPERTY DAMAGE BETWEEN 1950-2011")
month_crop <- ggplot(monthly_events, aes(MONTH,CROPDAMAGE, fill=MONTH))
month_crop + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("MONTHLY TOTAL CROP DAMAGE BETWEEN 1950-2011")
We now know tornados are the biggest danger for human life and drought is the biggest threat for the agriculture. And now we have learnt crop damage mostly taken at 8th month of the years. So can we assume droughts are being happening at 8 th months or droughts can be more damaging at 8th months? Let’s investigate this event type:
drought <- data %>% group_by(EVTYPE) %>% subset(EVTYPE=="DROUGHT") %>% summarise(MONTH = MONTH, CROP_DAMAGE = sum(CROPDMG))
`summarise()` has grouped output by 'EVTYPE'. You can override using the `.groups` argument.drought_crop <- ggplot(drought, aes(MONTH,CROPDAMAGE, fill=MONTH))
drought_crop + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("Monthly Total Crop Damage Between 1950-2011 By Drought" )
We seem to be right about our guess. Droughts are dangerous at 8th months. We should investigate tornados also, tornados are the most dangerous event for human life. Let’s look which months tornados has caused fatalities:
tornado <- data %>% group_by(EVTYPE) %>% subset(EVTYPE=="TORNADO") %>% group_by(MONTH) %>% summarise(FATALITIES = sum(FATALITIES))
tornado_fatality <- ggplot(tornado, aes(MONTH,FATALITIES, fill=MONTH))
tornado_fatality + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("Monthly Total Fatalities Between 1950-2011 By Tornados" )
From the chart we can assume at 4th and 5th months tornados are more fatal.
---
title: "R Notebook"
output:
  pdf_document: default
  html_notebook: default
---
## BRIEF ##
This document is about exploring and extracting some insights from the Storm Data which is an official publication of National Oceanic and Atmospheric Administration.
Across the USA starting from 1950 to 2011 meteorological events are observed with its results such as injuries, fatalities and damages on crops and on properties. We are going to investigate if event types are correlated with damage types.    
At first section We will download the data and clean some of it, transform the data, look at columns and group events to have ideas which events are more dangerous for human life and have strong impact on economy. We will compare top events that effects most. We will plot our data to understand better and see relations between events and damages. And we will examine by years and also by seasons of events. This data can be investigated by different points of view. But for more detailed analysis data has to be cleaned very carefully. Especially between 1950-1970 some stats are missing or deployed with personal measurements.      

## DATA PROCESSING ##
We will download the data as bz2 zip file format.
```{r}
url <- "https://d396qusza40orc.cloudfront.net/repdata%2Fdata%2FStormData.csv.bz2"
download.file(url, destfile = "./data.zip")
```

Bzfiles can be read without decompositioning. 
```{r}
data <- read.csv(bzfile("./data.zip"))
```
First we look at structure of our dataset.
```{r}
str(data)
```
And let's have a look at first rows of the data:
```{r}
head(data)
```
And dimension of data:
```{r}
dim(data)
```
So we have 37 columns and 902297 rows. As we understand from the first impression from the data we have day and time of starting and ending event, place (county), event type (EVTYPE), length and width, force of event (F), fatalities and injuries from the event, damage types, latitude and longitude knowledge.
But we have NA values in data. So let's have a look how many NAs we have:
```{r}
colSums(is.na(data))
```
We have char columns and there are "" values which can't be detected by is.na function. So let's try to find empty chars:
```{r}
table(data$CROPDMGEXP)
```
We see count of empty chars as 618413. When we use table function we can see empty chars in first item, another example:

```{r}
table(data$PROPDMGEXP)
```
So let's take a look only first item of what table's retrieve in only character type columns:
```{r}
for(i in 1:length(names(data))){
  if (class(data[,i]) =="character"){
    print(names(data)[i])
    print(table(data[,i])[1])
  }
}
```
So we have empty chars in most of char columns. And what is the ratio of empty chars on total rows in same column?

```{r}
for(i in 1:length(names(data))){
  if (class(data[,i]) =="character"){
    print(names(data)[i])
    print(table(data[,i])[1]/902297)
  }
}
```
Some character columns don't have any empty item which are:BGN_DATE,BGN_TIME, TIME_ZONE, STATE, EVTYPE. But in some columns empty chars are more common than others like %80.33 of END_AZI are empty chars. 

```{r}
data$BGN_DATE[1]
```
We already have a time column and in BGN_DATE column time " 0:00:00" is unnecessary:
```{r}
data$BGN_DATE <- gsub(" 0:00:00","",as.character(data$BGN_DATE))
data$BGN_DATE <- as.Date(data$BGN_DATE, format = "%m/%d/%Y")

```

We have 3 columns about date and time, first one is BGN_DATE second one is BGN_TIME and the last one is TIME_ZONE. We can paste all the columns and create a POSIXct column for further analysis.
```{r}
data$date_time <- paste(data$BGN_DATE, data$BGN_TIME, data$TIME_ZONE)
```

Let's see if have what we wanted
```{r}
data$date_time[1]
```
It looks good. Now let's have a look other char columns:
```{r}
str(data)
```
Let's look at END_DATE.
```{r}
unique(sapply(data$END_DATE, nchar))
```
So we can assume we have 4 kind of values in EDN_DATE including empty chars.
```{r}
table(sapply(data$END_DATE, nchar))
```
We have many empty chars on this column. 
Let's have a look at EVTYPE column:
```{r}
sort(unique(data$EVTYPE))
```

There are typos on the EVTYPE column and misplaced empty spaces also. And There are some Summary knowledge which will be investigated afterwards. But let's first we fix the upper lower cases:
```{r}
data$EVTYPE <- toupper(data$EVTYPE)
```

Let's have a look at Wind kind of events:
```{r}
grep("^WIND", unique(data$EVTYPE), value = TRUE)
```
Also there is WND or " WIND":
```{r}
grep("^WND", unique(data$EVTYPE), value = TRUE)
grep("^ WIND", unique(data$EVTYPE), value = TRUE)
```
Let's merge them into one type:
```{r}
data$EVTYPE[data$EVTYPE =="WND" | data$EVTYPE ==" WIND" | data$EVTYPE =="WINDS"] <- "WIND"
```
And there are empty spaces in front of the words.
```{r}
spaced_list <- list(grep("^ ", unique(data$EVTYPE), value = TRUE))
```
Let's fix empty spaces with trimws:
```{r}
for (i in 1:length(spaced_list[[1]])){
  data$EVTYPE[data$EVTYPE== spaced_list[[1]][i]]<-  trimws(spaced_list[[1]][i])
}
```

Now what do we have?
```{r}
unique(data$EVTYPE)
```
There are some abbreviations. TSTM, CSTL, HVY, FLD. Let's replace them with proper words: THUNDERSTROM, COASTAL, HEAVY and FLOOD respectively. 
```{r}
data$EVTYPE <- gsub("TSTM*","THUNDERSTORM", data$EVTYPE)
data$EVTYPE <- gsub("CSTL*","COASTAL", data$EVTYPE)
data$EVTYPE <- gsub("HVY*","HEAVY", data$EVTYPE)
data$EVTYPE <- gsub("FLD*","FLOOD", data$EVTYPE)
```
```{r}
sort(unique(data$EVTYPE))
```

Let's have a look some of the summaries as event type:
```{r}
data[data$EVTYPE=="SUMMARY SEPT. 25-26",]
```
```{r}
data[data$EVTYPE=="SUMMARY OF MARCH 24-25",]
```
Let's group these summaries and see if any injury or damage has recorded.

```{r}
summary(data[grepl("^SUMMARY", data$EVTYPE),])
```
So those rows doesn't contain any injury or damage report. Those rows are kind of summary of some down rows and only contains the locations and it is not important for us. Because at down rows we can see details. SO let's drop these rows from our data sets.
```{r}
data <- data[!grepl("^SUMMARY", data$EVTYPE),]
```

```{r}
dim(data)
```
So we dropped 902297 - 902222 = 75 rows.
```{r}
str(data)
```
Let's take a look at F (Force of the event) column:
```{r}
table(data$F)
```
It seems this columns is being used for tornados especially. 
```{r}
data$F[data$EVTYPE=="TORNADO"][1:10]
```
Fatalities and injuries are human related damages, PROPDMG looks like a property numbers that effected from the event:
```{r}

unique(data$PROPDMG)[1:10]
```
PROPDMGEXP seems like a categorical variable and it is a measurement of the property damage as dollars. K for Thousand dollars, M for Million dollars and B for Billion dollars.
```{r}
unique(data$PROPDMGEXP)
```
```{r}
data$PROPDMG[data$PROPDMGEXP=="h"]
```
So we should change the PROPDMG according to PROPDMGEXP. But there are numbers as characters and symbols +,- in PROPDMGEXP. Since those unknown categorizes are low numbered we will ignore them.
```{r}
dim(data)
for (i in 1:902222){
  if (data$PROPDMGEXP[i]=="K"){
    data$PROPDMG[i] <- data$PROPDMG[i]*1000
  }
  if (data$PROPDMGEXP[i]=="M" | data$PROPDMGEXP[i]=="m"){
    data$PROPDMG[i] <- data$PROPDMG[i]*1000000
  }
  if (data$PROPDMGEXP[i]=="B"){
    data$PROPDMG[i] <- data$PROPDMG[i]*1000000000
  }
}

```

Now let's have a look again to our PROPDMG column:
```{r}
sort(unique(data$PROPDMG), decreasing =T)[1:15]
```

CROPDMG column describes the agricultural damages of the event. 
```{r}
unique(data$CROPDMG)
```
And as in the property damage we have also a column named CROPDMGEXP.
```{r}
unique(data$CROPDMGEXP)
```
So let's reassign our CROPDMG column like we did in PROPDMG:
```{r}
for (i in 1:902222){
  if (data$CROPDMGEXP[i]=="K" | data$CROPDMGEXP[i]=="k"){
    data$CROPDMG[i] <- data$CROPDMG[i]*1000
  }
  if (data$CROPDMGEXP[i]=="M" | data$CROPDMGEXP[i]=="m"){
    data$CROPDMG[i] <- data$CROPDMG[i]*1000000
  }
  if (data$CROPDMGEXP[i]=="B"){
    data$CROPDMG[i] <- data$CROPDMG[i]*1000000000
  }
}
```

OK. Now let's look at other columns:
```{r}
str(data)
```
WFO, STATEOFFIC, ZONENAMES, LATITUDE, LONGITUDE, LATITUDE_E ,LONGITUDE_    are seems deployed with localization knowledge. And REFNUM is reference number for the events. 


## RESULTS ##

We have explored our columns and have some knowledge about the data set. Now let's think about it. In this dataset we would like to know which event type is more dangerous for humans or environment. That is going to be the first question.

```{r}
library(dplyr)
```

```{r}
event_prop_dmg <- data %>% group_by(EVTYPE) %>% summarise(PROPDMG = sum(PROPDMG))
```
```{r}
event_prop_dmg[order(event_prop_dmg$PROPDMG, decreasing = T),]
```
So FLOODOOD has the most damage impact over the properties. But as you could see there are so many similar event types like : FLOODASH FLOODOOD, RIVER FLOODOOD, FLOODASH FLOODOODING etc... So we can grepl those event types and sum of them but we should do the same to rest of the event types. Or we can try to categorize by guessing. What kind of events could have been done? Floods, Rains, Winds, Temperature related events, Snowing, Tornados, Erosion, etc... 
```{r}
event_prop_dmg[grepl("WIND", event_prop_dmg$EVTYPE),]
```
We can sum the property damages of the winds for sure. But how are we going to manage when two different types are combined like : RAIN/WIND, HIGH WINDS/SNOW, HEAVY SNOW AND STRONG WINDS ?
So in this analysis we are going to consider unique events and won't categorize the data.
Let's look at fatalities in events:
```{r}
event_fatalities <- data %>% group_by(EVTYPE) %>% summarise(FATALITIES= sum(FATALITIES))
```
```{r}
event_fatalities[order(event_fatalities$FATALITIES, decreasing = TRUE),]
```
TORNADO is in the top of the list with a big gap to other events in the list. 
And let's look at the INJURIES:

```{r}
event_injuries <- data %>% group_by(EVTYPE) %>% summarise(INJURIES = sum(INJURIES))
```
```{r}
event_injuries[order(event_injuries$INJURIES, decreasing = T),]
```
As expected tornados are the biggest threat for the human life.

And lastly let's look at CROPDMG.
```{r}
event_crop <- data %>% group_by(EVTYPE) %>% summarise(CROPDMG=sum(CROPDMG))
```
```{r}
event_crop[order(event_crop$CROPDMG, decreasing = T),]
```
For agriculture DROUGHT is the biggest threat. 

## PLOTTING SOME DATA ##
```{r}
library(ggplot2)
```

```{r}
event_fatalities[order(event_fatalities$FATALITIES, decreasing = TRUE)[1:10],]
```


```{r}
plot <- ggplot(event_fatalities[order(event_fatalities$FATALITIES, decreasing = TRUE)[1:10],], aes( y=FATALITIES,x= EVTYPE, fill=EVTYPE)) 
plot + geom_col() + xlab("") +theme(axis.text.x = element_text(angle = 90)) +scale_fill_brewer(palette="Spectral") + ggtitle("TOTAL FATALITIES IN 1950-2011 BASED ON EVENT TYPE")
```
```{r}
injuries <- ggplot(event_injuries[order(event_injuries$INJURIES, decreasing = T)[1:10],], aes(EVTYPE,INJURIES, fill=EVTYPE))
injuries + geom_col() + theme(axis.text.x = element_text(angle = 90))+scale_fill_brewer(palette="Paired") + ggtitle("TOTAL INJURIES IN 1950-2011 BASED ON EVENT TYPE")
```
```{r}
options(scipen=999)
crop <- ggplot(event_crop[order(event_crop$CROPDMG, decreasing = T)[1:10],], aes(EVTYPE,CROPDMG, fill=EVTYPE))
crop + geom_col() + theme(axis.text.x = element_text(angle = 90))+scale_fill_brewer(palette="Paired") + ggtitle("TOTAL CROP DAMAGE ($) IN 1950-2011 BASED ON EVENT TYPE")

```
```{r}
event_prop_dmg[order(event_prop_dmg$PROPDMG,decreasing = T),]
options(scipen=999)
prop <- ggplot(event_prop_dmg[order(event_prop_dmg$PROPDMG,decreasing = T)[1:10],], aes(EVTYPE,PROPDMG, fill=EVTYPE))
prop + geom_col() + theme(axis.text.x = element_text(angle = 90))+scale_fill_brewer(palette="Paired") + ggtitle("TOTAL PROPERTIES DAMAGE ($) IN 1950-2011 BASED ON EVENT")
```
It seems Floodood has the biggest impact on property damages. 
We plotted the data we have already discussed and it is obvious that tornados are the biggest danger for the human life but for agriculture drought is the biggest threat as we can see. 
Now let's investigate these events from different perspectives. 
Take a look at events from years:
```{r}
data <- data %>% mutate(YEAR= stringr::str_extract(data$BGN_DATE, "^.{4}"))
```
Grouping the data based on crop damage, injuries and fatalities on years:
```{r}
library(lattice)
year_groups <- data %>% group_by(YEAR) %>% summarise(CROPDAMAGE = sum(CROPDMG), INJURIES = sum(INJURIES), FATALITIES = sum(FATALITIES))

```
```{r}
year_groups[order(year_groups$FATALITIES, decreasing = T),]
```
```{r}
year_groups[order(year_groups$INJURIES, decreasing = T),]

```
```{r}
year_groups[order(year_groups$CROPDAMAGE, decreasing = T),]

```
Injuries most numbers are observed in 1998,2011 and 1974. Fatalities highest numbers are observed in 1995, 2011, 1999. So let's compare these two variable in 1974,1995,1998,1999 and in 2011 (both have high numbers in 2011)
```{r}
fatalities_injuries <- subset(year_groups, YEAR=="1995" | YEAR=="2011" | YEAR=="1999" | YEAR=="1998" | YEAR=="1974")

xyplot(INJURIES~FATALITIES | YEAR, data = fatalities_injuries, layout = c(5,1), main="INJURIES AND FATALITIES RELATION")
```
We could assume fatalities and injuries can be related but this doesn't seem to be so true. Only 2011 both variables are high. For ex in 1974 injuries are 6824 but fatalities are 366.

Let's do a similar comparison for crop damage and injuries:

```{r}
injuries_crop <- subset(year_groups, YEAR=="1994"| YEAR=="1993" | YEAR =="1998" |YEAR =="2011"| YEAR=="1974")
xyplot(CROPDAMAGE~INJURIES | YEAR, data = injuries_crop, layout = c(5,1), main ="CROPDAMAGE AND INJURIES RELATION")

```
Let's take a look at some event types damages:
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
```{r}

event_groups <- data %>% group_by(EVTYPE) %>% summarise(CROPDAMAGE = sum(CROPDMG), INJURIES = sum(INJURIES), FATALITIES = sum(FATALITIES), PROPERTY_DAMAGE = sum(PROPDMG))
top_events <-  subset(event_groups, EVTYPE=="TORNADO"| EVTYPE=="EXCESSIVE HEAT" | EVTYPE=="DROUGHT")
par(mfrow = c(1, 4), mar = c(4, 4, 2, 1), oma = c(0, 0, 2, 0))
barplot(INJURIES ~ EVTYPE, data= top_events)
barplot(CROPDAMAGE ~ EVTYPE,data= top_events)
barplot(FATALITIES ~ EVTYPE,data= top_events)
barplot(PROPERTY_DAMAGE ~ EVTYPE, data = top_events)
title("TOP EVENTS' THREAT COMPARISON", outer= T)
```
Let's take a look at events monthly. First We need to create a new column by mutating BGN_DATE column:
```{r}
data$MONTH <- substr(data$BGN_DATE, 6, 7)
```
And we will group the event damages by months.
```{r}
monthly_events <- data %>% group_by(MONTH) %>% summarise(CROPDAMAGE = sum(CROPDMG), INJURIES = sum(INJURIES), FATALITIES = sum(FATALITIES), PROPERTY_DAMAGE = sum(PROPDMG))
```
Let's have a look at our new grouped data:
```{r}
monthly_events
```
```{r}
month_injury <- ggplot(monthly_events, aes(MONTH,INJURIES, fill=MONTH))
month_injury + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("TOTAL INJURIES BETWEEN 1950-2011 BASED ON MONTH")
```
And fatalities by months:
```{r}
month_fatality <- ggplot(monthly_events, aes(MONTH,FATALITIES, fill=MONTH))
month_fatality + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("TOTAL FATALITIES BETWEEN 1950-2011 BASED ON MONTH")
```
Property damages by months:
```{r}
month_prop <- ggplot(monthly_events, aes(MONTH,PROPERTY_DAMAGE, fill=MONTH))
month_prop + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("MONTHLY TOTAL PROPERTY DAMAGE BETWEEN 1950-2011")
```
```{r}
month_crop <- ggplot(monthly_events, aes(MONTH,CROPDAMAGE, fill=MONTH))
month_crop + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("MONTHLY TOTAL CROP DAMAGE BETWEEN 1950-2011")
```
We now know tornados are the biggest danger for human life and drought is the biggest threat for the agriculture. And now we have learnt crop damage mostly taken at 8th month of the years. So can we assume droughts are being happening at 8 th months or droughts can be more damaging at 8th months?
Let's investigate this event type:
```{r}
drought <- data %>% group_by(EVTYPE) %>% subset(EVTYPE=="DROUGHT") %>% group_by(MONTH) %>% summarise(CROPDAMAGE = sum(CROPDMG))
```
```{r}
drought
```
```{r}
drought_crop <- ggplot(drought, aes(MONTH,CROPDAMAGE, fill=MONTH))
drought_crop + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("Monthly Total Crop Damage Between 1950-2011 By Drought" )
```
We seem to be right about our guess. Droughts are dangerous at 8th months.
We should investigate tornados also, tornados are the most dangerous event for human life.
Let's look which months tornados has caused fatalities:

```{r}
tornado <- data %>% group_by(EVTYPE) %>% subset(EVTYPE=="TORNADO") %>% group_by(MONTH) %>% summarise(FATALITIES = sum(FATALITIES))

```
```{r}
tornado
```
```{r}
tornado_fatality <- ggplot(tornado, aes(MONTH,FATALITIES, fill=MONTH))
tornado_fatality + geom_col() + scale_fill_brewer(palette="Paired") + ggtitle("Monthly Total Fatalities Between 1950-2011 By Tornados" )
```
From the chart we can assume at 4th and 5th months tornados are more fatal. 
