Packages

library(ggplot2)
library(tidyverse)
library(lubridate)
library(knitr)

Synopsis

This report shows the principal climatic problems are affecting the population in EEUU, using the NOAA Storm Database, this database takes information from the National Climatic Data Center (NCDC) regularly receives Storm Data from the National Weather Service (NWS) and Storm Data is an official publication of the National Oceanic and Atmospheric Administration (NOAA) which documents the occurrence of storms and other significant weather phenomena having sufficient intensity to cause loss of life, injuries, significant property damage, and/or disruption to commerce.

Reading data

storms <- read_csv("repdata_data_StormData.csv", 
    col_types = cols(BGN_DATE = col_datetime(format = "%m/%d/%Y %H:%M:%S"), 
        BGN_TIME = col_time(format = "%H%M")))

Transforming data

events <- storms %>% group_by(EVTYPE) %>%  summarise(fatalities = sum(FATALITIES), injuries = sum(INJURIES)) %>% gather(key = "effect", value = value, injuries, -EVTYPE, fatalities) %>% filter(value > 1000)
head(events)
## # A tibble: 6 x 3
##   EVTYPE         effect   value
##   <chr>          <chr>    <dbl>
## 1 EXCESSIVE HEAT injuries  6525
## 2 FLASH FLOOD    injuries  1777
## 3 FLOOD          injuries  6789
## 4 HAIL           injuries  1361
## 5 HEAT           injuries  2100
## 6 HEAVY SNOW     injuries  1021
economic <- storms %>% select(EVTYPE, PROPDMG, PROPDMGEXP) %>%  group_by(EVTYPE, PROPDMG, PROPDMGEXP) %>% filter(!is.na(PROPDMGEXP) & PROPDMG >= 100 & PROPDMGEXP == "M")
head(economic)
## # A tibble: 6 x 3
## # Groups:   EVTYPE, PROPDMG, PROPDMGEXP [1]
##   EVTYPE  PROPDMG PROPDMGEXP
##   <chr>     <dbl> <chr>     
## 1 TORNADO     250 M         
## 2 TORNADO     250 M         
## 3 TORNADO     250 M         
## 4 TORNADO     250 M         
## 5 TORNADO     250 M         
## 6 TORNADO     250 M

Results

ggplot(events, aes(EVTYPE, value, fill = effect)) + geom_bar(stat = "identity", position = "dodge") + coord_flip() + xlab("Event type") + ylab("Affected people") + ggtitle("Events that affect more than a thousand people")

ggplot(economic, aes(EVTYPE, PROPDMG, fill = EVTYPE)) + geom_bar(stat = "identity") + coord_flip() + theme_bw() + xlab("Event type") + ylab("Millions") + ggtitle("Events with greatest economic consequences") + theme(legend.position = "none")