R Dataset / Package Ecdat / nkill.byCountryYr
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dataset-94073.csv | 22.27 KB |
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On this Picostat.com statistics page, you will find information about the nkill.byCountryYr data set which pertains to Global Terrorism Database yearly summaries. The nkill.byCountryYr data set is found in the Ecdat R package. Try to load the nkill.byCountryYr data set in R by issuing the following command at the console data("nkill.byCountryYr"). This may load the data into a variable called nkill.byCountryYr. If R says the nkill.byCountryYr data set is not found, you can try installing the package by issuing this command install.packages("Ecdat") and then attempt to reload the data with library("Ecdat") followed by data("nkill.byCountryYr"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing nkill.byCountryYr at the command-line which should display the entire dataset. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the nkill.byCountryYr R data set. The size of this file is about 22,806 bytes. Global Terrorism Database yearly summariesDescriptionThe Global Terrorism Database (GTD) "is a database of incidents of terrorism from 1970 onward". Through 2015, this database contains information on 141,966 incidents.
Usagedata(terrorism) data(incidents.byCountryYr) data(nkill.byCountryYr) Format
NOTE: For nkill.byCountryYr and for terrorism[c('nkill', 'nkill.us')], NAs in GTD were treated as 0. Thus the actual number of deaths were likely higher, unless this was more than offset by incidents being classified as terrorism, when they should not have been.
DetailsAs noted with the "description" above, Pape et al. noted that the GTD reported an increase in suicide terrorism of over 70 percent between 2007 and 2013, while their Suicide Attack Database showed a 19 percent decrease over the same period. Pape et al. insisted that the most likely explanation for this difference is the change in the organization responsible for managing that data collection from ISVG to START. If the issue is restricted to how incidents are classified as "suicide terrorism", this concern does not affect the other variables in this summary. However, if it also impacts what incidents are classified as "terrorism", it suggests larger problems. SourceThe Global Terrorism Database maintained by the National Consortium for the Study of Terrorism and Responses to Terrorism (START, 2015), downloaded 2015-11-28. The world and US population figures came from "Total Population - Both Sexes", World Population Prospects 2015, published by the Population Division of the Department of Economic and Social Affairs of the United Nations, accessed 2016-09-05. The World and US death rates came from the World Bank, accessed 2016-09-05. ReferencesRobert Pape, Keven Ruby, Vincent Bauer and Gentry Jenkins, "How to fix the flaws in the Global Terrorism Database and why it matters", The Washington Post, August 11, 2014 (accessed 2016-01-09). Examplesdata(terrorism) # plot deaths per million population plot(kill.pmp~year, terrorism, pch=method, type='b') plot(kill.pmp.us~year, terrorism, pch=method, type='b', log='y', las=1) # terrorism as parts per 10,000 # of all deaths plot(pkill*1e4~year, terrorism, pch=method, type='b', las=1) plot(pkill.us*1e4~year, terrorism, pch=method, type='b', log='y', las=1) # plot number of incidents, number killed, # and proportion NAplot(incidents~year, terrorism, type='b', pch=method)plot(nkill.us~year, terrorism, type='b', pch=method) plot(nkill.us~year, terrorism, type='b', pch=method, log='y')plot(pNA.nkill.us~year, terrorism, type='b', pch=method) abline(v=1997.5, lty='dotted', col='red') # by country by year data(incidents.byCountryYr) data(nkill.byCountryYr)yr <- as.integer(colnames( incidents.byCountryYr)) str(maxDeaths <- apply(nkill.byCountryYr, 1, max) ) str(omax <- order(maxDeaths, decreasing=TRUE)) head(maxDeaths[omax], 8) tolower(substring( names(maxDeaths[omax[1:8]]), 1, 2)) pch. <- c('i', 'g', 'f', 'l', 's', 'c', 'u', 'p') cols <- 1:4matplot(yr, sqrt(t( nkill.byCountryYr[omax[1:8], ])), type='b', pch=pch., axes=FALSE, ylab='(square root scale) ', xlab='', col=cols, main='number of terrorism deaths\nby country') axis(1) (max.nk <- max(nkill.byCountryYr[omax[1:8], ])) i.nk <- c(1, 100, 1000, 3000, 5000, 7000, 10000) cbind(i.nk, sqrt(i.nk)) axis(2, sqrt(i.nk), i.nk, las=1) ip <- paste(pch., names(maxDeaths[omax[1:8]])) legend('topleft', ip, cex=.55, col=cols, text.col=cols) -- Dataset imported from https://www.r-project.org. |
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