Analysis
Last updated: 2020-06-29
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Knit directory: GeoPKOReport/
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This document contains a series of steps that the project members have performed to explore the Geo-PKO dataset.
Load packages.
library(tidyverse)
library(readr)
library(ggthemes)Import the dataset.
GeoPKO <- read_csv("data/geopko.csv")Now we can start with the actual fun stuff! Let's have a quick look at the first few rows of the dataset.
head(GeoPKO)# A tibble: 6 x 71
Source Mission year month location country latitude longitude No.troops RPF
<chr> <chr> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <chr> <lgl>
1 Map n~ BINUB 2007 3 Bujumbu~ Burundi -3.38 29.4 0 NA
2 Map n~ BINUB 2009 8 Bujumbu~ Burundi -3.38 29.4 0 NA
3 Map n~ MINUCI 2003 8 Abidjan Ivory ~ 5.31 -4.01 0 NA
4 Map n~ MINUCI 2003 11 Abidjan Ivory ~ 5.31 -4.01 0 NA
5 Map n~ MINUCI 2004 1 Abidjan Ivory ~ 5.31 -4.01 0 NA
6 Map n~ MINURCA 1998 6 Bangui Centra~ 4.38 18.6 1385 NA
# ... with 61 more variables: RPF_No <lgl>, RES <dbl>, RES_No <dbl>, FP <dbl>,
# FP_No <dbl>, No.TCC <chr>, name.of.TCC1 <chr>, No.troops.per.TCC1 <chr>,
# name.of.TCC2 <chr>, No.troops.per.TCC2 <chr>, name.of.TCC3 <chr>,
# No.troops.per.TCC3 <dbl>, name.of.TCC4 <chr>, No.troops.per.TCC4 <dbl>,
# name.of.TCC5 <chr>, No.troops.per.TCC5 <dbl>, name.of.TCC6 <chr>,
# No.troops.per.TCC6 <dbl>, name.of.TCC7 <chr>, No.troops.per.TCC7 <dbl>,
# name.of.TCC8 <chr>, No.troops.per.TCC8 <dbl>, name.of.TCC9 <chr>,
# No.troops.per.TCC9 <dbl>, name.of.TCC10 <lgl>, No.troops.per.TCC10 <lgl>,
# name.of.TCC11 <lgl>, No.troops.per.TCC11 <lgl>, name.of.TCC12 <lgl>,
# No.troops.per.TCC12 <lgl>, name.of.TCC13 <lgl>, No.troops.per.TCC13 <lgl>,
# name.of.TCC14 <lgl>, No.troops.per.TCC14 <lgl>, UNPOL..dummy. <dbl>,
# UNMO..dummy. <dbl>, HQ <dbl>, LO <dbl>, comments <chr>, cow_code <dbl>,
# gwno <dbl>, name <chr>, TCC1 <dbl>, TCC2 <dbl>, TCC3 <dbl>, TCC4 <dbl>,
# TCC5 <dbl>, TCC6 <dbl>, TCC7 <dbl>, TCC8 <dbl>, TCC9 <dbl>, TCC10 <lgl>,
# TCC11 <lgl>, TCC12 <lgl>, TCC13 <lgl>, TCC14 <lgl>, ADM1_id <dbl>,
# ADM1_name <chr>, ADM2_id <dbl>, ADM2_name <chr>, PRIOID <dbl>NoMission <- GeoPKO %>% select(year, Mission) %>% distinct(year, Mission) %>% count(year)
Plot1 <- ggplot(NoMission, aes(x=(as.numeric(year)), y=n)) + geom_point() + geom_line(size=0.5) +
scale_x_continuous("Year", breaks=seq(1994, 2018, 1))+theme_classic()+
scale_y_continuous("Number of missions", breaks=seq(0,10,1)) +
theme(panel.grid=element_blank(),
axis.text.x=element_text(angle=45, vjust=0.5)) +
ggtitle("Number of UN Peacekeeping Missions in Africa, 1994-2018")
Plot1
sessionInfo()R version 3.5.0 (2018-04-23)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 16299)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggthemes_4.2.0 forcats_0.5.0 stringr_1.4.0 dplyr_0.8.4
[5] purrr_0.3.3 readr_1.3.1 tidyr_1.0.2 tibble_2.1.3
[9] ggplot2_3.2.1 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] tidyselect_1.0.0 xfun_0.12 haven_2.2.0 lattice_0.20-35
[5] colorspace_1.4-1 vctrs_0.2.3 generics_0.0.2 htmltools_0.4.0
[9] yaml_2.2.1 utf8_1.1.4 rlang_0.4.5 later_1.0.0
[13] pillar_1.4.3 withr_2.1.2 glue_1.4.0 DBI_1.1.0
[17] dbplyr_1.4.2 modelr_0.1.6 readxl_1.3.1 lifecycle_0.1.0
[21] munsell_0.5.0 gtable_0.3.0 cellranger_1.1.0 rvest_0.3.5
[25] evaluate_0.14 knitr_1.28 httpuv_1.5.2 fansi_0.4.1
[29] broom_0.5.5 Rcpp_1.0.4.6 promises_1.1.0 backports_1.1.5
[33] scales_1.1.0 jsonlite_1.6.1 farver_2.0.3 fs_1.3.1
[37] hms_0.5.3 digest_0.6.25 stringi_1.4.6 grid_3.5.0
[41] rprojroot_1.3-2 cli_2.0.2 tools_3.5.0 magrittr_1.5
[45] lazyeval_0.2.2 crayon_1.3.4 whisker_0.4 pkgconfig_2.0.3
[49] xml2_1.2.2 reprex_0.3.0 lubridate_1.7.4 rstudioapi_0.11
[53] assertthat_0.2.1 rmarkdown_2.3 httr_1.4.1 R6_2.4.1
[57] nlme_3.1-137 git2r_0.26.1 compiler_3.5.0