gef-analysis-01/descriptive.R at master · DanRunfola/gef-analysis-01 · GitHub

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library(sp)
library(stargazer)
library(ggplot2)
library(scales)

#From data load script: GEF.noUS
GEF.spdf <- GEF.noUS

length( GEF.spdf[GEF.spdf$treatment == 1,])

#Stargazer Summary of GEF Projects for Description
GEF.projects <- GEF.spdf[GEF.spdf$treatment == 1,]
GEF.stargaze <- GEF.projects@data[c("dist_to_all_rivers.na.mean",
                                    "treatment",
                                    "dist_to_roads.na.mean",
                                    "srtm_elevation_500m.na.mean",
                                    "srtm_slope_500m.na.mean",
                                    "accessibility_map.na.mean",
                                    "gpw_v4_density.2005.mean",
                                    "ltdr_yearly_ndvi_mean.1982.mean",
                                    "ltdr_yearly_ndvi_mean.2014.mean",
                                    "v4composites_calibrated.2013.mean",
                                    "udel_air_temp_v4_01_yearly_min.2014.mean",
                                    "udel_air_temp_v4_01_yearly_max.2014.mean",
                                    "udel_air_temp_v4_01_yearly_mean.2014.mean",
                                    "udel_precip_v4_01_yearly_max.2014.mean",
                                    "udel_precip_v4_01_yearly_min.2014.mean",
                                    "udel_precip_v4_01_yearly_mean.2014.mean",
                                    "wdpa_5km.na.count",
                                    "treecover2000.na.mean",
                                    "lossyear.na.categorical_count",
                                    "X00forest25.na.sum"
                                    )]
stargazer(GEF.stargaze, type="html", median=TRUE)


GEF.project.dta <- read.table("/home/aiddata/Desktop/Github/GEF/Data/GlobalEnvironmentFacility_GeocodedResearchRelease_Level1_v1.0/data/projects.csv",
                            sep=",", header=TRUE)

length(GEF.project.dta )
GEF.project.dta.dates <- GEF.project.dta[GEF.project.dta$start_actual_isodate != "",]
min(as.Date(GEF.project.dta.dates$start_actual_isodate))
max(as.Date(GEF.project.dta.dates$start_actual_isodate))

GEF.locations.dta <- read.table("/home/aiddata/Desktop/Github/GEF/Data/GlobalEnvironmentFacility_GeocodedResearchRelease_Level1_v1.0/data/locations.csv",
                              sep=",", header=TRUE)
length(GEF.locations.dta[[1]])

#Average Disbursement
p1 <- ggplot(GEF.project.dta.dates,aes(x=GEF.project.dta.dates$transactions_start_year,y=total_disbursements,colour="Average Project Disbursement",group=1)) +
  stat_summary(fun.y ="mean", geom = "smooth", colour="black") +
  theme(legend.position="none")+
  ylab("Average Project Disbursement")+
  xlab("Year")+
  scale_y_continuous(labels = comma)+
  theme(text = element_text(size=15))

GEF.project.dta.dates$cnt <- 1
#Count of Projects
p2 <- ggplot(GEF.project.dta.dates,aes(x=GEF.project.dta.dates$transactions_start_year,y=cnt,group=1)) +
  stat_summary(fun.y ="sum", geom = "smooth", colour="black") +
  theme(legend.position="none")+
  ylab("Project Count")+
  xlab("Year")+
  scale_y_continuous(labels = comma)+
  theme(text = element_text(size=15))

min(GEF.project.dta$total_disbursements, na.rm=TRUE)
max(GEF.project.dta$total_disbursements, na.rm=TRUE)