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SampleInfill.R
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SampleInfill.R
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rm(list=ls())
setwd("C:\\Users\\jamatney\\Documents\\RTCA\\data\\RTCA_Tables_Raw")
list.files()
temp <- list.files(path = getwd())
tbl_Con_Nps_Areas <- read.csv("tbl_Con_Nps_Areas.csv")
tbl_ConAllStates <- read.csv("tbl_ConAllStates.csv")
tbl_CongDistricts <- read.csv("tbl_CongDistricts.csv")
tbl_ConNCoop <- read.csv("tbl_ConNCoop.csv")
tbl_ConOffice <- read.csv("tbl_ConOffice.csv")
tbl_ConSucReport <- read.csv("tbl_ConSucReport.csv")
tbl_Consultation <- read.csv("tbl_Consultation.csv")
tbl_Consultation_Fiscal_Years <- read.csv("tbl_Consultation_Fiscal_Years.csv")
tbl_CustomizedDumpTable <- read.csv("tbl_CustomizedDumpTable.csv")
tbl_DumpTable <- read.csv("tbl_DumpTable.csv")
tbl_Member <- read.csv("tbl_Member.csv")
tbl_Member_Office <- read.csv("tbl_Member_Office.csv")
tbl_Member_State <- read.csv("tbl_Member_State.csv")
tbl_Nps_Areas <- read.csv("tbl_Nps_Areas.csv")
tbl_Office <- read.csv("tbl_Office.csv")
tbl_Prj_Nps_Areas <- read.csv("tbl_Prj_Nps_Areas.csv")
tbl_PrjApplicant <- read.csv("tbl_PrjApplicant.csv")
tbl_PrjApplicantWebsite <- read.csv("tbl_PrjApplicantWebsite.csv")
tbl_PrjCloseOutInfo <- read.csv("tbl_PrjCloseOutInfo.csv")
tbl_PrjCongDistricts_Test <- read.csv("tbl_PrjCongDistricts_Test.csv")
tbl_PrjCooperator <- read.csv("tbl_PrjCooperator.csv")
tbl_PrjDetailDocument <- read.csv("tbl_PrjDetailDocument.csv")
tbl_PrjDetailInfo <- read.csv("tbl_PrjDetailInfo.csv")
tbl_PrjDetailPartnerWebsite <- read.csv("tbl_PrjDetailPartnerWebsite.csv")
tbl_PrjDetailPhoto <- read.csv("tbl_PrjDetailPhoto.csv")
tbl_PrjNationalCooperator <- read.csv("tbl_PrjNationalCooperator.csv")
tbl_PrjNCoop <- read.csv("tbl_PrjNCoop.csv")
tbl_PrjOffice <- read.csv("tbl_PrjOffice.csv")
tbl_prjPhase <- read.csv("tbl_prjPhase.csv")
tbl_prjStates <- read.csv("tbl_prjStates.csv")
tbl_PrjSucReport <- read.csv("tbl_PrjSucReport.csv")
tbl_Project_Fiscal_Years <- read.csv("tbl_Project_Fiscal_Years.csv")
tbl_ProjectTracking <- read.csv("tbl_ProjectTracking.csv")
tbl_State <- read.csv("tbl_State.csv")
tbl_Sys_Config <- read.csv("tbl_Sys_Config.csv")
list.of.data.frames <- list(tbl_Con_Nps_Areas,
tbl_ConAllStates,
tbl_CongDistricts,
tbl_ConNCoop,
tbl_ConOffice,
tbl_ConSucReport,
tbl_Consultation,
tbl_Consultation_Fiscal_Years,
tbl_CustomizedDumpTable,
tbl_DumpTable,
tbl_Member,
tbl_Member_Office,
tbl_Member_State,
tbl_Nps_Areas,
tbl_Office,
tbl_Prj_Nps_Areas,
tbl_PrjApplicant,
tbl_PrjApplicantWebsite,
tbl_PrjCloseOutInfo,
tbl_PrjCongDistricts_Test,
tbl_PrjCooperator,
tbl_PrjDetailDocument,
tbl_PrjDetailInfo,
tbl_PrjDetailPartnerWebsite,
tbl_PrjDetailPhoto,
tbl_PrjNationalCooperator,
tbl_PrjNCoop,
tbl_PrjOffice,
tbl_prjPhase,
tbl_prjStates,
tbl_PrjSucReport,
tbl_Project_Fiscal_Years,
tbl_ProjectTracking,
tbl_State,
tbl_Sys_Config)
merged.data.frame = Reduce(function(...) merge(..., all=T), list.of.data.frames)
dat <- read.csv("ApplicantPartnerOut.csv", header=TRUE, sep=",")
ser <- read.csv("RTCA_FINANCIAL.csv")
head(ser)
head(dat)
listr <- c("Healthy Communities", "Large Landscapes", "Outdoor Recreation", "Rivers and Watersheds", "Transportation", "Urban", "Youth Engagement")
length(ser$OBJECTID)
length(ser$Project_ID)
dat <- cbind(ser$Project_ID, dat)
dat <- cbind(ser$OBJECTID, dat)
drops <- c("OBJECTID","Project_ID")
dat <- dat[,!(names(dat) %in% drops)]
head(dat)
colnames(dat)[1] <- "OBJECTID"
colnames(dat)[2] <- "Project_ID"
head(dat)
write.csv(dat, row.names = FALSE, "data.csv")
start <- read.csv("data.csv")
toy.df <- start[,2:11]
toy.df[1:20,]
complete = na.omit(toy.df)
toy.df[is.na(toy.df$Partner_Organization), c("Partner_Organization","Partner_Website","Contact_Name","Contact_Phone_Number","Contact_Email","Mailing_Address","City","State","Zip_Code")] =
complete[sample(1:nrow(complete), size = sum(is.na(toy.df$Partner_Organization)), replace = TRUE),
c("Partner_Organization","Partner_Website","Contact_Name","Contact_Phone_Number","Contact_Email","Mailing_Address","City","State","Zip_Code")]
toy.df
full <- cbind(start[,1],toy.df)
colnames(full)[1] <- "OBJECTID"
str(full)
write.csv(full, row.names=FALSE, "RTCA_APPLICANT_PARTNER.csv")
head(start)
listr <- c("National Park Foundation", "National Forest Foundation",
"Sonoran Institute", "Publilc Lands Partnership",
"Association of Partners for Public Lands", "Partners in Parks",
"Community and Ecosystem Stewardship","University of Michigan Collaboration",
"Sustainable Communities Network","International Mountain Bicycling Association")
listw <- c("http://www.nationalparks.org/","http://www.nationalforests.org/",
"http://www.sonoraninstitute.org/","http://publiclandspartnership.org/",
"http://www.appl.org/i4a/pages/index.cfm?pageid=1","http://www.partnersinparks.org/",
"http://ocs.fortlewis.edu/Stewardship/default.htm","http://www.snre.umich.edu/ecomgt//collaboration.htm",
"http://www.sustainable.org/","https://www.imba.com/")
sample(listr,100, replace=TRUE)
require(plyr)
combined <- cbind(dat[c("OBJECTID","Project_ID")], as.data.frame(listr))
length(dat$Unit_Name)
dat$Category <- sample(listr, length(dat$Category), replace=TRUE)
listr <- c("Assist with Efforts", "Develop a master plan", "Facilitate Meetings", "Assist with engagement", "Identify management strategies", "Provide support", "Provide guidance")
dat$Definition <- sample(listr, length(dat$Definition), replace=TRUE)
head(dat)
dat$Unit_Name <- sample(listr, length(dat$Unit_Name), replace=TRUE)
dat$Fiscal_Year <- sample(1995:2015, length(dat$Fiscal_Year), replace=TRUE)
head(dat)
n=length(100:30000)
dat$Dollar_Amount <- sample(100:10000, length(dat$Dollar_Amount), replace=TRUE)
write.csv(dat, row.names=FALSE, "RTCA_SERVICE.csv")