William Hou
11/9/2020
CORE2010 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2010/rds/MD_SID_2010_CORE.csv");
CORE2011 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2011/rds/MD_SID_2011_CORE.csv");
CORE2012 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2012/rds/MD_SID_2012_CORE.csv");
CORE2013 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2013/rds/MD_SID_2013_CORE.csv");
CORE2014 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2014/rds/MD_SID_2014_CORE.csv");
CORE2015q4 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2015/rds/MD_SID_2015q4_CORE.csv");
CORE2015q1q3 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2015/rds/MD_SID_2015q1q3_CORE.csv");
colnames(CORE2015q1q3) = colnames(CORE2015q4);
CORE2015=rbind(CORE2015q1q3, CORE2015q4);
CORE2016 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2016/rds/MD_SID_2016_CORE.csv");
CORE2017 = read.csv("~/OneDrive/Johns Hopkins/Ali Sobhi Afshar - HCUP/Data/SIDC_MD_2017/rds/MD_SID_2017_CORE.csv");
zipFrequency <- function (yearData) {
yearData$ZIP3 <- as.factor(yearData$ZIP3);
zipFreq <- as.data.frame(table(yearData$ZIP3));
zipFreq <-zipFreq[order(-zipFreq$Freq), ];
colnames(zipFreq) = c("zip", "zipFreq");
zipFreq
}
UrbanOrRural <- function (yearData) {
UorR <- as.data.frame(table(yearData$PL_NCHS));
description = c('Central of >=1 million', 'Fringe of >=1 million',
'250,000-999,999', '50,000-249,999', 'Micropolitan', 'Rural');
UorR = UorR[1:6, ]
UorR = cbind(UorR, description);
colnames(UorR) = c("urban/rual", "Freq", "description");
UorR <-UorR[order(-UorR$Freq), ];
UorR;
}
zip zipFreq areaName
9 212 1534478 Main Baltimore
4 207 627743 Annapolis Junction
7 210 618730 Baltimore A-L
13 217 388135 Frederick
8 211 384414 Baltimore M-Z
5 208 376002 Bethesda
3 206 238806 Waldorf
6 209 225010 Silver Spring
14 218 173328 Salisbury
10 other 509140 other areas
Frequency description
1 871432 Central of >=1 million
2 3240855 Fringe of >=1 million
3 187554 250,000-999,999
4 289097 50,000-249,999
5 173899 Micropolitan
6 92007 Rural