title	author
Get Census Bureau CPS microdata from Census Bureau website	Daniel Bonnery

Data: Current Population Survey

dataCPS is an R package that pulls CPS public microdata from the census bureau website on install and packs it into an

Installation.

To install the package, execute:

devtools::install_github("DanielBonnery/dataCPS")

Note that installation is slow, because part of the installation process is the downloading of data from the Census Bureau website.

Detailed Documentation

Refer to the dataCPS R package pdf documentation manual available on the github repo: https://github.com/DanielBonnery/dataCPS/blob/master/dataCPS.pdf

Demonstration

By default, the package downloads zip files, and only select some variables, as shown in the following summary:

data("cps200501",package="dataCPS")
knitr::kable(summary(cps200501))

	hrhhid	hrintsta	hrmis	hrhhid2	gestfips	peage	pesex	pulineno	pehspnon	prpertyp	pemlr	pwsswgt	pwcmpwgt
	Length:156657	Length:156657	Length:156657	Length:156657	Length:156657	Min. :-1.00	Length:156657	Length:156657	Length:156657	Length:156657	Length:156657	Min. : 0.0	Min. : 0
	Class :character	Class :character	Class :character	Class :character	Class :character	1st Qu.:11.00	Class :character	Class :character	Class :character	Class :character	Class :character	1st Qu.: 609.9	1st Qu.: 0
	Mode :character	Mode :character	Mode :character	Mode :character	Mode :character	Median :32.00	Mode :character	Mode :character	Mode :character	Mode :character	Mode :character	Median : 1919.8	Median : 1186
	NA	NA	NA	NA	NA	Mean :32.54	NA	NA	NA	NA	NA	Mean : 1850.4	Mean : 1435
	NA	NA	NA	NA	NA	3rd Qu.:51.00	NA	NA	NA	NA	NA	3rd Qu.: 2813.5	3rd Qu.: 2613
	NA	NA	NA	NA	NA	Max. :85.00	NA	NA	NA	NA	NA	Max. :32265.5	Max. :31739

If other variables are needed, use the dataCPS::get_data_from_web or 'get_onemonth_data_from_web' function. Following example downloads the data for January 2005 and creates a data frame that contains all the variables available. Variable names are then displayed.

library(dataCPS)
m=as.Date("20050101","%Y%m%d")
download.instruction.file(last.format.change.date.f(m))
DD<-get_onemonth_data_from_web(m)
knitr::kable(t(sapply(DD,typeof)))

hrhhid	hrmonth	hryear4	hurespli	hufinal	huspnish	hetenure	hehousut	hetelhhd	hetelavl	hephoneo	hufaminc	hutypea	hutypb	hutypc	hwhhwgt	hrintsta	hrnumhou	hrhtype	hrmis	huinttyp	huprscnt	hrlonglk	hrhhid2	hubus	hubusl1	hubusl2	hubusl3	hubusl4	gereg	gestcen	gestfips	gtcbsa	gtco	gtcbsast	gtmetsta	gtindvpc	gtcbsasz	gtcsa	proldrrp	pupelig	perrp	peparent	peage	prtfage	pemaritl	pespouse	pesex	puafever	peafwhen	peafnow	peeduca	prdtrace	prdthsp	puchinhh	purelflg	pulineno	prfamnum	prfamrel	prfamtyp	pehspnon	prmarsta	prpertyp	penatvty	pemntvty	pefntvty	prcitshp	prcitflg	prinusyr	puslfprx	pemlr	puwk	pubus1	pubus2ot	pubusck1	pubusck2	pubusck3	pubusck4	puretot	pudis	peret1	pudis1	pudis2	puabsot	pulay	peabsrsn	peabspdo	pemjot	pemjnum	pehrusl1	pehrusl2	pehrftpt	pehruslt	pehrwant	pehrrsn1	pehrrsn2	pehrrsn3	puhroff1	puhroff2	puhrot1	puhrot2	pehract1	pehract2	pehractt	pehravl	puhrck1	puhrck2	puhrck3	puhrck4	puhrck5	puhrck6	puhrck7	puhrck12	pulaydt	pulay6m	pelayavl	pulayavr	pelaylk	pelaydur	pelayfto	pulayck1	pulayck2	pulayck3	pulk	pelkm1	pulkm2	pulkm3	pulkm4	pulkm5	pulkm6	pulkdk1	pulkdk2	pulkdk3	pulkdk4	pulkdk5	pulkdk6	pulkps1	pulkps2	pulkps3	pulkps4	pulkps5	pulkps6	pelkavl	pulkavr	pelkll1o	pelkll2o	pelklwo	pelkdur	pelkfto	pedwwnto	pedwrsn	pedwlko	pedwwk	pedw4wk	pedwlkwk	pedwavl	pedwavr	pudwck1	pudwck2	pudwck3	pudwck4	pudwck5	pejhwko	pujhdp1o	pejhrsn	pejhwant	pujhck1	pujhck2	prabsrea	prcivlf	prdisc	premphrs	prempnot	prexplf	prftlf	prhrusl	prjobsea	prpthrs	prptrea	prunedur	pruntype	prwksch	prwkstat	prwntjob	pujhck3	pujhck4	pujhck5	puiodp1	puiodp2	puiodp3	peio1cow	puio1mfg	peio2cow	puio2mfg	puiock1	puiock2	puiock3	prioelg	pragna	prcow1	prcow2	prcowpg	prdtcow1	prdtcow2	prdtind1	prdtind2	prdtocc1	prdtocc2	premp	prmjind1	prmjind2	prmjocc1	prmjocc2	prmjocgr	prnagpws	prnagws	prsjmj	prerelg	peernuot	peernper	peernrt	peernhry	puernh1c	peernh2	peernh1o	prernhly	pthr	peernhro	prernwa	ptwk	peern	puern2	ptot	peernwkp	peernlab	peerncov	penlfjh	penlfret	penlfact	punlfck1	punlfck2	peschenr	peschft	peschlvl	prnlfsch	pwfmwgt	pwlgwgt	pworwgt	pwsswgt	pwvetwgt	prchld	prnmchld	prwernal	prhernal	hxtenure	hxhousut	hxtelhhd	hxtelavl	hxphoneo	pxinusyr	pxrrp	pxparent	pxage	pxmaritl	pxspouse	pxsex	pxafwhen	pxafnow	pxeduca	pxrace1	pxnatvty	pxmntvty	pxfntvty	pxhspnon	pxmlr	pxret1	pxabsrsn	pxabspdo	pxmjot	pxmjnum	pxhrusl1	pxhrusl2	pxhrftpt	pxhruslt	pxhrwant	pxhrrsn1	pxhrrsn2	pxhract1	pxhract2	pxhractt	pxhrrsn3	pxhravl	pxlayavl	pxlaylk	pxlaydur	pxlayfto	pxlkm1	pxlkavl	pxlkll1o	pxlkll2o	pxlklwo	pxlkdur	pxlkfto	pxdwwnto	pxdwrsn	pxdwlko	pxdwwk	pxdw4wk	pxdwlkwk	pxdwavl	pxdwavr	pxjhwko	pxjhrsn	pxjhwant	pxio1cow	pxio1icd	pxio1ocd	pxio2cow	pxio2icd	pxio2ocd	pxernuot	pxernper	pxernh1o	pxernhro	pxern	pxernwkp	pxernrt	pxernhry	pxernh2	pxernlab	pxerncov	pxnlfjh	pxnlfret	pxnlfact	pxschenr	pxschft	pxschlvl	qstnum	occurnum	pedipged	pehgcomp	pecyc	pegrprof	pegr6cor	pems123	pxdipged	pxhgcomp	pxcyc	pxgrprof	pxgr6cor	pxms123	pwcmpwgt	peio1icd	peio1ocd	peio2icd	peio2ocd	primind1	primind2
character	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	character	character	character	double	double	double	double	character	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double	double

The following code is an example of use of the function 'rbind_period', that creates a dataframe combining a series of consecutive monthly CPS datasets.

library(dataCPS)
data("cps200501",package="dataCPS")
monthsinperiod("200511","200603")

FALSE [1] "200511" "200512" "200601" "200602" "200603"

cps200511.200603<-rbind_period("200511","200603",c("pwsswgt","pesex"))
Y<-plyr::ddply(
  cps200511.200603,
  ~month+pesex,
  function(d){data.frame(y=sum(d$pwsswgt))})

library(ggplot2)
graph1<-ggplot(data=Y,aes(x=month,y=y,group=pesex,color=pesex))+geom_line()
print(graph1)

In this example we plot the direct estimate of the unemployment rate. These estimates are rough versions (simpled weighted sums) and differ from the more elaborated estimates published by the Census.

  cps200501.201201<-rbind_period("200501","201201",c("pwsswgt","pesex","pemlr"))
Y<-plyr::daply(cps200501.201201,
  ~month+pesex+pemlr,
  function(d){sum(d$pwsswgt)})

U<-reshape2::melt(apply(Y[,,c("1","2")],1:2,sum)/apply(Y[,,c("1","2","3","4")],1:2,sum))
U$month=as.Date(paste(U$month,"01"), "%Y%m%d")
U$pesex=as.factor(U$pesex);
U$pesex=forcats::fct_collapse(U$pesex,male="1",female="2")
graph2<-ggplot(data=U[is.element(U$pesex,c("male","female")),],
               aes(x=month,y=value,group = pesex,colour=pesex))+geom_line()+xlab("")+ylab("")+ggtitle("Direct estimates of the employment rate by gender")
graph2