R_DHS_Example
StevenMcEachern
09/10/2019
#Build table
## Need a reference to a male-female vocabulary
## ABS Standard (Australian Bureau of Statistics)
## I typed this in by hand
## Source: https://www.abs.gov.au/ausstats/abs@.nsf/Latestproducts/1200.0.55.012Main%20Features212016
## This is an offical ABS Standard
colheaders <- c('Male','Female','Other')
colheaders## [1] "Male" "Female" "Other"## Get counbtry xodes from somehwhere
## Found a restful API
## Figured this out using https://www.programmableweb.com/news/how-to-access-any-restful-api-using-r-language/how-to/2017/07/21?page=2
base <- "https://github.com/apilayer/restcountries"
endpoint <- "https://restcountries.eu/rest/v2/alpha/bi"
#stock <- "AAPL"
call1 <- paste(base,endpoint, sep="")
get_countries <- GET(call1)
#https://restcountries.eu/rest/v2/all?fields=name;capital;currencies
require(RJSONIO)## Loading required package: RJSONIO##
## Attaching package: 'RJSONIO'## The following objects are masked from 'package:jsonlite':
##
## fromJSON, toJSON# Import DHS Indicator data for TFR for each survey
json_file <- fromJSON("http://api.dhsprogram.com/rest/dhs/data/FE_FRTR_W_TFR?perpage=500")
# Unlist the JSON file entries
json_data <- lapply(json_file$Data, function(x) { unlist(x) })
# Convert JSON input to a data frame
APIdata <- as.data.frame(do.call("rbind", json_data),stringsAsFactors=FALSE)
# Tabulate the TFR values by the survey IDs
xtabs(as.numeric(Value) ~ SurveyId, data=APIdata)## SurveyId
## AF2015DHS AL2008DHS AL2017DHS AM2000DHS AM2005DHS AM2010DHS AM2016DHS
## 5.3 1.6 1.8 1.7 1.7 1.7 1.7
## AO2006MIS AO2011MIS AO2015DHS AZ2006DHS BD1994DHS BD1997DHS BD2000DHS
## 5.8 6.3 6.2 2.0 3.4 3.3 3.3
## BD2004DHS BD2007DHS BD2011DHS BD2014DHS BF1993DHS BF1999DHS BF2003DHS
## 3.0 2.7 2.3 2.3 6.5 6.4 5.9
## BF2010DHS BF2014MIS BF2017MIS BJ1996DHS BJ2001DHS BJ2006DHS BJ2012DHS
## 6.0 5.5 5.2 6.0 5.6 5.7 4.9
## BJ2017DHS BO1989DHS BO1994DHS BO1998DHS BO2003DHS BO2008DHS BR1986DHS
## 5.7 5.0 4.8 4.2 3.8 3.5 3.4
## BR1996DHS BT1988DHS BU1987DHS BU2010DHS BU2012MIS BU2016DHS CD2007DHS
## 2.5 4.9 6.9 6.4 6.1 5.5 6.3
## CD2013DHS CF1994DHS CG2005DHS CG2011DHS CI1994DHS CI1998DHS CI2005AIS
## 6.6 5.1 4.8 5.1 5.3 5.2 4.6
## CI2012DHS CM1991DHS CM1998DHS CM2004DHS CM2011DHS CO1986DHS CO1990DHS
## 5.0 5.8 4.8 5.0 5.1 3.2 2.8
## CO1995DHS CO2000DHS CO2005DHS CO2010DHS CO2015DHS DR1986DHS DR1991DHS
## 3.0 2.6 2.4 2.1 2.0 3.7 3.3
## DR1996DHS DR1999DHS DR2002DHS DR2007DHS DR2013DHS EC1987DHS EG1988DHS
## 3.2 2.7 3.0 2.4 2.5 4.2 4.5
## EG1992DHS EG1995DHS EG2000DHS EG2003DHS EG2005DHS EG2008DHS EG2014DHS
## 3.9 3.6 3.5 3.2 3.1 3.0 3.5
## ER1995DHS ER2002DHS ES1985DHS ET2000DHS ET2005DHS ET2011DHS ET2016DHS
## 6.1 4.8 4.2 5.5 5.4 4.8 4.6
## GA2000DHS GA2012DHS GH1988DHS GH1993DHS GH1998DHS GH2003DHS GH2008DHS
## 4.2 4.1 6.4 5.2 4.4 4.4 4.0
## GH2014DHS GH2016MIS GM2013DHS GN1999DHS GN2005DHS GN2012DHS GU1987DHS
## 4.2 4.2 5.6 5.5 5.7 5.1 5.5
## GU1995DHS GU1999DHS GU2015DHS GY2005AIS GY2009DHS HN2005DHS HN2011DHS
## 5.1 5.0 3.1 2.5 2.8 3.3 2.9
## HT1994DHS HT2000DHS HT2006DHS HT2012DHS HT2016DHS IA1993DHS IA1999DHS
## 4.8 4.7 3.9 3.5 3.0 3.4 2.8
## IA2006DHS IA2015DHS ID1987DHS ID1991DHS ID1994DHS ID1997DHS ID2003DHS
## 2.7 2.2 3.1 3.0 2.9 2.8 2.6
## ID2007DHS ID2012DHS JO1990DHS JO1997DHS JO2002DHS JO2007DHS JO2009DHS
## 2.6 2.6 5.6 4.4 3.7 3.6 3.8
## JO2012DHS JO2017DHS KE1989DHS KE1993DHS KE1998DHS KE2003DHS KE2008DHS
## 3.5 2.7 6.7 5.4 4.7 4.9 4.6
## KE2014DHS KE2015MIS KH2000DHS KH2005DHS KH2010DHS KH2014DHS KK1995DHS
## 3.9 3.7 3.8 3.4 3.0 2.7 2.5
## KK1999DHS KM1996DHS KM2012DHS KY1997DHS KY2012DHS LB1986DHS LB2007DHS
## 2.0 4.6 4.3 3.4 3.6 6.7 5.2
## LB2009MIS LB2011MIS LB2013DHS LB2016MIS LK1987DHS LS2004DHS LS2009DHS
## 5.9 4.9 4.7 4.2 2.7 3.5 3.3
## LS2014DHS MA1987DHS MA1992DHS MA2003DHS MB2005DHS MD1992DHS MD1997DHS
## 3.3 4.6 4.0 2.5 1.7 6.1 6.0
## MD2004DHS MD2008DHS MD2011MIS MD2013MIS MD2016MIS ML1987DHS ML1996DHS
## 5.2 4.8 5.2 4.4 4.1 7.1 6.7
## ML2001DHS ML2006DHS ML2012DHS ML2015MIS ML2018DHS MM2016DHS MR2000DHS
## 6.8 6.6 6.1 6.3 6.3 2.3 4.5
## MV2009DHS MV2016DHS MW1992DHS MW2000DHS MW2004DHS MW2010DHS MW2012MIS
## 2.5 2.1 6.7 6.3 6.0 5.7 5.3
## MW2014MIS MW2015DHS MW2017MIS MX1987DHS MZ1997DHS MZ2003DHS MZ2011DHS
## 5.1 4.4 4.2 4.0 5.2 5.5 5.9
## MZ2015AIS MZ2018MIS NC1998DHS NC2001DHS NG1990DHS NG2003DHS NG2008DHS
## 5.3 5.4 3.6 3.2 6.0 5.7 5.7
## NG2010MIS NG2013DHS NG2015MIS NI1992DHS NI1998DHS NI2006DHS NI2012DHS
## 6.1 5.5 5.0 7.0 7.2 7.0 7.6
## NM1992DHS NM2000DHS NM2006DHS NM2013DHS NP1996DHS NP2001DHS NP2006DHS
## 5.4 4.2 3.6 3.6 4.6 4.1 3.1
## NP2011DHS NP2016DHS PE1986DHS PE1992DHS PE1996DHS PE2000DHS PE2004DHS
## 2.6 2.3 4.1 3.5 3.5 2.8 2.6
## PE2007DHS PE2009DHS PE2010DHS PE2011DHS PE2012DHS PH1993DHS PH1998DHS
## 2.5 2.6 2.5 2.6 2.6 4.1 3.7
## PH2003DHS PH2008DHS PH2013DHS PH2017DHS PK1991DHS PK2006DHS PK2012DHS
## 3.5 3.3 3.0 2.7 4.9 4.1 3.8
## PK2017DHS PY1990DHS RW1992DHS RW2000DHS RW2005DHS RW2008DHS RW2010DHS
## 3.6 4.7 6.2 5.8 6.1 5.5 4.6
## RW2013MIS RW2015DHS RW2017MIS SD1990DHS SL2008DHS SL2013DHS SL2016MIS
## 4.2 4.2 4.2 4.7 5.1 4.9 4.2
## SN1986DHS SN1993DHS SN1997DHS SN2005DHS SN2006MIS SN2008MIS SN2010DHS
## 6.4 6.0 5.7 5.3 4.9 4.9 5.0
## SN2012DHS SN2014DHS SN2015DHS SN2016DHS SN2017DHS ST2008DHS SZ2006DHS
## 5.3 5.0 4.9 4.7 4.6 4.9 3.8
## TD1997DHS TD2004DHS TD2014DHS TG1988DHS TG1998DHS TG2013DHS TG2017MIS
## 6.4 6.3 6.4 6.4 5.2 4.8 4.4
## TH1987DHS TJ2012DHS TJ2017DHS TL2009DHS TL2016DHS TM2000DHS TN1988DHS
## 2.2 3.8 3.8 5.7 4.2 2.9 4.2
## TR1993DHS TR1998DHS TR2003DHS TR2008DHS TR2013DHS TT1987DHS TZ1992DHS
## 2.5 2.6 2.2 2.2 2.2 3.1 6.2
## TZ1996DHS TZ1999DHS TZ2004DHS TZ2007AIS TZ2010DHS TZ2012AIS TZ2015DHS
## 5.8 5.6 5.7 5.6 5.4 5.4 5.2
## TZ2017MIS UA2007DHS UG1988DHS UG1995DHS UG2000DHS UG2006DHS UG2009MIS
## 4.9 1.2 7.4 6.9 6.9 6.7 6.3
## UG2011DHS UG2014MIS UG2016DHS UZ1996DHS VN1997DHS VN2002DHS YE1991DHS
## 6.2 5.7 5.4 3.3 2.3 1.9 7.7
## YE1997DHS YE2013DHS ZA1998DHS ZA2016DHS ZM1992DHS ZM1996DHS ZM2002DHS
## 6.5 4.4 2.9 2.6 6.5 6.1 5.9
## ZM2007DHS ZM2013DHS ZW1988DHS ZW1994DHS ZW1999DHS ZW2005DHS ZW2010DHS
## 6.2 5.3 5.4 4.3 4.0 3.8 4.1
## ZW2015DHS
## 4.0plot(APIdata$SurveyYear,APIdata$Value,main = "Total Fertility Rate by Year", ylab = "TFR", xlab = "Year")
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