v0.6.2 corrections for #79 issue with haven labels

ropensci · Feb 28, 2019 · fdaa94d · fdaa94d
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: rdhs
 Type: Package
 Title: API Client and Dataset Management for the Demographic and Health Survey (DHS) Data
-Version: 0.6.1.900
+Version: 0.6.2
 Authors@R: 
     c(person(given = "OJ",
              family = "Watson",

diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,7 @@
+## rdhs 0.6.2
+
+* Duplicate labels when parsing flat data files corrected (#79)
+
 ## rdhs 0.6.1
 
 * `extraction(add_geo=TRUE)` correction for Kenya 2014 surveys (#67)

diff --git a/README.md b/README.md
@@ -70,19 +70,19 @@ Obtain survey estimates for Malaria prevalence among children from the Democrati
 
 ```r
 dhs_indicators(indicatorIds = "ML_PMAL_C_RDT", returnFields=c("IndicatorId", "ShortName"))
-#>                              ShortName   IndicatorId
-#> 1: Malaria prevalence according to RDT ML_PMAL_C_RDT
+#>                             ShortName   IndicatorId
+#> 1 Malaria prevalence according to RDT ML_PMAL_C_RDT
 
 dhs_data(countryIds = c("CD","TZ"), indicatorIds = "ML_PMAL_C_RDT", surveyYearStart = 2013,
        returnFields=c("Indicator", "SurveyId", "Value", "SurveyYearLabel", "CountryName"))
-#>                              Indicator  SurveyId SurveyYearLabel Value
-#> 1: Malaria prevalence according to RDT CD2013DHS         2013-14  30.8
-#> 2: Malaria prevalence according to RDT TZ2015DHS         2015-16  14.4
-#> 3: Malaria prevalence according to RDT TZ2017MIS            2017   7.3
-#>                  CountryName
-#> 1: Congo Democratic Republic
-#> 2:                  Tanzania
-#> 3:                  Tanzania
+#>                             Indicator  SurveyId SurveyYearLabel Value
+#> 1 Malaria prevalence according to RDT CD2013DHS         2013-14  30.8
+#> 2 Malaria prevalence according to RDT TZ2015DHS         2015-16  14.4
+#> 3 Malaria prevalence according to RDT TZ2017MIS            2017   7.3
+#>                 CountryName
+#> 1 Congo Democratic Republic
+#> 2                  Tanzania
+#> 3                  Tanzania
 ```
 
 ### Identify survey datasets
@@ -95,11 +95,11 @@ Now, obtain survey microdatasets to analyze these same indicators. Query the *su
 sc <- dhs_survey_characteristics()
 sc[grepl("Malaria", sc$SurveyCharacteristicName), ]
 #>    SurveyCharacteristicID SurveyCharacteristicName
-#> 1:                     96            Malaria - DBS
-#> 2:                     90     Malaria - Microscopy
-#> 3:                     89            Malaria - RDT
-#> 4:                     57          Malaria module 
-#> 5:                      8 Malaria/bednet questions
+#> 57                     96            Malaria - DBS
+#> 58                     90     Malaria - Microscopy
+#> 59                     89            Malaria - RDT
+#> 60                     57          Malaria module 
+#> 61                      8 Malaria/bednet questions
 ```
 
 Use `dhs_surveys()` identify surveys for the countries and years of interest.
@@ -119,7 +119,7 @@ Lastly, identify the datasets required for download. By default, the recommended
 ```r
 datasets <- dhs_datasets(surveyIds = survs$SurveyId, fileFormat = "FL", fileType = "PR")
 str(datasets)
-#> Classes 'data.table' and 'data.frame':	3 obs. of  13 variables:
+#> 'data.frame':	3 obs. of  13 variables:
 #>  $ FileFormat          : chr  "Flat ASCII data (.dat)" "Flat ASCII data (.dat)" "Flat ASCII data (.dat)"
 #>  $ FileSize            : int  6595349 6622102 2172102
 #>  $ DatasetType         : chr  "Survey Datasets" "Survey Datasets" "Survey Datasets"
@@ -133,7 +133,6 @@ str(datasets)
 #>  $ DHS_CountryCode     : chr  "CD" "TZ" "TZ"
 #>  $ FileName            : chr  "CDPR61FL.ZIP" "TZPR7AFL.ZIP" "TZPR7QFL.ZIP"
 #>  $ CountryName         : chr  "Congo Democratic Republic" "Tanzania" "Tanzania"
-#>  - attr(*, ".internal.selfref")=<externalptr>
 ```
 
 ### Download datasets
@@ -163,17 +162,17 @@ The path to your config is saved between sessions so you only have to set this o
 microbenchmark::microbenchmark(dhs_datasets(surveyYearStart = 1986),times = 1)
 #> Unit: seconds
 #>                                  expr      min       lq     mean   median
-#>  dhs_datasets(surveyYearStart = 1986) 2.077998 2.077998 2.077998 2.077998
+#>  dhs_datasets(surveyYearStart = 1986) 1.810807 1.810807 1.810807 1.810807
 #>        uq      max neval
-#>  2.077998 2.077998     1
+#>  1.810807 1.810807     1
 
 # after caching, results will be available instantly
 microbenchmark::microbenchmark(dhs_datasets(surveyYearStart = 1986),times = 1)
 #> Unit: milliseconds
 #>                                  expr      min       lq     mean   median
-#>  dhs_datasets(surveyYearStart = 1986) 1.684018 1.684018 1.684018 1.684018
+#>  dhs_datasets(surveyYearStart = 1986) 1.582677 1.582677 1.582677 1.582677
 #>        uq      max neval
-#>  1.684018 1.684018     1
+#>  1.582677 1.582677     1
 ```
 
 Now download datasets by providing a list of desired dataset filenames.

diff --git a/codemeta.json b/codemeta.json
@@ -10,7 +10,7 @@
   "codeRepository": "https://ropensci.github.io/rdhs/",
   "issueTracker": "https://github.com/ropensci/rdhs/issues",
   "license": "https://spdx.org/licenses/MIT",
-  "version": "0.6.1.900",
+  "version": "0.6.2",
   "programmingLanguage": {
     "@type": "ComputerLanguage",
     "name": "R",
@@ -306,7 +306,7 @@
   ],
   "releaseNotes": "https://github.com/ropensci/rdhs/blob/master/NEWS.md",
   "readme": "https://github.com/ropensci/rdhs/blob/master/README.md",
-  "fileSize": "537.042KB",
+  "fileSize": "628.102KB",
   "contIntegration": [
     "https://travis-ci.org/ropensci/rdhs",
     "https://codecov.io/github/ropensci/rdhs?branch=master"

diff --git a/cran-comments.md b/cran-comments.md
@@ -1,6 +1,6 @@
 ## Test environments
 * local Windows 7 x64, R 3.5.1
-* local Linux 4.15.0-39-generic, R 3.5.1
+* local Linux 4.15.0-39-generic, R 3.5.2
 * local OS X, R 3.5.1
 
 ## R CMD check results

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