Read_AE_SPSS_into_R.Rmd

---
title: 'Read Athero-Express SPSS file into R'
author: "Arjan Boltjes"
date: "30/04/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Load packages
```{r load_packages}
library(tidyverse)
library(haven)
```

## Import data
```{r import_ae}
# Athero-Express
path <- "/home/arjan/Cardio/Athero-Express/2019-1NEW_AtheroExpressDatabase_ScientificAE_23042019.sav"
ae <- read_sav(path)
```

## Tidy data
```{r tidy_ae}
names(ae) %<>%
     str_replace_all("\\.", "_") %>%    ## remove "." from variable names, replace with "_"
     tolower()

# Replace value codes by value labels 
ae %<>% haven::as_factor() %>%
     mutate(study_number = str_replace(study_number, "([0-9]+)", "ae\\1")) %>%  
     dplyr::rename(sex = gender) %>%
     print()

## Change the df variable classes by hand
manual_classses_ae <- read_tsv("20190430_variable_classes_AB.csv") %>%    ## make sure this .csv is in the currect directory, set WD, or set path to file
     gather() %>%
     rename(variables = 1, class_of_variable = 2) %>%
     mutate(class_of_variable = str_replace_all(class_of_variable, c("numerical" = "numeric"))) %>%
     print()

## Check whether column variables of manual_classes_ae corresponds to colnames ae
all(manual_classses_ae$variables == colnames(ae))

## if not in right order:
# manual_classses_ae <- manual_classses_ae[match(manual_classses_ae$variables, names(ae)),]
# ae_copy <- ae ## create ae copy for double checking

## Edit class types of ae variables
funs <- sapply(paste0("as.", manual_classses_ae$class_of_variable), match.fun)
ae[] <- Map(function(dd, f) f(as.character(dd)), ae, funs)
```

## Dimensions ae
```{r dim_ae}
dim(ae)
ae
```