refactor again because of check complaining

.gitignore

@@ -4,7 +4,7 @@
 /inst/reports/
 !/inst/reports/*.pdf
 !/inst/reports/*.tex
-/data/csv/*
+/inst/csv/*
 /parlament_49_53_texts/
 .Rproj.user
 *.Rproj

R/fetch.R

@@ -41,7 +41,7 @@ fetch_batch <- function(offset, download_dir) {
 #' if create is TRUE, the directory given in download_dir is created
 #'
 #' @export
-fetch_all <- function(download_dir="data/records/", create=FALSE) {
+fetch_all <- function(download_dir="inst/records/", create=FALSE) {
     # check if download_dir path is a directory path
     if (str_sub(download_dir, -1) != .Platform$file.sep)
         download_dir <- str_c(download_dir, .Platform$file.sep)

R/parse.R

@@ -8,7 +8,7 @@
 #' @param path character
 #'
 #' @export
-read_all <- function(path="data/records/") {
+read_all <- function(path="inst/records/") {
     cat("Reading all records from", path, "\n")
     available_protocols <- list.files(path)
     res <- pblapply(available_protocols, read_one, path=path)
@@ -212,7 +212,7 @@ parse_speakerlist <- function(speakerliste_xml) {
 #' @param create set TRUE if the path does not exist yet and you want to create it
 #' 
 #' @export
-write_to_csv <- function(tables, path="data/csv/", create=F) {
+write_to_csv <- function(tables, path="inst/csv/", create=F) {
     check_directory(path, create)
     write.table(tables$speaker, str_c(path, "speaker.csv"))
     write.table(tables$speeches, str_c(path, "speeches.csv"))
@@ -229,7 +229,7 @@ write_to_csv <- function(tables, path="data/csv/", create=F) {
 #' reading the tables from a csv is way faster than reading and repairing the data every single time
 #' 
 #' @export
-read_from_csv <- function(path="data/csv/") {
+read_from_csv <- function(path="inst/csv/") {
     list(speaker = read.table(str_c(path, "speaker.csv")) %>%
              tibble() %>%
              mutate(id = as.character(id)),

man/fetch_all.Rd

@@ -4,7 +4,7 @@
 \alias{fetch_all}
 \title{Download available records}
 \usage{
-fetch_all(download_dir = "data/records/", create = FALSE)
+fetch_all(download_dir = "inst/records/", create = FALSE)
 }
 \arguments{
 \item{download_dir}{character}

man/read_all.Rd

@@ -4,7 +4,7 @@
 \alias{read_all}
 \title{Parse xml records}
 \usage{
-read_all(path = "data/records/")
+read_all(path = "inst/records/")
 }
 \arguments{
 \item{path}{character}

man/read_from_csv.Rd

@@ -4,7 +4,7 @@
 \alias{read_from_csv}
 \title{create a tibble from the csv file}
 \usage{
-read_from_csv(path = "data/csv/")
+read_from_csv(path = "inst/csv/")
 }
 \arguments{
 \item{path}{directory to read files from

man/write_to_csv.Rd

@@ -4,7 +4,7 @@
 \alias{write_to_csv}
 \title{Write the parsed and repaired results into separate csv files}
 \usage{
-write_to_csv(tables, path = "data/csv/", create = F)
+write_to_csv(tables, path = "inst/csv/", create = F)
 }
 \arguments{
 \item{tables}{list of tables to convert into a csv files.}

vignettes/funwithdata.Rmd

@@ -26,18 +26,18 @@ library(tidyr)
 
 First, you need to download all records of the current legislative period.
 ```r
-fetch_all("../data/records/") # path to directory where records should be stored
+fetch_all("../inst/records/") # path to directory where records should be stored
 ```
 Second, those `.xml` files, need to be parsed into `R` `tibbles`. This is accomplished by:
 ```r
-read_all("../data/records/") %>% repair() -> res
+read_all("../inst/records/") %>% repair() -> res
 ```
 We also used `repair` to fix a bunch of formatting issues in the records and unpacked
 the result into more descriptive variables.
 
 For development purposes, we load the tables from csv files.
 ```{r}
-res <- read_from_csv('../data/csv/')
+res <- read_from_csv('../inst/csv/')
 ```
 and unpack our tibbles
 ```{r}

vignettes/genderequality.Rmd

@@ -38,7 +38,7 @@ the result into more descriptive variables.
 
 For development purposes, we load the tables from csv files.
 ```{r}
-res <- read_from_csv('../data/csv/')
+res <- read_from_csv('../inst/csv/')
 ```
 and unpack our tibbles
 ```{r}

vignettes/hitlercomparison.Rmd

@@ -25,11 +25,11 @@ library(ggplot2)
 
 First, you need to download all records of the current legislative period.
 ```r
-fetch_all("../data/records/") # path to directory where records should be stored
+fetch_all("../inst/records/") # path to directory where records should be stored
 ```
 Second, those `.xml` files, need to be parsed into `R` `tibbles`. This is accomplished by:
 ```r
-read_all("../data/records/") %>% repair() -> res
+read_all("../inst/records/") %>% repair() -> res
 
 speeches <- res$speeches
 speaker <- res$speaker
@@ -40,7 +40,7 @@ the result into more descriptive variables.
 
 For development purposes, we load the tables from csv files.
 ```{r}
-tables <- read_from_csv('../data/csv/')
+tables <- read_from_csv('../inst/csv/')
 
 comments <- tables$comments
 speeches <- tables$speeches
@@ -50,7 +50,7 @@ talks <- tables$talks
 
 Further, we need to load a list of words that were used by Hitler but not by standard German texts.
 ```{r}
-fil <- file('../data/hitler_texts/hitler_words')
+fil <- file('../inst/hitler_texts/hitler_words')
 Worte <- readLines(fil)
 hitlerwords <- tibble(Worte)
 ```