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README.Rmd
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---
output:
md_document:
variant: markdown_github
---
# mboxr
<!-- badges: start -->
[](https://cran.r-project.org/package=mboxr)
[](https://cranlogs.r-pkg.org/badges/grand-total/mboxr)
[](http://www.gnu.org/licenses/gpl-3.0)
[](https://travis-ci.org/jooyoungseo/mboxr)
[](https://ci.appveyor.com/project/jooyoungseo/mboxr)
[](https://codecov.io/gh/jooyoungseo/mboxr?branch=master)
<!-- badges: end -->
The goal of mboxr is to allow R users to conveniently import an [**mbox file**](https://en.wikipedia.org/wiki/Mbox) into [**R tibble**](https://tibble.tidyverse.org/) for hands-on analyses in R environment.
# Installation
## Python Dependencies
`mboxr` requires Anaconda Python environment on your system Path.
If you have not installed Conda environment on your system, please [download and install Anaconda](https://www.anaconda.com/download/) (Python 3.6 or later is recommended).
For this package, I have implemented [**mailbox.mbox**](https://docs.python.org/3/library/mailbox.html), [**email.header.decode_header**](https://docs.python.org/3/library/email.header.html), [**email.utils**](https://docs.python.org/3/library/email.utils.html) and [**pandas.DataFrame**](https://pandas.pydata.org/) Python modules into R using [**reticulate**](https://rstudio.github.io/reticulate/).
## R Package Installation
### Development Version
You can install the latest development version as follows:
```{r, eval=FALSE}
if(!require(remotes)) {
install.packages("remotes")
}
remotes::install_github("jooyoungseo/mboxr")
```
### Stable Version
You can install the released version of mboxr from [CRAN](https://CRAN.R-project.org) with:
```{r, eval=FALSE}
install.packages('mboxr')
```
## Usage
Please use `read_mbox()` function after loading `mboxr` library like below:
```{r test, eval=FALSE}
library(mboxr)
# Importing your mbox file into an R:
test <- system.file("extdata", "test1.mbox", package = "mboxr")
data <- read_mbox(test)
data
#> # A tibble: 2 x 6
#> date from to cc subject content
#> <dttm> <chr> <chr> <chr> <chr> <chr>
#> 1 2011-07-08 12:08:34 Author <~ Recipient~ <NA> Sample ~ "This is the bod~
#> 2 2011-07-08 12:08:34 Author <~ Recipient~ <NA> Sample ~ "This is the sec~
# Or, you can save your mbox file as an RDS file while assigning a tibble variable at the same time like below:
data <- read_mbox(mbox = test, file = "output.rds")
data
#> # A tibble: 2 x 6
#> date from to cc subject content
#> <dttm> <chr> <chr> <chr> <chr> <chr>
#> 1 2011-07-08 12:08:34 Author <~ Recipient~ <NA> Sample ~ "This is the bod~
#> 2 2011-07-08 12:08:34 Author <~ Recipient~ <NA> Sample ~ "This is the sec~
# You can merge all mbox files in your current directory or in any specified path into one tibble and save as an RDS file for the integrated one:
test_path <- system.file("extdata", package = "mboxr")
all_data <- merge_mbox_all(path = test_path, file = "all_merged_mbox.rds")
## Find your "output.rds" file saved in your working directory while freely using the imported tibble in your R session!
all_data
#> # A tibble: 4 x 6
#> date from to cc subject content
#> <dttm> <chr> <chr> <chr> <chr> <chr>
#> 1 2011-07-08 12:08:34 Author <~ Recipient~ <NA> Sample m~ "This is the bo~
#> 2 2011-07-08 12:08:34 Author <~ Recipient~ <NA> Sample m~ "This is the se~
#> 3 2011-07-09 12:09:35 Author <~ Recipient~ <NA> Another ~ "R is the best!~
#> 4 2011-07-10 10:03:32 Author <~ Recipient~ <NA> The last~ "This is the la~
```