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# Find os:

```{r}
os <- Sys.info()[[1]]
```

# Create OS-relevant Dropbox file path:

```{r}
if(os == "Windows"){

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# Preview dataframe to write beforehands:
head(my_fav_df)

# Check dimensions of the dataframe you wish to write in a .csv file:
dim(my_fav_df)


# Set path of (i)output directory (ii) filename:
savedir    = "home/cgpu/favorite_dir/"
FILE = paste0(savedir,  'favorite_filename', '.csv')

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# 3 relevant packages:

## Basic, 
```{r}
utils::sessionInfo()
```

## Slightly cooler, nicer output display 
## DWNL: https://github.com/r-lib/sessioninfo 
```{r}

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names_to_keep  <- c('item1', 'item2', 'etc')
df_sliced       <- df[is.element(df$name , names_to_keep ), ]

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#!/usr/bin/env python3
 
 
#  TO RUN JUST TYPE:
#  python3 snp_selection.py
 
# INPUT FILES AND OPTIONS WILL BE REQUESTED AS USER INPUT
 
 
# THE FOLLOWING PROGRAMME IS PART OF the PACtool package (https://pypi.python.org/pypi/PACtool)

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# Highlighting errors, warnings, messages
Color code what R tells you when you need to knw something about your code.

This cool snippet found here: https://selbydavid.com/2017/06/18/rmarkdown-alerts/<br>
Kuddos to [David](https://twitter.com/TeaStats) for sharing!

```{r echo=FALSE}
# Cool snippet for color coding errors

knitr::knit_hooks$set(

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# https://rmarkdown.rstudio.com/word_document_format
```

---
title: "From rmd to word document"
date: "`r Sys.Date()`"
output: 
  word_document:
  toc          : TRUE #to include a table of contents in the output
  toc_depth    : 3 # Depth of headers to include in table of contents

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# installing/loading the package:
if(!require(installr)) { install.packages("installr"); require(installr)} #load / install+load installr
 
# Installing pandoc
install.pandoc()

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---
title: 'My very favorite title'
date: "`r Sys.Date()`"
output: 
  word_document:
  toc          : TRUE #to include a table of contents in the output
  toc_depth    : 3 # Depth of headers to include in table of contents
  fig_width    :   # Default width (in inches) for figures
  fig_height   :   # Default width (in inches) for figures
  fig_caption  : TRUE #to render figures with captions

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# Dataframe with the aliquot IDs of the cohort's samples, 96 x 4 
aliquot_ID           <- data.frame(matrix(NA, nrow = length(ofsthelse), ncol = length(LCMS_id)))
colnames(aliquot_ID) <- LCMS_id