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this tutorial explains how to create your own packages in vr programming language the tutorial was created in collaboration with wolfripple who is an expert on topics such as r programming data analysis and statistical computing volvo is also the owner of the youtube channel statistic in dd on which he provides our programming tutorials himself i definitely recommend checking out his channel because he's providing amazing content on the channel so without too much talk i'll head it over to wolfripple for the tutorial welcome to the statistics globe youtube channel also from my side i'm really honored and humbled to be asked to contribute to statistics globe by joachim so thank you for this opportunity it's the first collaboration that i'm doing on youtube so i'm really excited about that and i hope you find my contribution useful i'm talking about how to create your own r package today and if you think that maybe this is too much of an advanced topic for you just give me a few moments before you click away to talk about motivation and then hopefully you'll catch on because i think it's really a cool way of expressing yourself in order to create your own package so why is it worth thinking about creating your own r package even if you don't feel like a very advanced r programmer well first and foremost it's much easier than you may think if you haven't done it before we'll create an r package in this video in two minutes or less depending on how much i talk but you only have to do a few clicks to get a working version of a minimal r package to get the basic file structure that's very easy to do in rstudio secondly which preconditions do you need to fulfill to create an r package sebastian rochette from thinkr in france put it this way you need to have written at least one line of our code in your career so far to be qualified enough so i assume that this is the case for the vast majority of viewers so before we get practical let's think about when it makes sense to create your own r package maybe you know that quote from the great r for data science book by hadley wickham and gary krullemont when you find yourself copying the same piece of code two times or more it's time to write a function and we can extend that to creating a package when you find yourself copying and pasting functions across files or across projects then it's a good idea to create your own package so it's a way of easily reusing your code without code duplication it gives you a chance to organize your code in a central place it can be a great help when you collaborate with others in ongoing projects next to version control of course which we're not going to talk about in this video your own our package is a great way of standardizing your code for example when you want to create consistent plot themes i've seen that at companies where i did trainings they created an in-house package just to have a consistent plot theme and a consistent color scheme our packages are also great when you want to document your functions in a human-friendly way so it's much easier to look at rs built-in help files than to skim over scripts and read through code comments and also even if you don't write any functions a package can still be very useful that is when you want to share and document data in a central place so let's get practical let's create our first r package and you'll see it's very easy to do so i go to the project menu in the top right of the screen it says project none and i create a new project in rstudio so i click on new project takes a few seconds to open up this new project wizard and now it's a good idea to do it in a new directory and you see that our package is a type of project that you can create if you don't work with projects yet in our studio i can highly recommend that even if you don't work on packages projects are a great way of organizing your code and keeping your history and your global environment separate for different projects so you can switch conveniently between projects but for a package it makes even more sense so we choose our package we need to give it a name so i just call it my first r package so it's not a very thoughtful name but you can choose any name and we are not going to use version control here if you don't have git installed you don't see that also our end we're not using so we keeping the very simple defaults i'm just switching to a different folder and created there so we can leave the rest as is we're not starting with any scripts that we could add here we just create an empty package well it's almost empty it's an rstudio example package so i click on create project without further ado so it takes a couple of seconds to initialize the project and you see it's not completely empty it contains a basic function and so we have a starting point already so we see in the top left we have a script and it does something that a lot of introductions in different programming languages and i.t topics do it prints hello world so let's be quick and not mess around with it much we look at the file structure in a moment but um let's get started very quickly we have a new tab here next to environment history and connections we have a build tab that only exists inside of our projects that are packages in our studio and we have a couple of extra menu points here like and restart so let's do that to get a quick start you see some text is running through and the package is actually installed and you see in the console and the bottom left it says library my first r package so it is installed we look at the file structure in a moment but let's see what it does so we see from the script hello.r there's a function called hello so let's try if we can run this function so i just type in the console hello and indeed it prints hello world to the console so the package is working we should find it under the packages tab so let's see if we find it there i have the search field my first r package so it is there it has been installed like any regular r package and now and there are a couple of things um where we need to think differently when creating a package compared to writing our scripts that are not packages so usually when we define a function the function will show up in the global environment but here we see in the top right panel the environment is empty so the hello function is not defined in the global environment but it lives in the package so this is important i could run the function definition in the script and then the function would appear in the global environment hello but this is not recommended because then i can easily get confused the function should only live in the package namespace and not in the global environment so i will remove it again to not be confused here okay so we saw the packages installed but what does it contain obviously it has this script that we see in the source pane in the top left hello.r that defines the function it also gives some useful information and a link to the great r packages book by hadley wickham and jenny bryan so you can buy that book but you can also read it online for free which is great and it's true for a number of other packages from the rstudio team so you can find a lot of resources there so what does the basic file structure look like we see that on the files in the bottom right so we have two folders the r folder i think is pretty straightforward to understand it contains our r scripts in this case hello.r i move up again and then there's a man folder it's not about discriminating women or anything gender-specific but man stands for manual so hello.rt holds the documentation for the function so we can check in the console if the function is documented so i type question mark hello and indeed we have a very simple help page hello world description prince hello world usage examples so a minimal documentation for our function this documentation comes from the hello.rd file in the man subfolder so we can click on that and if you know latte this may look familiar the good news is if you don't know latte or if you don't feel like writing code like this we don't have to write this code so this was created here by our studio by the sample project but in a moment when we create the next package we'll see there's an easier way a more convenient way of creating the documentation but we can use the built-in documentation so our function is documented just like other packages that we may use a few more words about the other files that we see in the file structure so there's an r build ignore file where you can specify files that you need during package development but that shall not be part of your final package so you can put these in our build ignore there's a package called use this that offers convenience functions to manage this file so you don't have to edit entries there by hand because you need to use regular expressions but that is easy using the use this package then there's a description that holds some basic meta information this is a pure text file so it's fine to edit that by hand so it has the package name my first r package but then obviously we would have to edit the title and the description here what the package does and so on by the way if you publish a package on cran the title must not contain the word package so this is the description there are also functions and they use this package to edit the description but as this is just a plain text file you can also edit it by hand the other files in the basic file structure there's this dot our approach file with the name of the package so my first our package dot our approach in this case that's a file that we don't need to touch it's an rstudio internal file that manages this as an rstudio project so we don't need to edit that and then there's the namespace that manages if our functions are available for outside users so you can have so-called exported functions or non-exported functions and here we see it's a regular expression but the good news is again we don't need to edit that by hand there are convenience functions to manage the namespace so that's easy as well the hello function was obviously exported because we could use it after installation so so much for our first simple example and in the next section of the video we create a slightly more complex package with a function that we document by hand so much for the rstudio example package let's create a second package with our own function that we will also document because we didn't see documentation so far so again i start a new project and the project menu at the top right new project i don't need to save the environment new directory is recommended and then here i'm using our package using dev tools devtools contains some convenience functions so this is recommended for package development i call the package my calc because i have a calculation function that i want to document create project so again it takes a few seconds and you see now we have no scripts in the r folder so it's really an empty package and we have no man subfolder for the documentation because nothing has been documented yet so you see from scratch how to start up with a package i prepared a simple function that we can use called mycalc but this is not part of the package yet and i show you how to use they use this package to ease package development so i'm typing library dev tools which contains some tools for package development and you see that also they use this package is loaded when i do that and now i can just use a function use r to start up a new script i could manually open a script and save it in the r sub folder but i do it this way and i call the script my calc and now you see that in the r subfolder the script is created my calc but it's empty so this script that you see here is just my helper file so that i don't have to type everything by hand but it's not yet part of the package so i put the function in there and what the function does is it takes a numeric vector and a function as an input and then the function is applied to the numeric vector f of x so if that sounds a bit abstract i save it and then instead of installing the package there's a shortcut you can just load the function load all or ctrl shift l and then i can use the function my calc and let's say we use a vector from 1 to 10 and the mean function and it calculates the mean of this vector so it takes the numeric vector in the function as an input and returns the result 5.5 so so far so good um the function is working but when i want to have a look at the documentation question mark my calc there's no documentation we haven't documented the function yet so um this used to be much harder it's easier now i hope to convince you of that so you can go to the code menu in our studio and there's a an entry just below the middle insert or oxygen skeleton or there's also a keyboard shortcut but you can find it in the menu and then we get the basic structure of commands that we need to fill in the documentation so we can do that here you see we get the skeleton um there are so called r oxygen tags like param return value and export says the function is available for outside users so we don't have to remember all that by heart but we can use this structure and then just fill it in so prepare this a little bit we have x as a numeric vector f as a function and the return value and an example how to use that so i copy that over to our script to complete the documentation so all we filled in was the parameters x and f an omega vector in the function the return value is the result of the calculation and we have one example so i can save that script now and then go again to the build tab and document the function there's a keyboard shortcut ctrl shift d or we can click on this menu entry document so it's writing the documentation now and now we have this man subfolder that we saw before in the documentation in the first example and it's got this rd file with this latte like style but you see um we don't need to edit that by hand so this is created for us from this skeleton that is i think not too hard to create we can load the function again load all and then look for the help file again question mark my calc and now we see there is a basic documentation i didn't provide a title um but uh in the description so i need to fill that in still but there's usage there's the arguments and the return bank and at the bottom we also see an example mycalc 1 to 10 mean so we have this documentation you get the key idea i think um so the main takeaway should be it's not too hard to create a package it can be quite fun it's really i find raises my confidence in using or having tried out a few packages of my own so i encourage you to do that try that out um subscribe to the statistics club channel if you haven't already all the best see you next time ciao thanks again to wolf ripple for his contribution to this video if you want to learn more on how to create your own packages in vr programming language i can recommend once again to check out wolf's channel statistic in dd because on this channel he's providing a serious on how to create your own package in r and in this series he's discussing the topics of this video in some more detail i will put a link to his channel into the description of the video so you can find it there and if you have liked this video make sure to give thumbs up on the video or leave us a comment below thanks a lot for watching and see you in the next video