How to Set Up Your Data Science Environment (Anaconda Beginner)

hello everyone can hear back with another data science fundamentals video for you today I'm showing you how to set up your data science environment in data science even if you're using Python or using are most people use anaconda which is a data science Pacific platform so what I'm going to do today is I'm going to show you how to download this how to set it up and how to configure it so that you can use it going forward and - this really just makes your life as simple as possible when you're when you're learning this field if you enjoy this video please hit that like button and if you want to see more content at the intersection of data science and sports analytics please consider subscribing to my channel I actually was having some problems with all of the packages on here and I thought this would be a good opportunity to just delete it from my computer and start fresh so this is some of the impetus for this video the other reason I'm making this is I've used anaconda and a lot of these packages in some of my other videos and I wanted to show you how to install it from scratch in case you didn't know how ok so let's get started we go to anaconda calm let's just go to the regular one here this is all linked in the description below and you can just go and click this big download button over here now depending on which can you know system you're using you can do Windows Mac or Linux I'm on Windows and I'm going to download the Python 3.7 version if you download Python 3.7 you can still use Python 2.7 you just have to create a different instance of anaconda and I will show you how to do that and a little bit so we can download this here you see it's a pretty big file and it takes some time to download okay so my instance is finally finished downloading and I can click and open this up here so we fit through this page we click Next we agree to the license agreement and I generally do it just for me you can do it for all users but sometimes when you're updating it or doing things like that you have to login to the as the admin which can kind of be a pain so I recommend just doing it for yourself then you store it and users whatever your computer is anaconda three you can sort some other places but I think this is generally a good spot to put it now they generally don't recommend that you put the path environment and you do this after the fact and I think that that's probably a good idea so I'm gonna go ahead with those and now we will have this basically download on our computer here okay so this usually takes five or so minutes so this process generally takes some time I kind of cut a little footage to speed things up for you here so we continue and then we eventually finish here you don't have to learn more about anaconda cloud or get started with anaconda here but I think that's it's generally fun to do so if you select those things it'll bring you to some of these login areas where you can create an account if you want I won't really worry about that right now but what we will do is we'll log into the Anaconda Navigator right here and so we can see basically what we just downloaded and I'll walk you through each of these packages to kind of talk you through how you can use them as a data scientist and how they could improve the quality of your work to a certain extent so let's pop this open so the main tools if you use Python as a data scientist are going to be spider so this is the IDE that I usually use you might also use a Jupiter notebooks and then Jupiter lab is a expansion on Jupiter notebooks that gives you some of the features that you might see in spider so I think spider is probably the most similar to a normal IDE where you're writing Python scripts and running them Jupiter is kind of on the other end where it's completely interactive and you're running just basically blocks of code and then Jupiter lab is a little bit of a hybrid again I personally use spider but some might consider that a little bit old-school so if you want to be on the cutting edge I would I would make sure you know how to use at least all three of these tools and again if you're doing projects I would generally recommend that you do them and show them to other people through a Jupiter notebook that's kind of what is done on Kaggle comm that's what I see and a lot of github repos but all three of these tools are generally pretty good if you're using our our studio is pretty much your best option I would you know that's the only thing that I've personally used in our and I've had a good experience with it it is in my opinion almost identical to spider in Python so if you are using R and you want to try and transition over to learning some Python that spider ID might be a comfortable fit for you if you're doing actual development if you're putting something into production you're cutting something up I personally like vs code a lot it works very well for me and it's a pretty simple interface as well so generally what I'm trying to access anaconda or running it or run any of these things I actually do it through the anaconda prompt so you can go anaconda prompt and that will pop off this is in a Mac it's the same as the terminal same as in Linux but on Windows you have to open this prompt so let's say I wanted to open spider I would do spider just like that and it will eventually open up here for me same things with Jupiter or Jupiter lab the vs code all of these things will be run through here now if you want to install a new package let's say you wanted to install pandas for example what you can do is let's exit here so we can do Conda install pandas anak it'll load right through here I would assume I already have the package installed but if not this is a good approach to doing it here so we can first see yes and this will update pandas here so I also said earlier in the video that I would show you how to create an instance where you were using a different version of Python so in order to do this with you Conda create name and we're gonna call this py 2 and then we're gonna do python equals two point seven so this will install Python 2.7 as an instance and so we can activate that instance and run that through here so rather than you know python 3 is great but it can't run basically every package so it actually tells us what to do here so we can do as Conda activate py 2 and that gives us the same instance of Python version 2.7 we'll do the same thing again spider here oops okay so it turns out I actually have to install spider on this environment so we do Conda install spider and so it'll collect these packages there we go and we'd have to do the same thing for all of these other packages here this one might take just a little bit and so if you have these different environments what you can do is install different things on them so for example I have a tensorflow environment that I use where I have everything installed if you want to preserve this you can you can create an environment and always use that or you can share it as like a docker image or something like that so it took a little bit but I just had to open this again so we can do activate - I - it opens this as you can see we're using this py2 instance and we type spider I'm still getting some some kind of weird error messages and stuff like that but this is working so as we can see here let me move this into the frame we're using Python 2.7 0.16 and that's exactly what we want if we exit this and we'll just start a new one and we just do a spider here it'll open up with Python 3.7 or whatever I use so as we can see here this is Python three point seven point four so that is how you again create one of these new instances works with all of these different ones as well so that's it for this tutorial hopefully it helps you get familiar with the tools that are used in data science either if you use Python or if you use R I know that it took me a little while to figure out how to install all this stuff and get used to using it so hopefully this cuts through some of that noise and allows you to understand what's really important and how to configure these things thank you so much for watching and good luck on your data science journey

Channel: Ken Jee

Views: 63,448

Rating: 4.9027777 out of 5

Keywords: data science environment, data science anaconda, Data Science, Ken Jee, Machine Learning, data scientist, data science journey, data science setup, data science beginner, data science python, data science tutorial, data science fundamentals, data sciences basics, data sciences, data science for beginners, spyder, jupyter, data science ide, jupyter data science, machine learning anaconda, machine learning environment, anaconda python, data science tutorial playlist

Id: C4OPn58BLaU

Length: 9min 57sec (597 seconds)

Published: Fri Feb 21 2020

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• Original Title: How to Set Up Your Data Science Environment (Anaconda Beginner)
• Author: Ken Jee
• Description: In this video I show you how to download and set up your data science environment. Most data scientists use Anaconda, which is a data science specific ...
• Youtube URL: https://www.youtube.com/watch?v=C4OPn58BLaU