@@LukeBarousse I was about 5 minutes into your video and had the same thought. I would absolutely love a tutorial on creating a web-scraping tool specifically to look at new job positions on Indeed or Linked In. Probably going to send you an email asking if I could pay to have you put together a tutorial. It would be invaluable.
I work with both R and python on a daily basis, from a statistical tool stand point the R ecosystem is better, more statistical tests are available, with more statistics (like confidence intervals) and under the hood the implementation tends to be more accurate, also for a beginner with a stat background R api is closer to the theory so it's faster to pickup. Python is way better as a general purpose programming language hands down. I'm working on porting some of R's statistical tools to python
Agreed. I think they both have their purposes and as a statistical tool R is the way to go. Python has a bit of catching up to do but it will for sure.
Did you learn R first or Python for data analytics? I started with Python in the beginning for basics & then moved to R. I didn't learn Python libraries but I have learned some R libraries. Now I feel these libraries are pretty overwhelming. I am thinking to go back to python.
How do you use Python (or R) for data analytics? ALSO, Al Bellamy and I are GOOD FRIENDS and we pick on each other all the time. I don't think I communicated this well in the video, so wanted to clarify that Al meant no ill intention with his comments and neither did I with mine.
I use both. I find everything-data to be much easier to accomplish in R up until the point when your data product needs to be a cog in a bigger machine. Then it's Python.
I made some research on this topic at our University. Statistically, many IT students, prefer Phyton over R and it was no surprise because many of them think that Phyton is more dynamic and easy to understand, where as r needs to type complex syntax to perform operations. But I prefer R for doing statistical analysis and other stuff. With R, I think you'll be able to to to the deeper insights into a statistics. Glory to those R diehards.
My first programming language was Java. If you understand most programming languages including R, you can pick up how to use Python. These people who are complaining act like it's a war crime. They need to chill.
I have often noticed people focus on the seemingly cool stuff like coding too much without the basic understanding. I have an IT background and currently a BI Developer. My preferred list would be the following: 1. Get enough knowledge of Statistics 2. Use one simple statistics tool with a Graphical User Interface e.g SPSS, Stata, etc 3. Sharpen your MS Excel skills 4. Learn SQL for data analysis 5. BI tool or Visialization tool e.g. Power BI, Tableau 5. Learn a Data Science programming language e.g python, SAS, R 6. Build projects I'm sure you'll be the complete package. Thank me later 😊😊
Start with Excel. It's indispensable . I learned R before I learned SQL. Once you learn the dyplr package of R, SQL will be a breeze. SQL is not that hard once you understand the principles of data manipulation and R is a great way to learn that.
People should learn from you how to take criticism in the most positive way before learning anything that is to do with data analytics. Great video. And savage response by giving a shoutout to the same person. 😂
Great video and analysis there, hi Luke, I'm a Software Engineer from Guatemala and currently I'm working as a Data Analyst. Personally, there are a couple of points that I'd like to mention that I strongly believe are worthy, in order to have a healthy discussion. I use Spark, Python and SQL almost every day on my job, like each language to me has its own pros and cons. I used to work as a DBA, so I have a couple of second thoughts regarding SQL haha. I do agree that Excel, R and SQL are good foundational languages to start in this field, and I'm not a Python fan, or better said, I'm not advocating for any language, to me, the tool, or language of choice, will depend on the needs of your project, and the community you have. Like, why would you use SQL or Python or R or any language, when you can actually combine them. My advice, would be, don't marry any language or tool, because that's all what they are: TOOLS.
Boom! Love this knowledge bomb Hugo! Thanks for sharing this. Very much agree with your perspective. You need multiple tools in order to succeed as a data analyst!
I actually genuinely love using R. It's really the first programming language (I don't count SQL as it's not really the same thing as I see it) that I've tackled after studying C++ for years and studying basic Linux kernel scripting and it is honestly fun. I've never felt so confident with optimizing my code before. Also, it is ridiculously easy for me to grasp most new concepts. I won't lie, I haven't looked much into python, with only a couple hours of it under my belt, but I think I will always be attached to R. Also, sidenote Rstudio is a fantastic IDE for all the above languages. Imho. Thanks for the video, I watched it before starting the Google Certificate and again now.
Hey Luke, I am currently taking 3 courses 2 hrs a day 2 days a week for 10 weeks. Data Analysis with R & RStudio, Data Analysis with Python Anaconda and Python basic Machine learning. That's how I came across with your channel. 4 months ago I took a 60 hrs course in Python 3 which was based in the Cisco PCPA. These courses are free in my city because of a Microsoft techspark project they did with the Mexican government. My dream is to get an Entry level job in Data science I just have my High School Degree but if I get a job with the salary they have for entry level positions in my city I will be able to pay my college right now I have 2 daughters and my wife is pregnant and making 100dlls a week! I know it sounds crazy but the economy in Mexico is very different. I just wanted to say thank you for all the quality content and give you some context on the audience you reach and might not have an idea you are helping a lot of people. Honestly Thank you.
"...so when I understood that R was barbaric, I switched over and learnt Python." Luke you're a savage and the R community will be coming for you. 😀😀😂😂 I'm living for this R vs Python "debate".
Why is R considered 'barbaric' though? If anything, I find it a clean and simple language that doesn't try too hard to do everything like python. It only lives for data analysis and it does the job excellently. If only I could wrap my head around its love affair with lists and the ***apply family of functions!
Funny thing is, while R may be barbaric, the R user community is pretty polite and equitable. Notice I didn't say anything negative about Python itself in that video, just the vast army of Python Fanboys. 😉
@@faustin289 I was saying "Barbaric" as a joke! R is a very decent tool IMO for a data analyst! I'm just Python Fanboy, so I'm obliged to say rude things like that 🤣
Luke, I'm on the final module of the Google Data Analyst Certificate, learning R. I too wondered why I was learning R since job posts more often asked for Python. I learned Intermediate JavaScript so understood foundational programming before this course. I like using Sheets & SQL but feel I need to dive deeper into Excel. I love this journey and wish I could plug my brain into learning multiple languages at once -- Python, advanced SQL and advanced Excel functions. This video pushed me to subscribe, thank you for the analysis!
"I myself started with r on my journey, and realized when r became barbaric I switched" -Luke. Dude starting on projects not long ago with r, I really feel this one. I came from a biomedical science background and learning r for my minor bioinformatics. I didn't had any expectations whatsoever and had no idea about programming at all. Coming from no background, r has been really challenging and fun experience to learn. The learning process of r had really much similarities between my background and the syntax. Didn't thought that statistical analysis was really fun to work with, since I had only used excel for statistics before.
😂 I really didn’t think many people were going to catch me saying that… hahaha Awesome to hear about the projects with R, it can be tough at time but totally worth it. So much better then dealing with spreadsheets alone for analysis.
Luke you should be supervising masters students. You just did a hypothesis testing supported by a mixed qualitative and quantitative analysis. Brilliant! No kiding. You should be supervising those kids. You'd be a super lecturer. Thanks for the video and take care.
Aww Bouseaux, thanks for the kind words my friend!! And ha, I wouldn't mind teaching a class one day, but glad you noticed the motive behind my video! 🙌🏼 May need to do more videos like this!
Hi Luke, like always great video. I completely agree with your analysis. I am a python fanboy, but you are right. Python is not a requirement for a lot of cases. Having said that, I do believe that having Python under your skill belt is a plus. Same goes with knowing R. Oh I also use datacamp.
Also I would argue due to the popularity of python its easier to get resources about it in order to get decent / above average with it . Within the course, to go with R, is to make sure that there is a definitive base skill level for it; while with python you can learnt that anywhere to a decent degree.
Ty for the advices! I started with R and now I am using python because I like working in other programming stuffs such as automatization and webscrapping
Your videos❤😩😩 I just can’t stop watching, been binging all night and I can’t get enough. Thank you so much Luke, I’m a newbie to Data Analysis, I’m about to start out even though I haven’t even gotten a Laptop yet. I’m hopeful to start out as soon as I have saved enough for a HP or Dell Laptop. I’m glad I have a background on excel from computer lessons my mum enrolled me at after junior highschool here in Nigeria. Studied Nutrition in the university and becoming a Data analyst on Food, diet and the medical sector sounds really nice🥺. I am definitely doing this, might take sometime but surely it would happen. Once again, thank you Mr. Luke, you inspire me alot and your contents are so wholesome. It’s liberating, it gives me a feel that this is achievable because of how well and easy you’ve broken it down. I’ll sleep now, sadly I can’t get even 4 hours sleep from now (it’s 4:16 am in Nigeria) because I have to work this morning but it’s been so worth it😅.
Hey Luke! Amazing video. This video speaks exactly my thoughts. I have been thinking why people are not focusing on skills like Excel & SQL and straightaway diving into Python libraries. Phew! I realized this early & started working on Excel & SQL.
Hey, Luke! Thank you so much for this informative video. I think that maybe I am living my life backwards, but I am halfway through learning R with DataCamp, and was planning to flow directly into learning SQL > XL > PowerBI. I know that this might be against your recommendations, but it is really helping me understand the world of data analysis better and it teaches me how to think in those terms. This as I come from a completely different background as an ESL teacher. But anyway, I love R and your channel both jajaja!
Hey Samuel, the recommendation I provided here was a generalization focused on those that want to enter the world of data analytics and get a job quick. There is no "perfect" path. The fact that you are motivated enough to continue your studies with R while also learning data analysis is good enough in my book!! Keep up the hard work and studies!!
This was GREAT!! I liked the R portion most of all from the Google DA Cert course. I was wondering the differences between the two and if I was missing out on anything with Python. You definitely hear a ton more about Python than R. The thing I like about R is it's quick and dirty capabilities. You can go from CSV to visualizations within a minute or two on a large dataset. You definitely can get to know quite a bit about a dataset in a short time w/ R. I would like to learn more Python soon, but it's not as urgent as I thought it might be. Thanks man!
My personal experience was pretty much the same as that you pictured: -started with excel + some vba code -SQL fundamentals -Matlab for university -R as my very first data analysis/science environment -python for everything If I were good at, I'd probably keep on working with both R and Python. Even if Python it's the one I prefer, I have to admit that R is much easier as starting point. Many less libraries mean much less confusion and let u focus on few crucial ones. I miss its outstanding libraries for statistic tests and the way u can insert inputs according your needs.
I got my certification through the Google courses. I honestly think that R is far more difficult to learn than Python. I'm teaching myself the latter and i'm finding it's easier to learn (without much guidance) than R (with the courses guidance). So, with that said, I'm not sure whether or not R is inherently more difficult than Python, or if the course's teaching style simply didn't match my learning style. But yeah, I've really enjoyed Python and mostly resented R.
Everybody has their own learning style, so I agree with you that its hard to say... is it the learning method or is it the language? Either way, you are proceeding forward with learning a language which is A+ is my book! Keep up the hard work Christian!!!
In my opinion..lets not have roadblock on what tech to master..Its basically on the usecase we handle..If its about deployment, deeplearning , nlp, oops, scraping -- python is my choice..If its about statistical test, market basket analysis, other eda analysis -- R is my choice..It depends on community interest on a specific algorithm..
i started with python first as I started learning data science through a government subsidized diploma which teaches Python/Tableau by default. It was the most cost efficient way for me.However, I am looking to pickup R as it is the preferred language that the analytics department at my company uses. im currently in a non-analytics role but i still find python useful in automating some tasks, manipulating data with pandas etc. that would take me hours on excel.
Thank sooooo much for this vid.... I want to break in into the tech world and I wanted to be a data analyst but did not know the path I should go to achieve such goals... thank you for providing all the 8nfo I need to start on my journey
As an economist, I use R for econometric/spatial/general data analysis and now I'm also getting into shiny dashboards, which allow me to present results nicely. I've very limited knowledge of Python, but my goal with it is learning web scraping and other stuff that R can't do as well... Same with SQL, which I'm using to query huge databases.
Take love Luke. You are amazing. Your analysis is much mind blowing. No one talk me that I should be master of Excel.All of them said, start with python. Most of the article and videos give important on python first.Your recommendation is blessing of new comer. Thank you. Actually I was looking such as video.You have given all answer of my query. ❤️😇
I like this little R vs Python fight. for sure each community will strive to develop further modules and packages and refine them. we will all benefit from that. personally I want to love both of them. I use a lot microsoft solution and have the impression python is used a lot with azure to transform and load the data. and R is used to support machine learning solutions like machine learning studio. I wonder if google is going that route? thanks for the video Luke!
The issue at hand is that no video has segregated the use and value of using either language for a specific purpose. Overall, while both R and Python languages achieve almost the same results, they show them using different visuals and representations depending on the purpose. Usually, they are looked at their work dealing with statical results. R language is mostly popular among the scientific community, universities, and large and sophisticated organizations. It’s used for a lot of advanced statistical analysis that most organizations will never need to use. Python, on the other hand, is mostly used for the analysis of the average business world from small to midsize companies, and even large. Most data analysts get bogged down into details about tools rather than the actual use case. I feel that looking into LI job postings should be enough to tell you what path you’re following. One must examine oneself and decide the path to follow rather than the tools. Knowing oneself and passion will help you then decide on the tools. Am I looking for a sophisticated organization that needs more a Data Science person? This role is more sophisticated as if would go into more advanced analytics techniques and technologies. Or, am I looking into companies that want a more entrepreneurial person with more business acumen to find business insights for a company? A data analyst role would then be more appropriate for this role as it will deal with data is spreadsheets and simple databases. From here, we can then determine the types of tools that would be more effective and the language. Yet, we can do more with Python if looked outside statistical needs and analytics needs. We can build things that R simply is not designed for.
I'm not a data scientist. Just interested in the field as an amateur. @Luke, we need more people like you, in any field and not just tech, who calmly and objectively try to understand how to improve their area of work, rather than denigrating people like this Al person did. Great video. Keep up the good work and the attitude.
Thanks for the kind words!!! Oh BTW Al is a great dude!! He was only saying the things he did as a joke. I in NO WAY was trying to make Al seem like he was abad dude, I really enjoyed his humor on this subject so I wanted to share it!
Hey Luke, I love your videos so much I've found myself binge-watching them lately. You compare a lot about the certificates, but I'm curious as to what data science boot camp program you would recommend to a friend. I think it would be a good idea for a video as the boot camps most often build on top of the certificates.
Hey Michael, I've never taken a boot camp program, per se. I'd have to investigate thsi further to find out more. Most of my learnings have been through e-learning platforms like Coursera and DataCamp as they were lower cost options for me
cool video, my only problem with this analysis is scraping ALL job postings. Outs of those 150k, a lot might be skecthy or simply undesirable jobs. As a statistician who recently spent a lot of time looking for my first job, I haven't seen a job offering talking about Tableau even once
as an accountant who is learning this stuff the reason why excel is so popular is because us finance folks live in excel. you have to think about the end user when you do your data analytics and using excel as a canvas for your final product will make non data analyst folks feel more comfortable.
Luke you are one of the best data analytics youtubers that I'm a big fun of.I'm a computer science student in my last year andhaving both skills and interests in both data analytics and IOT fields , however wondering which one holds the most demand for entry job . What do you think ?
Hey Charaf, thanks for the kind words my dude!! I'm not too familiar with the job demand in IOT, but for data analytics I feel like it's staying positive. Plus is can be applied in so many different industries that I really feel it's promising... Good luck in your studies!
As someone in the data science community(analyst/ETL/DataEngineering) I would generally agree with this video. SQL really is the foundational skill you need before Python or R. Writing proper, and specific queries will save you so much time and effort. Whether the data is local, or in a cloud based service, you need to know SQL to even interact with it. You will never analyze the data if you cant write sql to retrieve it. That being said, I still think Python is easier for beginners vs R because the syntax is considerably easier. Python is generally written in plain english whereas R has a lot of funky syntax. That being said, R is still very useful and certainly beats python when dealing with floating point numbers.
Stellar Vid. I got a lot of anxiety thinking " Oh crap, I've wasted so much time doing nothing, now look at this mountain of work I need to tackle. AND I"M STILL GONNA PROCRASTINATE" but you know.... I'm kind of... sick and tired of being sick and tired man. I GOTTA BE ABOVE IT !
Used to use R to implement statistics models into my analysis on risk. However, the vast majority of dudes in my team work with python so do not see any difference in it, R is just a bit easier for me in terms of syntaxis 😀
I just started the Module in the Google Data Analytics Certification on Coursera where they start with R programming. I feel, because I am from a completely non technical background, it is both high and low for me now. The high being that since I am not aware about any programming language at all, I just have to start with something, which is R, currently. And the low being too many reviews from experts about how one is better than the other are giving me a scare. But like you mentioned, I am just at the beginning level of Data Analytics, switching careers after a 15 year run into HR. So, I'd rather focus on R, probably practice more of Tableau and SQL before I think about going with a specific programming language.
I'm also on the Google Data Analytics Certification. Been in music education for ten years (teaching). I'm enjoying it! I do plan to take other courses on Python soon. Can't wait to see where it takes me.
Thanks for your analysis and comparison between Python and R. Personally, I think both programming languages are useful for data analysis, but these tools are not enough for data analysts since we also need to master other tools like SQL, Tableau, Power BI, and speadsheets. By the way, I really like the way you use Python to collect relevant job information from LinkedIn to make analysis. Since I'm doing the Google DA certificate, I'll have to learn R first. After finishing, I've planned to do the track Data Analyst with Python from datacamp because I think I can learn the most of Python for data analysis here. Your learning journey of Python really encourages me to follow my learning pathway. So thanks again and I'm looking forward to your new videos!
For some, in data analytics, learning Python may very well be an unneeded distraction, when R is so much more to the point. Learn the one language you need, and learn it well. Google just might have it right here.
if you are learing python as a data analyst, better learn cython too. If ur code is running in a few minutes, then its fine. But if it takes hours, or days to run, then better implement cython. That being said, most of the code optimization can be done in the structure of the code (less nested for loop and if-else statement). Numpy array operation is a way to achieve this. In my case I am comfortable with both python and C. So, whenever I need speed I wrote a piece in C and link to my python code.
So I am getting my bachelor's this summer and learnd the basics of both r and python. I can confidently say, that the most common limitation with either of the two is your own knowledge. That said, i prefer to work with R simply because it comes more naturally to me and usually my intuition gets me to where i want to be more often than not. Programming in Python often feels like a fight...
Most criticisms of R I read are blatantly wrong. People who throw shade seem to have last interacted with the language in 2012. I also agree that R is easier to learn. Finally, if you come from a statistics background, as opposed to comp sci, R may actually provide more job opportunities, as you can look for both Statistician as well as data analyst / scientist positions.
I have learn Python a little bit and now i just start Google cert. with R. I think R is more easily in term of picking up the basic in data analysis. Actually I think both R and Python are good at data field.
Python is such a great language to learn as you can apply it rather simply to a LOT of problems. I have a bit of an issue with the habit of learning a lot of different programming languages when I could just get better with one more flexible tool.
In your journey to learn data analytics, and understanding all these programs, were you able to tackle all your education on a Mac? Or did you split the programs between a Mac and PC?
As a software engineer I find python barbaric. Statically typed, compiled languages just kick ass in the long run. It's ok for data analysis scripts but R is probably better for that specific job. Turns out being a jack of all trades, master of none language has served Python well. Overrated imo
I learned Java first and missed the strong typing and elegant autopromotion and polymorphism. But after many years of coding, typehints in python seems pretty sufficient for building powerful data analysis and ML pipelines. Of course if you want to do anything superfast, it's best to implement in c++, and interface with python or R.
languages are engineering tools; what determines the effectiveness of a language for a problem domain is usually the body of legacy code written for that domain and it’s reliability and efficacy, which is derived from the dedication of a language’s users, rather than the grand forward planning and wisdom of its designers use any language long enough, learn enough of them, and you start to realize that we programmers have to be shrewd with our application of these different models of computation like statisticians and scientists are with their models of natural phenomena: recognizing that all are wrong, but some are occasionally useful
Just think about it through the inequality lens: disadvantaged R users are partly supported by such google actions, no big deal, good news for R users, not a big problem for Python users, given the amount of available materials
I've learnt both R and Python as part of my degree - Starteed a job as an OT engineer, and anyone who used R is gone from the business - everything is M, Dax, Python, SQL. Even the machine learning machines (that used shiny apps in docker) are not being used anymore - its all being pushed to the cloud. Its a crap shoot as to what your future business will use. But learn Python as a sure thing, it can actually do a range of things beyond data analysis.
I work with both Python and R. I love Python as a programming language, it reminds me of Perl in some ways. When it comes to statistical analysis, I find it very satisfying to use R. I highly recommend being multilingual and picking a language that you love and perfecting it than letting Google or job trends dictate that choice.
Really interesting having just discovered your videos, I'm an experienced Data Analyst in the Education sector (6 years and a further 4 in Emergency Services) and my main tools have been Excel and to a greater extent R (with a sprinkling of SQL). For the type of analysis I do, I've found R much more useful than Python. I have however, felt I need to learn Python due to many advertised Data Analyst roles asking for it, when thinking of the next step of my career. But as I don't use it everyday at the moment, it is hard to retain that information so I'm looking for ways to incorporate Python into some of my regular work. Food for thought... as I feel I've stagnated a bit and stayed safe with Excel and R.
Thanks for sharing this, and glad you found my channel! Both Excel and R (more specifically) can be such powerful tools as you've shown here. Thanks for sharing your perspective on Python and R!
@@LukeBarousse Thanks Luke, it's inspired me to get back to learning Python again, so I'm going to pick that up again this week at work. So thank you for inadvertently doing that 🙂👍. Subbed and I will be watching with interest from now on. Rob
Luke, you are the man, loved how you approached this without ego. I rarely write comments but you got me pumped up. Without knowing it, you described my career path: Excel ✓ Power Bi ✓ SQL ✓ (funny thing here, I thought I knew R but with your explanation I don't lol) Python - Just started a few weeks ago and very pumped! I will probably end with R but I feel I have a long way to go with Python. Thanks for your content it's great!
The point is that Python might not be better than R in Google’s view but Python required jobs are more abundant so you would not waste valuable learning time on something you will never use
That information is quite good for me. I already work with excel VBA, power query and power Pivot. My role is to automatize projects and reports. I already developed a project using python as well. Unfortunately I can't share because it contains company's information. But I guess I am almost ready to transition.
Thankyou for the guidance. I was looking for this from months. Everyone out there know alot but you put it in the bestway. Mastering Excel SQL visualization/programming skills. Its a path for beginners. God bless
Hi Luke, thank you for sharing this video. I believe I'm not the only DA noob that got stuck in the weeds of R vs Python. You did a great job with explaining that there is so much to be learned before this question makes any sense for beginners. Could you please recommend any Excel learning resources? Or do you remain firmly with GDAPC being the one-stop-shop for beginners?
Hey Marko, I think the GDAPC is a good introduction... but def not the final resource for mastering excel. I personally used this book (along with a course I took in college) to better master Excel. amzn.to/2Xj14qe
Honestly I just don't wanna learn a new programming tools when I already got one that I can use reliably. I don't get why people think Python is better. It's just a matter of saving time and effort from my side.
If i want to work as a machine learning engineer or data scientist one day which entry level job role should i start applying to get my foot in the door in the industry?? I dont mind starting from the bottom and working my way up.
I'm not concerned with automation at this moment in impacting data analytics. The BIGGER problem we are facing RN in this community is establishing data pipelines for CLEAN data. I feel companies are going to be investing heavily in this and this is the future problem data analysts need to be thinking about.
I think any work related to analysis will be difficult to be replaced by machines for a long time because the hardest part in analyzing this kind of work is probably because it takes into account human nature and the psychology of customers. This is a feeling that is difficult to reflect in the data depends on the empirical judgment of analysts.
Hey Luke, I’ve just come across your channel today and I can not be more grateful about your content. Your easy-to-follow guides to data analytics and how to entry these kind of jobs are excellent! I have a question though, I’m finishing a computer science degree right now, where I’ve learnt quite a bit of everything (R, Python, C, Java, sql, etc) but nothing in full detail (apart from Python which I learnt myself at job). What would you recommend me going for after finishing the degree and the Google Certificate? Mastering Excel/SQL? Thank you in advance and have a nice 2022!!
No problem at all! Glad you are enjoying the content!! And yeah I would recommend Excel/SQL (that is if you are interested in becoming a data analyst). I made a new video on this recently, not sure if you saw it yet: th-cam.com/video/aqRxZSrJLEc/w-d-xo.html
I know Python and SQL pretty well. Should I learn Excel, R, (Tableau or Power Bi) now? Or maybe theory like statistics and further knowledge in pandas, numpy and matplotlib?
Thanks for all the content!!! Much appreciated and highly enjoyable :) I have a question though. Being in mid-career, wanting to add some skills I'm currently taking the Google Analytics cert, however I wanted to add Phyton as well. Being a newbie, and needing to do the grunt work is the Coursera Crash course or Udemy's Phyton BootCamp recommended for this or any other course to consider instead?
Hi Luke, in the Capstone project phase of Google Data Analytics. And I seem to be able to use merely just R to cover the entire phase from Ask, Prepare, Process, Analyze, Share, to Act. I wonder, when is it that I will be required to use Excel/SQL by necessity to analyze data?
In the course? I'm not too sure but I feel it covers the basics of Excel and SQL during the course. As demonstrated in this video Excel and SQL are highly valuable skills for data analysis and you'll be requested to use these skills as a data analysts. Although you may not use Excel and SQL in your capstone, that doens't mean a data analyst doesn't use it in their real job
@@LukeBarousse sure thing .. Keep up with great content ! Python will have to be on my learning path but I am combining it with Julia after I get a good grasp on starting and finishing project with R
Paused at the 1:12 mark: "Do data analysts really need to learn Python?" No, they can get by just fine with the many other tools available. The exact same answer could be given about R, or pretty much any other tool. Ironically the software that is probably the most irreplicable is fricking excel.
Job posting of data analyst in your area inferred that Python is a most demand skill than R? Could it be the case that Python just happens to be most popular and not most useful? The fact that more companies ask for it does not mean you should learn it as a data analyst. R is so much better at data visualization and data wrangling than Python is.
Umm, I showed that python and R are NOT the most important and that Excel and SQL are! But to your point, yes Python may be overly hyped, but it doesn't take away that it's listed more in job descriptions than R. With companies using more AI/ML to filter out candidates for skills based on what they list on their resume, I think others need to know keywords to use to ensure they get noticed for a job!
@@LukeBarousse so you mean the title should be "what tools to learn to increase the chances of landing a job as a data analyst". Either way, I should have started with props. Great video and initiative.
@@jdlopez131 Agree that that's a better title... but unfortunately with the TH-cam algorithm I need titles like these to reach more people. 😒 Nonetheless thanks for the kind words Jorge and I appreciate your perspective!!
***I was just scrolling down and reading the comments ans I was amazed that you actually replied to all of em...*** I use python for data science although my journey started with R in data science. But the only reason I don't use R because of..........idk
The principal idea is not to program with one or other, most of the time u will just search in internet a solution for a problem that appear with your problem, and replicate it. So if u know read codes in R and python and understand it, you gonna have more ways to take an ideia to solve your problem. So, i think u can go to any language R/python but at least need to understand both.
I realize this vid is taking about Data Analysts. But for Data Scientists, you will want to know both Python and R. Just like Google, my master's program in DS started out in R and then switched to Python. In the job market, your competition will be people who are proficient in both. Excel? Well, when your dataset consists of millions of untidy records, Excel is like a knife at a gunfight. SQL? Of course, that goes without saying. As a Data Scientist, you will need Python, R and SQL.
An perhaps intangible factor related to R is that, because it was built for statistics by statisticians and is used for academic research in traditional conservative sectors such as health||biotech|pharma|consulting, it enjoys, right or wrong, a degree of respectability that more common. mainstream languages do not. It also signals, right or wrong, that one has a basic knowledge and appreciation for stats.
I once wrote a program in R and it took 40 minutes to process 200+ CSV files and this was not acceptable. I re-wrote the program in python and it completed the task in 3 minutes. I then put R aside and specialized in python. Be good in one language R/python but really good. it is better to be good at one language really well than being a master of none :) . R script is a little simplier than python but once you get familiar, python is fun and powerful
I would absolutely love an in-depth tutorial from beginning to end on how you put your web-scraping script together.
If this comments gets some more likes, I'm definitely down for this!!!
+1
@@LukeBarousse Please do this.....
Subscribing so I don't miss this vid!
@@LukeBarousse I was about 5 minutes into your video and had the same thought. I would absolutely love a tutorial on creating a web-scraping tool specifically to look at new job positions on Indeed or Linked In. Probably going to send you an email asking if I could pay to have you put together a tutorial. It would be invaluable.
I work with both R and python on a daily basis, from a statistical tool stand point the R ecosystem is better, more statistical tests are available, with more statistics (like confidence intervals) and under the hood the implementation tends to be more accurate, also for a beginner with a stat background R api is closer to the theory so it's faster to pickup. Python is way better as a general purpose programming language hands down. I'm working on porting some of R's statistical tools to python
Very much agree with this my dude! Thanks for sharing this!
the R api being closer to theory and math terminology is spot on, that's why it's preferred for data science positions that utilize math more
وين تعلمت خويا هذا المجال ؟ من ڨوڨل سارتيفيكايت ؟ راني حاب نبدا هذا المجال اذا عندك roadmap نكون مشكور ليك الله يحفظك
Agreed. I think they both have their purposes and as a statistical tool R is the way to go. Python has a bit of catching up to do but it will for sure.
Did you learn R first or Python for data analytics? I started with Python in the beginning for basics & then moved to R. I didn't learn Python libraries but I have learned some R libraries. Now I feel these libraries are pretty overwhelming.
I am thinking to go back to python.
How do you use Python (or R) for data analytics?
ALSO, Al Bellamy and I are GOOD FRIENDS and we pick on each other all the time. I don't think I communicated this well in the video, so wanted to clarify that Al meant no ill intention with his comments and neither did I with mine.
I have barely managed the python basics and now R ????
@@shraddhaverma4111 Pick one and go from there!
I approach this issue the same way I do MS Excel and Google Sheet. I use one as my daily driver and the other when I must.
I use both. I find everything-data to be much easier to accomplish in R up until the point when your data product needs to be a cog in a bigger machine. Then it's Python.
@@kwamsahortor Thanks for sharing this!! I like this approach
I made some research on this topic at our University. Statistically, many IT students, prefer Phyton over R and it was no surprise because many of them think that Phyton is more dynamic and easy to understand, where as r needs to type complex syntax to perform operations. But I prefer R for doing statistical analysis and other stuff. With R, I think you'll be able to to to the deeper insights into a statistics. Glory to those R diehards.
Ha! I can appreciate me some R!
My first programming language was Java. If you understand most programming languages including R, you can pick up how to use Python. These people who are complaining act like it's a war crime. They need to chill.
It is pretty common for python to thrown into people's faces.
I have often noticed people focus on the seemingly cool stuff like coding too much without the basic understanding. I have an IT background and currently a BI Developer. My preferred list would be the following:
1. Get enough knowledge of Statistics
2. Use one simple statistics tool with a Graphical User Interface e.g SPSS, Stata, etc
3. Sharpen your MS Excel skills
4. Learn SQL for data analysis
5. BI tool or Visialization tool e.g. Power BI, Tableau
5. Learn a Data Science programming language e.g python, SAS, R
6. Build projects
I'm sure you'll be the complete package. Thank me later 😊😊
you didnt give any clue about python or R 1st. No thanks!
Start with Excel. It's indispensable . I learned R before I learned SQL. Once you learn the dyplr package of R, SQL will be a breeze. SQL is not that hard once you understand the principles of data manipulation and R is a great way to learn that.
People should learn from you how to take criticism in the most positive way before learning anything that is to do with data analytics. Great video. And savage response by giving a shoutout to the same person. 😂
ha! I try to be savage! Thanks for watching!!
That was a perfect response to criticism.
Great video and analysis there, hi Luke, I'm a Software Engineer from Guatemala and currently I'm working as a Data Analyst. Personally, there are a couple of points that I'd like to mention that I strongly believe are worthy, in order to have a healthy discussion. I use Spark, Python and SQL almost every day on my job, like each language to me has its own pros and cons. I used to work as a DBA, so I have a couple of second thoughts regarding SQL haha. I do agree that Excel, R and SQL are good foundational languages to start in this field, and I'm not a Python fan, or better said, I'm not advocating for any language, to me, the tool, or language of choice, will depend on the needs of your project, and the community you have. Like, why would you use SQL or Python or R or any language, when you can actually combine them. My advice, would be, don't marry any language or tool, because that's all what they are: TOOLS.
Boom! Love this knowledge bomb Hugo! Thanks for sharing this. Very much agree with your perspective. You need multiple tools in order to succeed as a data analyst!
Very wise!! sometimes the tools are more googleable for certain tasks :) vba + python + sql work wonders
I love this.
I actually genuinely love using R. It's really the first programming language (I don't count SQL as it's not really the same thing as I see it) that I've tackled after studying C++ for years and studying basic Linux kernel scripting and it is honestly fun. I've never felt so confident with optimizing my code before. Also, it is ridiculously easy for me to grasp most new concepts. I won't lie, I haven't looked much into python, with only a couple hours of it under my belt, but I think I will always be attached to R. Also, sidenote Rstudio is a fantastic IDE for all the above languages. Imho. Thanks for the video, I watched it before starting the Google Certificate and again now.
Can completely agree with this for R, it's def a great option to use. Thanks for sharing Clyde!
Hey Luke,
I am currently taking 3 courses 2 hrs a day 2 days a week for 10 weeks. Data Analysis with R & RStudio, Data Analysis with Python Anaconda and Python basic Machine learning. That's how I came across with your channel. 4 months ago I took a 60 hrs course in Python 3 which was based in the Cisco PCPA. These courses are free in my city because of a Microsoft techspark project they did with the Mexican government. My dream is to get an Entry level job in Data science I just have my High School Degree but if I get a job with the salary they have for entry level positions in my city I will be able to pay my college right now I have 2 daughters and my wife is pregnant and making 100dlls a week! I know it sounds crazy but the economy in Mexico is very different.
I just wanted to say thank you for all the quality content and give you some context on the audience you reach and might not have an idea you are helping a lot of people.
Honestly Thank you.
Thanks for sharing this Cris, Good luck with your journey in data science. I admire your hard work and perseverance. You got this my dude!!
"...so when I understood that R was barbaric, I switched over and learnt Python." Luke you're a savage and the R community will be coming for you. 😀😀😂😂 I'm living for this R vs Python "debate".
I got my shields ready... I'm ready to take on the R nerds... hahahaha Thanks Michael!!
Why is R considered 'barbaric' though?
If anything, I find it a clean and simple language that doesn't try too hard to do everything like python. It only lives for data analysis and it does the job excellently.
If only I could wrap my head around its love affair with lists and the ***apply family of functions!
Funny thing is, while R may be barbaric, the R user community is pretty polite and equitable. Notice I didn't say anything negative about Python itself in that video, just the vast army of Python Fanboys. 😉
@@Major_Data There are no rules in Python Fanboy land!! We take no prisoners!! 😂
@@faustin289 I was saying "Barbaric" as a joke! R is a very decent tool IMO for a data analyst! I'm just Python Fanboy, so I'm obliged to say rude things like that 🤣
Luke, I'm on the final module of the Google Data Analyst Certificate, learning R. I too wondered why I was learning R since job posts more often asked for Python. I learned Intermediate JavaScript so understood foundational programming before this course. I like using Sheets & SQL but feel I need to dive deeper into Excel. I love this journey and wish I could plug my brain into learning multiple languages at once -- Python, advanced SQL and advanced Excel functions. This video pushed me to subscribe, thank you for the analysis!
Heck yeah, good luck with finishing up the certificate!
"I myself started with r on my journey, and realized when r became barbaric I switched" -Luke. Dude starting on projects not long ago with r, I really feel this one. I came from a biomedical science background and learning r for my minor bioinformatics. I didn't had any expectations whatsoever and had no idea about programming at all. Coming from no background, r has been really challenging and fun experience to learn. The learning process of r had really much similarities between my background and the syntax. Didn't thought that statistical analysis was really fun to work with, since I had only used excel for statistics before.
😂 I really didn’t think many people were going to catch me saying that… hahaha
Awesome to hear about the projects with R, it can be tough at time but totally worth it. So much better then dealing with spreadsheets alone for analysis.
Luke you should be supervising masters students. You just did a hypothesis testing supported by a mixed qualitative and quantitative analysis. Brilliant! No kiding. You should be supervising those kids. You'd be a super lecturer. Thanks for the video and take care.
Aww Bouseaux, thanks for the kind words my friend!! And ha, I wouldn't mind teaching a class one day, but glad you noticed the motive behind my video! 🙌🏼 May need to do more videos like this!
Hi Luke, like always great video. I completely agree with your analysis. I am a python fanboy, but you are right. Python is not a requirement for a lot of cases. Having said that, I do believe that having Python under your skill belt is a plus. Same goes with knowing R. Oh I also use datacamp.
Heck yeah thanks for sharing this Marco! Glad to have you as a fellow "Python Fanboy"!! Very much agree with your assessment of Python and R.
Also I would argue due to the popularity of python its easier to get resources about it in order to get decent / above average with it . Within the course, to go with R, is to make sure that there is a definitive base skill level for it; while with python you can learnt that anywhere to a decent degree.
Excellent video! I especially appreciate you opening up the scope and sharing the other tools that are important!
Thanks for this Moon!!
Ty for the advices! I started with R and now I am using python because I like working in other programming stuffs such as automatization and webscrapping
Heck yeah, thanks for sharing this Wilson, such a good reason to switch over to Python!
Your videos❤😩😩
I just can’t stop watching, been binging all night and I can’t get enough.
Thank you so much Luke, I’m a newbie to Data Analysis, I’m about to start out even though I haven’t even gotten a Laptop yet. I’m hopeful to start out as soon as I have saved enough for a HP or Dell Laptop.
I’m glad I have a background on excel from computer lessons my mum enrolled me at after junior highschool here in Nigeria.
Studied Nutrition in the university and becoming a Data analyst on Food, diet and the medical sector sounds really nice🥺. I am definitely doing this, might take sometime but surely it would happen.
Once again, thank you Mr. Luke, you inspire me alot and your contents are so wholesome.
It’s liberating, it gives me a feel that this is achievable because of how well and easy you’ve broken it down.
I’ll sleep now, sadly I can’t get even 4 hours sleep from now (it’s 4:16 am in Nigeria) because I have to work this morning but it’s been so worth it😅.
Glad you have been enjoying the videos!!
Good luck on your learning journey you got this! 🙌🏼
Hey Luke!
Amazing video.
This video speaks exactly my thoughts. I have been thinking why people are not focusing on skills like Excel & SQL and straightaway diving into Python libraries.
Phew! I realized this early & started working on Excel & SQL.
You're on the right track Vivek! To often (including myself) we get lured into learning Python before learning other important skills
I use R, google sheets and Java for all analysis. Never had to touch python at all. But it depends on where you work and what their tech stack is.
Thanks for sharing this tech stack, I agree depends on where you work!
Thank you Luke, Have a great day!
Personally I finished the Google Analytics certification and started to learn Python in my own pace.
This is awesome to hear Eyal! Good luck with your Python studies, you won't regret it
Hey, Luke! Thank you so much for this informative video.
I think that maybe I am living my life backwards, but I am halfway through learning R with DataCamp, and was planning to flow directly into learning SQL > XL > PowerBI.
I know that this might be against your recommendations, but it is really helping me understand the world of data analysis better and it teaches me how to think in those terms. This as I come from a completely different background as an ESL teacher.
But anyway, I love R and your channel both jajaja!
Hey Samuel, the recommendation I provided here was a generalization focused on those that want to enter the world of data analytics and get a job quick. There is no "perfect" path. The fact that you are motivated enough to continue your studies with R while also learning data analysis is good enough in my book!! Keep up the hard work and studies!!
In Sweden, Power Bi is about 5 times more likely to be in postings than Tableau.
This was GREAT!! I liked the R portion most of all from the Google DA Cert course. I was wondering the differences between the two and if I was missing out on anything with Python. You definitely hear a ton more about Python than R. The thing I like about R is it's quick and dirty capabilities. You can go from CSV to visualizations within a minute or two on a large dataset. You definitely can get to know quite a bit about a dataset in a short time w/ R. I would like to learn more Python soon, but it's not as urgent as I thought it might be. Thanks man!
Yep, def not as urgent!! If R is getting your job done then it is good enough and stick with it to master it!! Thanks for sharing this Philip!
Bullllseye on the analysis & presentation! My guy doesn’t miss. Great stuff dude
My personal experience was pretty much the same as that you pictured:
-started with excel + some vba code
-SQL fundamentals
-Matlab for university
-R as my very first data analysis/science environment
-python for everything
If I were good at, I'd probably keep on working with both R and Python.
Even if Python it's the one I prefer, I have to admit that R is much easier as starting point. Many less libraries mean much less confusion and let u focus on few crucial ones. I miss its outstanding libraries for statistic tests and the way u can insert inputs according your needs.
Thanks for sharing this perspective. Very much agree about the ease of learning R as well and it still being a powerful language!!
I got my certification through the Google courses. I honestly think that R is far more difficult to learn than Python. I'm teaching myself the latter and i'm finding it's easier to learn (without much guidance) than R (with the courses guidance). So, with that said, I'm not sure whether or not R is inherently more difficult than Python, or if the course's teaching style simply didn't match my learning style.
But yeah, I've really enjoyed Python and mostly resented R.
And then following this, I absolutely love SQL and would be 1000% happy if my entire day was spent in it.
Everybody has their own learning style, so I agree with you that its hard to say... is it the learning method or is it the language? Either way, you are proceeding forward with learning a language which is A+ is my book! Keep up the hard work Christian!!!
In my opinion..lets not have roadblock on what tech to master..Its basically on the usecase we handle..If its about deployment, deeplearning , nlp, oops, scraping -- python is my choice..If its about statistical test, market basket analysis, other eda analysis -- R is my choice..It depends on community interest on a specific algorithm..
BoOOm!! Very much agree with this Arvind!!!
Love your sincerity in your viewpoints. Always Top Top quality from you Luke
Luke every video is EYE opener. BIG THANKS!!!!!
Thank you!
i started with python first as I started learning data science through a government subsidized diploma which teaches Python/Tableau by default. It was the most cost efficient way for me.However, I am looking to pickup R as it is the preferred language that the analytics department at my company uses. im currently in a non-analytics role but i still find python useful in automating some tasks, manipulating data with pandas etc. that would take me hours on excel.
Yeah I think they are both great. It’s awesome to hear how you are applying both!!
Thank sooooo much for this vid.... I want to break in into the tech world and I wanted to be a data analyst but did not know the path I should go to achieve such goals... thank you for providing all the 8nfo I need to start on my journey
Aw thanks for this Julio! Keep up the positive vibes my dude, you got this!
As an economist, I use R for econometric/spatial/general data analysis and now I'm also getting into shiny dashboards, which allow me to present results nicely. I've very limited knowledge of Python, but my goal with it is learning web scraping and other stuff that R can't do as well... Same with SQL, which I'm using to query huge databases.
Heck yeah, these are great goals to have with Python. I think you've picked a great reason to start learning it! good luck!
@@LukeBarousse thanks! Your content is being really useful
Take love Luke. You are amazing. Your analysis is much mind blowing. No one talk me that I should be master of Excel.All of them said, start with python. Most of the article and videos give important on python first.Your recommendation is blessing of new comer. Thank you. Actually I was looking such as video.You have given all answer of my query. ❤️😇
Heck yeah! This is so awesome to hear Rako! Good luck in your learning journey!!
Very helpful insight going into my last year of uni. Thanks.
Heck yeah, glad I could help!!
I like this little R vs Python fight. for sure each community will strive to develop further modules and packages and refine them. we will all benefit from that. personally I want to love both of them. I use a lot microsoft solution and have the impression python is used a lot with azure to transform and load the data. and R is used to support machine learning solutions like machine learning studio. I wonder if google is going that route? thanks for the video Luke!
Thanks for watching!
The issue at hand is that no video has segregated the use and value of using either language for a specific purpose.
Overall, while both R and Python languages achieve almost the same results, they show them using different visuals and representations depending on the purpose. Usually, they are looked at their work dealing with statical results.
R language is mostly popular among the scientific community, universities, and large and sophisticated organizations. It’s used for a lot of advanced statistical analysis that most organizations will never need to use.
Python, on the other hand, is mostly used for the analysis of the average business world from small to midsize companies, and even large.
Most data analysts get bogged down into details about tools rather than the actual use case. I feel that looking into LI job postings should be enough to tell you what path you’re following.
One must examine oneself and decide the path to follow rather than the tools. Knowing oneself and passion will help you then decide on the tools.
Am I looking for a sophisticated organization that needs more a Data Science person? This role is more sophisticated as if would go into more advanced analytics techniques and technologies.
Or, am I looking into companies that want a more entrepreneurial person with more business acumen to find business insights for a company? A data analyst role would then be more appropriate for this role as it will deal with data is spreadsheets and simple databases.
From here, we can then determine the types of tools that would be more effective and the language.
Yet, we can do more with Python if looked outside statistical needs and analytics needs. We can build things that R simply is not designed for.
Thanks for sharing this perspective!
Thank You Luke for putting effort and given us a brilliant idea about the same topic.
Great response, Luke! Positive and professional. Keep up the good work.
Aww thanks so much Diego!!
Dude, I haven't laughed that hard in forever. Brilliant!
I'm not gonna lie... I was a little nervous for your reaction to this 😳
Glad you got a laugh out of it!!
@@LukeBarousse I'm honored! Seriously, I should do a tutorial on how to start beefs between TH-camrs... 🤣
I'm not a data scientist. Just interested in the field as an amateur. @Luke, we need more people like you, in any field and not just tech, who calmly and objectively try to understand how to improve their area of work, rather than denigrating people like this Al person did. Great video. Keep up the good work and the attitude.
Thanks for the kind words!!! Oh BTW Al is a great dude!! He was only saying the things he did as a joke. I in NO WAY was trying to make Al seem like he was abad dude, I really enjoyed his humor on this subject so I wanted to share it!
Hey Luke, I love your videos so much I've found myself binge-watching them lately. You compare a lot about the certificates, but I'm curious as to what data science boot camp program you would recommend to a friend. I think it would be a good idea for a video as the boot camps most often build on top of the certificates.
Hey Michael, I've never taken a boot camp program, per se. I'd have to investigate thsi further to find out more. Most of my learnings have been through e-learning platforms like Coursera and DataCamp as they were lower cost options for me
As a Python fan, Python is just fun and nice to read. However, I like how you address the issue. Self reflection isn't easy.
It's never easy but must be done! Thanks for sharing this!!
cool video, my only problem with this analysis is scraping ALL job postings. Outs of those 150k, a lot might be skecthy or simply undesirable jobs. As a statistician who recently spent a lot of time looking for my first job, I haven't seen a job offering talking about Tableau even once
as an accountant who is learning this stuff the reason why excel is so popular is because us finance folks live in excel. you have to think about the end user when you do your data analytics and using excel as a canvas for your final product will make non data analyst folks feel more comfortable.
Very much agree with this, thanks for sharing this. Excel is very user friendly to a lot of people
Luke you are one of the best data analytics youtubers that I'm a big fun of.I'm a computer science student in my last year andhaving both skills and interests in both data analytics and IOT fields , however wondering which one holds the most demand for entry job . What do you think ?
Hey Charaf, thanks for the kind words my dude!! I'm not too familiar with the job demand in IOT, but for data analytics I feel like it's staying positive. Plus is can be applied in so many different industries that I really feel it's promising... Good luck in your studies!
As someone in the data science community(analyst/ETL/DataEngineering) I would generally agree with this video.
SQL really is the foundational skill you need before Python or R. Writing proper, and specific queries will save you so much time and effort. Whether the data is local, or in a cloud based service, you need to know SQL to even interact with it. You will never analyze the data if you cant write sql to retrieve it.
That being said, I still think Python is easier for beginners vs R because the syntax is considerably easier. Python is generally written in plain english whereas R has a lot of funky syntax.
That being said, R is still very useful and certainly beats python when dealing with floating point numbers.
Heck yeah, Love a fellow Python fan! Thanks for sharing this Gabriel on your perspective!
R is way easier to setup from zero
This is such a good eagle eye view on what skills to master and why
Thanks Anvesh!
Stellar Vid. I got a lot of anxiety thinking " Oh crap, I've wasted so much time doing nothing, now look at this mountain of work I need to tackle. AND I"M STILL GONNA PROCRASTINATE" but you know.... I'm kind of... sick and tired of being sick and tired man. I GOTTA BE ABOVE IT !
Love this attitude my dude!!
Used to use R to implement statistics models into my analysis on risk. However, the vast majority of dudes in my team work with python so do not see any difference in it, R is just a bit easier for me in terms of syntaxis 😀
Thanks for sharing this Daniil!! Very much agree with your assessment here!
I just started the Module in the Google Data Analytics Certification on Coursera where they start with R programming. I feel, because I am from a completely non technical background, it is both high and low for me now. The high being that since I am not aware about any programming language at all, I just have to start with something, which is R, currently. And the low being too many reviews from experts about how one is better than the other are giving me a scare. But like you mentioned, I am just at the beginning level of Data Analytics, switching careers after a 15 year run into HR. So, I'd rather focus on R, probably practice more of Tableau and SQL before I think about going with a specific programming language.
Very much agree with this Shilpa! Don't be intimidated by R, it's perfect for learning a programming language! Good luck!!
I'm also on the Google Data Analytics Certification. Been in music education for ten years (teaching). I'm enjoying it! I do plan to take other courses on Python soon. Can't wait to see where it takes me.
Thanks for your analysis and comparison between Python and R. Personally, I think both programming languages are useful for data analysis, but these tools are not enough for data analysts since we also need to master other tools like SQL, Tableau, Power BI, and speadsheets. By the way, I really like the way you use Python to collect relevant job information from LinkedIn to make analysis. Since I'm doing the Google DA certificate, I'll have to learn R first. After finishing, I've planned to do the track Data Analyst with Python from datacamp because I think I can learn the most of Python for data analysis here. Your learning journey of Python really encourages me to follow my learning pathway. So thanks again and I'm looking forward to your new videos!
Aw thanks for the kind words!! I think you have a great learning plan established for data analysis and python, so keep it up!
For some, in data analytics, learning Python may very well be an unneeded distraction, when R is so much more to the point. Learn the one language you need, and learn it well. Google just might have it right here.
Very much agree with this!! 🙌🏼
if you are learing python as a data analyst, better learn cython too. If ur code is running in a few minutes, then its fine. But if it takes hours, or days to run, then better implement cython. That being said, most of the code optimization can be done in the structure of the code (less nested for loop and if-else statement). Numpy array operation is a way to achieve this. In my case I am comfortable with both python and C. So, whenever I need speed I wrote a piece in C and link to my python code.
Thanks for sharing this hemanta, def agree on using this for speed efficiency. I typically stick with Python as my code runs fast enough for me
Enlightened. Thanks Luke!!!
So I am getting my bachelor's this summer and learnd the basics of both r and python. I can confidently say, that the most common limitation with either of the two is your own knowledge. That said, i prefer to work with R simply because it comes more naturally to me and usually my intuition gets me to where i want to be more often than not. Programming in Python often feels like a fight...
Thanks for sharing this Luke! Yeah like youve come to realized I think the most limiting thing is your knowledge and application of the tool!
Most criticisms of R I read are blatantly wrong. People who throw shade seem to have last interacted with the language in 2012. I also agree that R is easier to learn. Finally, if you come from a statistics background, as opposed to comp sci, R may actually provide more job opportunities, as you can look for both Statistician as well as data analyst / scientist positions.
Nice! Very much agree with this, thanks for sharing this perspective on R!
I have learn Python a little bit and now i just start Google cert. with R. I think R is more easily in term of picking up the basic in data analysis. Actually I think both R and Python are good at data field.
Hey thanks for sharing this, awesome perspective to hear!
You R starting quite a battle with this one! Great video! DataNerds can use a lot of tools!
Thank you to my top subscriber! You are gonna crush this race this weekend!!
Python is such a great language to learn as you can apply it rather simply to a LOT of problems. I have a bit of an issue with the habit of learning a lot of different programming languages when I could just get better with one more flexible tool.
Very much agree with this!
In the Google DA Cert, about to start the R section of the course (almost to the finish line) Looking forward to learning!
This was another very helpful video. Thank you for posting.
In your journey to learn data analytics, and understanding all these programs, were you able to tackle all your education on a Mac? Or did you split the programs between a Mac and PC?
This is also a good project to add to your own experience as a data analyst.
Thanks for the video!
As a software engineer I find python barbaric. Statically typed, compiled languages just kick ass in the long run. It's ok for data analysis scripts but R is probably better for that specific job. Turns out being a jack of all trades, master of none language has served Python well. Overrated imo
Probably a little bit overrated!! ha I respect your opinion though, thanks for sharing this perspective Glenn!
So python is not mastering the AI world right now ???or data science? Or even bioinformatics?
I learned Java first and missed the strong typing and elegant autopromotion and polymorphism. But after many years of coding, typehints in python seems pretty sufficient for building powerful data analysis and ML pipelines. Of course if you want to do anything superfast, it's best to implement in c++, and interface with python or R.
languages are engineering tools; what determines the effectiveness of a language for a problem domain is usually the body of legacy code written for that domain and it’s reliability and efficacy, which is derived from the dedication of a language’s users, rather than the grand forward planning and wisdom of its designers
use any language long enough, learn enough of them, and you start to realize that we programmers have to be shrewd with our application of these different models of computation like statisticians and scientists are with their models of natural phenomena: recognizing that all are wrong, but some are occasionally useful
Thanks for sharing this!! Very interesting perspective!
Just think about it through the inequality lens: disadvantaged R users are partly supported by such google actions, no big deal, good news for R users, not a big problem for Python users, given the amount of available materials
I've learnt both R and Python as part of my degree - Starteed a job as an OT engineer, and anyone who used R is gone from the business - everything is M, Dax, Python, SQL. Even the machine learning machines (that used shiny apps in docker) are not being used anymore - its all being pushed to the cloud. Its a crap shoot as to what your future business will use. But learn Python as a sure thing, it can actually do a range of things beyond data analysis.
The cloud is for sure taking over. Thanks for sharing this perspective Matt!
I work with both Python and R. I love Python as a programming language, it reminds me of Perl in some ways. When it comes to statistical analysis, I find it very satisfying to use R. I highly recommend being multilingual and picking a language that you love and perfecting it than letting Google or job trends dictate that choice.
Yes, highly agree with the benefits of being multilingual. I def appreciate certain aspects of python and R by knowing the basics of both
Your videos are enlightening Luke. Nice work. 👌
Thanks for the kind words, I try to make them easy to follow!!
Thank you Luke for all the good stuff.
Glad you like it!
Really interesting having just discovered your videos, I'm an experienced Data Analyst in the Education sector (6 years and a further 4 in Emergency Services) and my main tools have been Excel and to a greater extent R (with a sprinkling of SQL). For the type of analysis I do, I've found R much more useful than Python. I have however, felt I need to learn Python due to many advertised Data Analyst roles asking for it, when thinking of the next step of my career. But as I don't use it everyday at the moment, it is hard to retain that information so I'm looking for ways to incorporate Python into some of my regular work. Food for thought... as I feel I've stagnated a bit and stayed safe with Excel and R.
Thanks for sharing this, and glad you found my channel! Both Excel and R (more specifically) can be such powerful tools as you've shown here. Thanks for sharing your perspective on Python and R!
@@LukeBarousse Thanks Luke, it's inspired me to get back to learning Python again, so I'm going to pick that up again this week at work. So thank you for inadvertently doing that 🙂👍. Subbed and I will be watching with interest from now on. Rob
@@GamingRobioto heck yeah! Glad to have another sub! Good luck with the python studies, Rob 🙌🏼
Great content, was looking for an answer to this!
Thanks for coming on over to my channel CK!! Glad I was able to help!!
Luke, you are the man, loved how you approached this without ego.
I rarely write comments but you got me pumped up. Without knowing it, you described my career path:
Excel ✓
Power Bi ✓
SQL ✓ (funny thing here, I thought I knew R but with your explanation I don't lol)
Python - Just started a few weeks ago and very pumped!
I will probably end with R but I feel I have a long way to go with Python.
Thanks for your content it's great!
Thanks Fernando! Good luck with the Python studies! 🙌🏼
The point is that Python might not be better than R in Google’s view but Python required jobs are more abundant so you would not waste valuable learning time on something you will never use
That information is quite good for me. I already work with excel VBA, power query and power Pivot. My role is to automatize projects and reports. I already developed a project using python as well. Unfortunately I can't share because it contains company's information. But I guess I am almost ready to transition.
Yeah I think your start with excel is foundational. Keep up with the learning new tools!
"when i understood r was barbaric" lmfao
Sir your advice is helping me as a entry level Data Analyst so i'm really Thankful to you with tons of Love 💓
Thankyou for the guidance. I was looking for this from months. Everyone out there know alot but you put it in the bestway.
Mastering Excel
SQL
visualization/programming skills. Its a path for beginners. God bless
6:44 wow really, only 8 Million people use python? I expected that number to be much higher. Great video btw!
Yeah I was surprised too! So few people!
Hi Luke, thank you for sharing this video. I believe I'm not the only DA noob that got stuck in the weeds of R vs Python. You did a great job with explaining that there is so much to be learned before this question makes any sense for beginners. Could you please recommend any Excel learning resources? Or do you remain firmly with GDAPC being the one-stop-shop for beginners?
Hey Marko, I think the GDAPC is a good introduction... but def not the final resource for mastering excel. I personally used this book (along with a course I took in college) to better master Excel.
amzn.to/2Xj14qe
If you can do a pivot table, there's nothing more to learn in Excel. I'm not sure I will ever put "Excel" in my list of skills on CV.
Thanks for sharing this!
Honestly I just don't wanna learn a new programming tools when I already got one that I can use reliably. I don't get why people think Python is better. It's just a matter of saving time and effort from my side.
Thank you so much for suggesting datacamp i have tried learning from different channels and coursera too but datacamp is the best🙌
Thanks for sharing this Tejaswi!!
If i want to work as a machine learning engineer or data scientist one day which entry level job role should i start applying to get my foot in the door in the industry?? I dont mind starting from the bottom and working my way up.
What's your opinion about the future of data analysts with the arrive of AI and automatization?
Thanks and nice content 😊
I'm not concerned with automation at this moment in impacting data analytics. The BIGGER problem we are facing RN in this community is establishing data pipelines for CLEAN data. I feel companies are going to be investing heavily in this and this is the future problem data analysts need to be thinking about.
@@LukeBarousse thanks man
It would be great if you deepened this topic in a video
@@humanoanonimo1558 This is a great idea!!!
Insightful. .thank you
I think any work related to analysis will be difficult to be replaced by machines for a long time because the hardest part in analyzing this kind of work is probably because it takes into account human nature and the psychology of customers. This is a feeling that is difficult to reflect in the data depends on the empirical judgment of analysts.
Thanks for the video it's really helpful for beginners like me but I really love if you make a tutorial on web scraping in python
Hey Luke,
I’ve just come across your channel today and I can not be more grateful about your content. Your easy-to-follow guides to data analytics and how to entry these kind of jobs are excellent!
I have a question though, I’m finishing a computer science degree right now, where I’ve learnt quite a bit of everything (R, Python, C, Java, sql, etc) but nothing in full detail (apart from Python which I learnt myself at job). What would you recommend me going for after finishing the degree and the Google Certificate? Mastering Excel/SQL?
Thank you in advance and have a nice 2022!!
No problem at all! Glad you are enjoying the content!! And yeah I would recommend Excel/SQL (that is if you are interested in becoming a data analyst). I made a new video on this recently, not sure if you saw it yet: th-cam.com/video/aqRxZSrJLEc/w-d-xo.html
@@LukeBarousse Yeah! In fact that's the one which brought me to you :)
Thank you again for the advice and keep up the amazing content!!!
@@lordespax Aww thanks my dude! Sorry about the same vid recommendation 😂🤦🏼♂
Good luck with your studies!
I am a CS student. I don't like Excel and don't wanna learn it. Tho, I am good in python as well as in R and SQL. Is that enough?
Really depends on what the job is requiring
I know Python and SQL pretty well. Should I learn Excel, R, (Tableau or Power Bi) now? Or maybe theory like statistics and further knowledge in pandas, numpy and matplotlib?
Thanks for all the content!!! Much appreciated and highly enjoyable :) I have a question though. Being in mid-career, wanting to add some skills I'm currently taking the Google Analytics cert, however I wanted to add Phyton as well. Being a newbie, and needing to do the grunt work is the Coursera Crash course or Udemy's Phyton BootCamp recommended for this or any other course to consider instead?
I'm not too sure on Udemy, as I haven't looked into their offerings as much as Coursera's
@@LukeBarousse ok thanks. I'll stick to Coursera and ure vids then ;)
Hi Luke, in the Capstone project phase of Google Data Analytics.
And I seem to be able to use merely just R to cover the entire phase from Ask, Prepare, Process, Analyze, Share, to Act.
I wonder, when is it that I will be required to use Excel/SQL by necessity to analyze data?
In the course? I'm not too sure but I feel it covers the basics of Excel and SQL during the course. As demonstrated in this video Excel and SQL are highly valuable skills for data analysis and you'll be requested to use these skills as a data analysts. Although you may not use Excel and SQL in your capstone, that doens't mean a data analyst doesn't use it in their real job
I think R is a more user friendly experience than python and combined with Julia for more powerful computing down the line.
Thanks for sharing this J J!
@@LukeBarousse sure thing .. Keep up with great content ! Python will have to be on my learning path but I am combining it with Julia after I get a good grasp on starting and finishing project with R
Paused at the 1:12 mark: "Do data analysts really need to learn Python?" No, they can get by just fine with the many other tools available. The exact same answer could be given about R, or pretty much any other tool. Ironically the software that is probably the most irreplicable is fricking excel.
Job posting of data analyst in your area inferred that Python is a most demand skill than R? Could it be the case that Python just happens to be most popular and not most useful? The fact that more companies ask for it does not mean you should learn it as a data analyst. R is so much better at data visualization and data wrangling than Python is.
Umm, I showed that python and R are NOT the most important and that Excel and SQL are! But to your point, yes Python may be overly hyped, but it doesn't take away that it's listed more in job descriptions than R. With companies using more AI/ML to filter out candidates for skills based on what they list on their resume, I think others need to know keywords to use to ensure they get noticed for a job!
@@LukeBarousse so you mean the title should be "what tools to learn to increase the chances of landing a job as a data analyst". Either way, I should have started with props. Great video and initiative.
@@jdlopez131 Agree that that's a better title... but unfortunately with the TH-cam algorithm I need titles like these to reach more people. 😒 Nonetheless thanks for the kind words Jorge and I appreciate your perspective!!
***I was just scrolling down and reading the comments ans I was amazed that you actually replied to all of em...***
I use python for data science although my journey started with R in data science. But the only reason I don't use R because of..........idk
Thanks for noticing this! And I had a similiar journey. Can’t really tell you why I left R? 🤷🏼♂️
The principal idea is not to program with one or other, most of the time u will just search in internet a solution for a problem that appear with your problem, and replicate it. So if u know read codes in R and python and understand it, you gonna have more ways to take an ideia to solve your problem. So, i think u can go to any language R/python but at least need to understand both.
Thanks for sharing this perspective about R and python!
I realize this vid is taking about Data Analysts. But for Data Scientists, you will want to know both Python and R. Just like Google, my master's program in DS started out in R and then switched to Python. In the job market, your competition will be people who are proficient in both.
Excel? Well, when your dataset consists of millions of untidy records, Excel is like a knife at a gunfight.
SQL? Of course, that goes without saying. As a Data Scientist, you will need Python, R and SQL.
Thanks for sharing this perspective of a data scientist, I agree with all of your points here!
An perhaps intangible factor related to R is that, because it was built for statistics by statisticians and is used for academic research in traditional conservative sectors such as health||biotech|pharma|consulting, it enjoys, right or wrong, a degree of respectability that more common. mainstream languages do not. It also signals, right or wrong, that one has a basic knowledge and appreciation for stats.
I once wrote a program in R and it took 40 minutes to process 200+ CSV files and this was not acceptable. I re-wrote the program in python and it completed the task in 3 minutes. I then put R aside and specialized in python. Be good in one language R/python but really good. it is better to be good at one language really well than being a master of none :) . R script is a little simplier than python but once you get familiar, python is fun and powerful
Thanks for sharing your experience with both these tools! Always interesting to hear different perspectives on this topic!