R vs Python | Which is Better for Data Analysis?

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  • Опубликовано: 23 дек 2024

Комментарии • 409

  • @ALZulas
    @ALZulas 3 года назад +514

    I used to give a lecture on when to use R and when to use Python. I gave it for many years, but every year both languages would grow closer and closer together. I eventually stopped giving the lecture, because they're so much the same that it doesn't benefit students to talk about it anymore. The only thing that's different anymore, in my opinion, is it depends on how your brain thinks about problems. If you think about and solve problems from a programmer mind set, Python will be easier for you brain to wrap around. If you come from SAS, MPlus, or SPSS, R might be easier for your brain to wrap around. Much like picking skis or snowboards, try them both and go with the one that feels right for the way you work.

    • @jhernandez9617
      @jhernandez9617 3 года назад +3

      No. F*ck R. It needs to die and become a bad memory for the human species.

    • @BboyKeny
      @BboyKeny 3 года назад +2

      @@jhernandez9617 Why?

    • @myworldAI
      @myworldAI 3 года назад

      @@jhernandez9617 haha ,don't F**K R, R👍👍👍👍💖💖❤

    • @dir2310
      @dir2310 3 года назад +21

      this comment save my 11 mins, thanks!

    • @kevinboone5015
      @kevinboone5015 3 года назад +2

      I know Im asking randomly but does anyone know a trick to get back into an instagram account..?
      I somehow lost my account password. I appreciate any tips you can give me.

  • @bernardogrivon9139
    @bernardogrivon9139 3 года назад +127

    As a noob with only excel background, I got into R much more easily. One huge advantage of R imo is RStudio. Such a great tool to work with. Also in R the documentation is helpful, even the error messages are useful. I'm starting with python, but for me it's not as sticky and intuitive. I find Spyder as an IDE ok, but imo it's way behind RStudio.

    • @jerrisg9457
      @jerrisg9457 3 года назад +2

      Agreed on RStudio being a huge advantage.

    • @vivekjoshi3769
      @vivekjoshi3769 3 года назад

      Agree on RStudio. it is really helpful!

    • @hak41711
      @hak41711 3 года назад +2

      Try using vs code for python

    • @CuteBoyLesh
      @CuteBoyLesh 2 года назад +1

      Jupyter Notebook or Atom are great

    • @CKinUSAmerica
      @CKinUSAmerica 2 года назад

      I also pretty much only with excel background. But I picked up python more easily… it’s really hard to understand R language..though I have to learn it anyways

  • @bendirval3612
    @bendirval3612 2 года назад +64

    Python is unquestionably more straightforward as a language in general. However, it's fundamentally a general-purpose scalar language, not a vector-data language like R or a matrix language like matlab. That fact makes the type of data manipulation and analysis that is meat and potatoes in R less convenient in Python. "Hello world" is easier in Python, but real data analysis is easier in R. I use Python for general programming, but it's just not worth the trouble to force Python to pretend to be R for data analysis, econometrics, or statistics. Python is way, way behind in all forms of data analysis. For example, Python is only now considering basic ideas like "missing" values being different from "not a number" values, which the creators of R thought of and planned for from day 1. If I had to pick one language as "better," I might choose Python, but it's not better for data analysis, which is what's being discussed here.

    • @borisn.1346
      @borisn.1346 2 года назад

      Well said!

    • @alextjflorida
      @alextjflorida Год назад

      agree, I prefer R in terms of statistical analyses.

  • @davidreynolds3895
    @davidreynolds3895 3 года назад +32

    The syntax example for R is way more complicated than it needs to be. You technically don’t even need to load any packages to read in a CSV and calculate the mean.

    • @simonparker4992
      @simonparker4992 2 года назад +13

      x

    • @dominicj7977
      @dominicj7977 8 месяцев назад +1

      As a non-programmer who use programming for work, I find R's syntax to be more intuitive. Programmers ma think in a different way.

  • @keith819
    @keith819 3 года назад +25

    For a new programer, I'd say learn Python.
    It's much much easier to get a job with Python, your in the general software engineer camp vs being locked to data scientist roles.

  • @jamesstonehouse3448
    @jamesstonehouse3448 3 года назад +18

    I came to R from using C, visual engineering environment (an instrument control language used in metrology), SAS & SQL. Nowadays I make my living with R, automating reporting, text mining, and developing data manipulation tools for an intelligence team. It has to be said that in my industry, I haven't yet come acress a Python user. It might just be that the big players in town are all either R or SAS background.

  • @tanvird3
    @tanvird3 3 года назад +41

    5:56 you can use colMeans(nba[sapply(nba, is.numeric)]) for calculating means of the numeric columns, you don't even have to import any libraries. I understand the python way is still cleaner, however, there are tons of situations where the other way around is true.
    7:09 library(tidyverse) and you get every functionality that python pandas can offer, you don't have to remember a lot of things for doing a simple task.

    • @rashawnhoward564
      @rashawnhoward564 3 года назад +15

      Even easier summary(data) will give mean, median, Q1, Q2, min, and max of data no loading packages and its cleaner than python.

    • @explicitlynotboundby
      @explicitlynotboundby 3 года назад +2

      @@rashawnhoward564 Exactly. Alex is bullshitting.

    • @BzRist
      @BzRist 2 года назад +1

      In R, you could also use library(tidytable) for the same functionality with great memory efficiency.

    • @frankaragona1463
      @frankaragona1463 2 года назад +1

      Was just going to say this. That was a pretty poor example.. There are so many more situations where R is cleaner and easier to use for wrangling data. I feel that pandas is disappointing whereas dplyr/tidyverse in general are better tools for data science

  • @jerchiury
    @jerchiury 3 года назад +16

    I don't want to worry too much about data types when doing my analysis. The fact that base R supports operations of matrices and data frames makes it much easier to use. R knows when you are subtracting two series (column/vector whichever) to subtract it term by term for example, it's pretty messy with python when you get lists, series, arrays and such going about all with different methods for that one exact operation.

  • @solom465
    @solom465 3 года назад +112

    Personally I prefer R when doing hardcore data analysis. Dplyr, ggplot2. and the rest of the tidyverse enable you to do more with dramatically less code compared to Python. For anything outside of hardcore Data analysis I use Python.

    • @AlexTheAnalyst
      @AlexTheAnalyst  3 года назад +9

      I can definitely feel that

    • @winnumber101
      @winnumber101 3 года назад +1

      I’m with this

    • @squirrelpatrick3670
      @squirrelpatrick3670 3 года назад +1

      I really prefer pandas to dplyr, and R was my first language of the two. I did spend a while getting fluent with it.

    • @dominicj7977
      @dominicj7977 3 года назад +3

      ​@@squirrelpatrick3670 R's data table is one of the fastest in the whole programming language universe.
      I rarely use dplyr or pandas after I started using data table in R

    • @hammadsheikh6032
      @hammadsheikh6032 3 года назад +1

      Same here! R is king for hardcore analysis, but go beyond that, and Python leaves it in the dust. But R is my first love.

  • @lauragonzalez5584
    @lauragonzalez5584 3 года назад +41

    I've waited long for this video! Right now I'm learning Python and in my company, they use both depending on if we are using classical statistical models or ML. However, I'm also an economist who would like to get more involved in academia and I think R is more used there than Python. Both are excellent choices tbh

    • @adrielbezerra7887
      @adrielbezerra7887 2 года назад

      @Harry S It depends on where you are and the country laws. Here in Brazil there's no law which regulates the data analyst profession in private market (aka companies). But in public sector is required to have an university degree as statistician, IT, software engineer, etc.

    • @skcocemag
      @skcocemag 2 года назад +2

      Controversial take: I would suggest python for economists. Reason being, if you're an economist, you are likely to use (or a coauthor is likely to use) Stata. The newer versions of Stata talk to Python really really well. I can run Stata from within Jupyter or Spyder or run Python from within Stata VERY easily, and that includes, for example, running a Python command from Stata USING my live Stata dataset! In other words, you can open stata, play with some data, then run a python command on that data, then run a stata command on that data, etc.
      Will Python be able to do something newer, for example techniques that have come out in the wake of Goodman-Bacon 2018? Probably not. But just use the instructions to turn your section of your .do file into python code and run what you need to there, then switch back. Easy peasy.

    • @hivan04
      @hivan04 10 месяцев назад

      Thank you for this comment, I'm currently a second year Econ student and this helped a lot!

  • @davidyolchuyev2905
    @davidyolchuyev2905 3 года назад +11

    for finding the mean of the column in R, you use mean() function. I dont know why you have shown pipes in the R section of syntax example

    • @olivierspanhove8808
      @olivierspanhove8808 3 года назад +2

      I know right, it's even one of the functions in the base package !

  • @mohamedjelassi9672
    @mohamedjelassi9672 3 года назад +10

    When we speak about analysis, we speak about mathematics and more precisely statistics... in my point of view, R has more mathematical libraries than python ... and please keep python for web development and other stuffs

  • @simonparker4992
    @simonparker4992 2 года назад +57

    Two minutes in, you're pedalling the standard nonsense that R is a statistical package. I've been using R for twelve years and pretty much never for statistics. Text processing, data cleaning, report writing (markdown) and GIS, GIS, GIS. R is really good for mapping and geospatial data processing (not just spatial statistics).

    • @Hugo-fi9xr
      @Hugo-fi9xr 2 года назад +10

      The strenght of R is the statistics you can't deny that. Sure you can do other things with this language but it strong point is making plots, modifying data frames and statistical tests. Sorry for my english btw

    • @alienboogieman
      @alienboogieman 2 года назад

      2 mins in and you already b**ching. Geez that flacid ego needs be toned down son.

    • @simonparker4992
      @simonparker4992 Год назад +8

      @@alienboogieman I was being polite. It's a crap video at best. It's disingenuous and dishonest at worst.

    • @alienboogieman
      @alienboogieman Год назад

      @@simonparker4992 is that what your wife said to you before she left your ass? If so, good because you assume you know best when you do not.

    • @عبدالمجيدالعتيبي-ز6ع
      @عبدالمجيدالعتيبي-ز6ع Год назад

      Is there a similarities between csharp and R language, because I'm using c# now and i have good experience with it

  • @jaqo92
    @jaqo92 3 года назад +14

    I learn both. My conclusion is python is better but i love Rmarkdown and ggplot more than jupyter and matplotlib + seaborn.

  • @jacobusstrydom7017
    @jacobusstrydom7017 3 года назад +37

    Very good, I mostly use R. But when Combining R with python and sql, then you are unstoppable data programing machine. So learn both, it's a lot of fun.

    • @DailyMental
      @DailyMental 2 года назад

      Hey sir, im currently learning from scratch, would you recommend me to learn R first and then move to python or what would be your approach?

    • @jacobusstrydom7017
      @jacobusstrydom7017 2 года назад +5

      @@DailyMental wow good question. I learned SQL then python and R.
      My opinion is that R requires less code to do something than python. Also the amazing R Tidyverse package makes it so mush easier to code and to work with data. Also R mostly just works, where with python you do get a couple more issues with package versions.
      But saying that, SQL is also a great place to start because it's easy to read and understand the code.
      Keep in mind that allot of companies store data in a databases so it's always a bonus if you can use SQL to extract data from the database and then analyze it in R or python.
      This is just my opinion. Good luck

    • @DailyMental
      @DailyMental 2 года назад +1

      @@jacobusstrydom7017 Thank you for the advice! I was thinking this as well, SQL is my first step and then R since im from a business background and its probably better to have a solid foundation before learning more complex syntax.

  • @arcaneknight9799
    @arcaneknight9799 3 года назад +96

    Power BI vs. Tableau

    • @deniskk2
      @deniskk2 3 года назад +6

      power bi..... no mistake there. download it & see 30 minutes demo

    • @arcaneknight9799
      @arcaneknight9799 3 года назад +4

      @@deniskk2 I've used Power BI and love it. I don't have much experience with Tableau, so I'm wondering his justification for Tableau.

    • @AlexTheAnalyst
      @AlexTheAnalyst  3 года назад +28

      Coming soon!

    • @diazjubairy1729
      @diazjubairy1729 3 года назад +7

      Tableu is expensive but have great feature and ux, power bi is cheaper even free but not so great ux. Both of the app will do your data viz job eventually

    • @osito9810
      @osito9810 3 года назад +3

      guysss, Google data studio is better than Power Bi y Tableau

  • @trancehvn
    @trancehvn 3 года назад +2

    I feel this video is a little biased at 5:55, as I don't think anybody will write that code to just get the mean

  • @chancellorpalpatine3352
    @chancellorpalpatine3352 3 года назад +10

    I think R is better, as pandas is much slower and less easy to use than dplyr. Data prep takes up most of my time, so this is huge. Both R and python are relatively equivalent to me for machine learning. Alot of these ml packages are just R and Python wrappers to c code. Maybe if you work for a fang and do alot of pure deep learning, python may be better, but I think that situation is rather rare.

  • @datamics
    @datamics 3 года назад +8

    It truly depends: once on personal preference, and also on what your work, that is your company, requires you to use. I prefer Python, and I think Python will grow to offer the same amount of features (if not more) as R in the future.

  • @rashawnhoward564
    @rashawnhoward564 3 года назад +4

    You definitely cherry picked to get mean of column you don't need to load packages just the base summary function will give that. summary(data) will give you the mean, median, Q1, Q3, min and max of every numeric column, not to mention the counts of qualitative columns.

  • @Vivian-ve1qt
    @Vivian-ve1qt 3 года назад +4

    When I subscribed to this channel two weeks ago I did it because I wanted to be ready for my data analyst interview. I passed it very well and I think this channel helped at least when it came to learning more about the job and the differences between a data analyst and a data scientist. I will start on the first day of March and I am looking forward to it. I am studying for a master in Big Data at the same time and I am learning R there, whereas I need to learn Python for work. R doesn't look difficult to me but Python kinda looks more familiar for me and those with a background in other general purpose programming languages. I agree about the huge amount of libraries in R and I think that it is really great for visualization. However, since Python is becoming the most popular programming language I would already prefer it for that reason alone not counting anything else.

  • @aldorodriguez7310
    @aldorodriguez7310 Год назад +7

    It would be nice to have a video with examples or real world scenarios for both cases.

  • @kirillshmidt3776
    @kirillshmidt3776 2 года назад +4

    filtering with pandas
    df[df['column'] == x]
    vs R data.table
    df[column == x, ]
    What is easier to read? Become even worse in pandas then you have more complex condition.
    Not to mention multi index in pandas. It is a hell.
    And direct comparison with reading of csv in r that you can also do in 2 lines:
    x

  • @nasser.h9473
    @nasser.h9473 3 года назад +10

    I don’t think it’s a big deal, it’s a preferential thing! I’m currently learning how to use Python

  • @prishitachoudhary8920
    @prishitachoudhary8920 3 года назад +2

    Thank you Alex for this video!

  • @adrielbezerra7887
    @adrielbezerra7887 3 года назад +11

    Honestly, I like both. Since I came from SPSS and statistics background, R suits me better. But when I need to analyze missing values or do some graphics, Python helps me a lot more.

    • @ankicanozinic6551
      @ankicanozinic6551 2 года назад +1

      What would you recommend to a beginner in statistics - SPSS or R?

    • @adrielbezerra7887
      @adrielbezerra7887 2 года назад +2

      @@ankicanozinic6551 If you never touched a database or programming before, SPSS may be easier to learn once it resembles a little bit the Excel and alikes. Also, you can click the buttons SPSS offers and the software gives you the programming script that your clicks generate. Disadvantage: SPSS requires a paid license. But it has a trial version to test.
      If you're commited (and have enough time to study) to learn programming basics alongside with statistics, R is the way to go.
      The answer is: it depends. I always tell my students to go step by step. Well, hopefully it will be useful to you.

    • @ankicanozinic6551
      @ankicanozinic6551 2 года назад +1

      @@adrielbezerra7887 thank you for a thorough explanaiton

    • @tufazzulmiah6299
      @tufazzulmiah6299 9 месяцев назад

      I am a statistics background student.If Learn MS excel, R and power BI for data analysts, it is enough for me in smooth data analysis ?

  • @romanvasiura6705
    @romanvasiura6705 2 года назад +1

    Thank you!
    I'll try both.
    Approximately in a month I'll have a course in Coursera about R (from Google Data Analyst Certification),
    but after that I'm interested to try Python as well.

  • @souhaibsebbane5623
    @souhaibsebbane5623 2 года назад +2

    Stopped watching at 5:55 because either Alex was biased or he has no idea whatsoever about R, since he did not use the mean( ) function which is even a base R function and you don't need to install and load any package to use it.

  • @borisn.1346
    @borisn.1346 2 года назад +1

    Love your overall points Alex, but saying that R can't be integrated in web apps is plane wrong!

  • @aalb1970
    @aalb1970 10 месяцев назад

    I mostly do data analysis on survey data and in my experience R is more robust in this regard. For instance, there are several packages that will create survey weights for you, but I have yet to find one Python package that actuially works.
    I do agree that Python syntax is somewhat easier to pick up, but once you understand vectorized operations in R it becomes easier to use.

  • @CunningCaracal
    @CunningCaracal 3 года назад +24

    From my understanding if you're familiar with SAS, R would probably be easier to pick up vs Python. I personally started with C#/C++ so python was easier for me to pick up. Also perfect troll post on LinkedIn, just say something controversial and walk away lol 👍.

  • @arielleung3917
    @arielleung3917 3 года назад +5

    R and Python require totally different mindsets. Picking the better one of them is like asking "which is a better career, statistician or engineer?". With my mathematical background I find R code much more straightforward, and when I started to use Python, it's not like any single piece of code is unreadable but the entire workflow is unfamiliar: how tasks are broken down, why makes a copy here, and so on. It also took me quite some time to be convinced that Python does not have a library for the Spatio-Temporal Autoregression model (for a few hours I thought I just hadn't searched the right way) since R offers abundent solutions for spatio-temporal data. Eventually I realized that modelling is never at the top of engineers' priority list, and mathematicians/statisticians can focus on the intellectual work only because engineers have got their hands dirty. Also, Python makes it easier to collaborate with other platforms. If I were to communicate with laymen rather than other professionals in my company, deploying a dashboard or web app would be the best explanation. Again, it didn't occur to me because this hadn't been my top priority, so I preferred R. Now the job has changed and I'm using Python more often.

    • @LHommeEnVert
      @LHommeEnVert 11 месяцев назад

      If there are no librairie for spacio temporal autoregression you can build it from scratch with python, as object oriented programming languages which is not possible in R

    • @ikari0133
      @ikari0133 3 месяца назад

      @@LHommeEnVertthen how do you think they built the library in the first place??

  • @jacqmarthy536
    @jacqmarthy536 3 года назад +4

    The youtube algorithm brought me here lol. I think an example of data analysis using popular libraries on both for comparison is good. Like the processing time, the amount of codes written etc. For me python is easier since in colleague we used cpp and fortran for learning basics of algorithm and numerical methods. The one time i had to use spss for statistics assignments i got really confused.

  • @down_with_data
    @down_with_data 3 года назад +4

    By the way R can be embedded in web application.

  • @BabyBugBug
    @BabyBugBug 3 года назад +4

    It helps to know many programming languages - that much I have learned so far

    • @BboyKeny
      @BboyKeny 3 года назад

      True, for me it broadens your way of thinking about programming in general.
      Since every language approaches the subject in a unique way with a unique motivation.
      It makes you very appreciative of the strengths and weaknesses of every language.

  • @Dylan-zm3ht
    @Dylan-zm3ht 3 года назад +18

    I prefer the R syntax. I find it easier to remember “weird” syntax.

  • @bgpolitan
    @bgpolitan 2 года назад +5

    I am an economist trying to dedicate to data analysis and I still didn't understand the pros and cons of both, so this video is exactly what I needed. Thank you! 😄

  • @bo3thman917
    @bo3thman917 3 года назад +1

    my whole knowledge in programming is with c++, I even made my calculations for my M.Sc in Statistics and Operations research in c++ . Now I’m not sure what to begin with Python or R. Most my work are hover around numerical analysis.

  • @ethaniel7551
    @ethaniel7551 3 года назад +22

    I guess you could say that the messages Alex received in regard to his “controversial” post included some R-Rated content ;)

  • @sergiotorres513
    @sergiotorres513 3 года назад +16

    Great video. But I think you could make a syntax example with R much easier. If you want to know the mean of a variable or of data you only type mean(data) or mean(data$variable), of course, depends on this variable or data is numeric or not. Thanks for your video. Regards.

    • @AlokPratapSingh4001
      @AlokPratapSingh4001 3 года назад +1

      Also, mean for each column, just use the code
      sapply(dataframe, mean)

    • @dominicj7977
      @dominicj7977 3 года назад

      using apply functions or colmeans( )

    • @hak41711
      @hak41711 3 года назад

      You could simply use the describe method for that using pandas

  • @QuantumImperfections
    @QuantumImperfections 3 года назад +28

    I've personally enjoyed my SQL, Excel, R, PowerBI group I've got set-up. The only thing I really planned for was learning PowerBI but the rest came about oddly naturally. Great video by the way!

    • @AlexTheAnalyst
      @AlexTheAnalyst  3 года назад +4

      That's a good toolbelt right there!

    • @praveen26699
      @praveen26699 2 года назад

      I too learned Power bi...Is it easy to learn R?

    • @QuantumImperfections
      @QuantumImperfections 2 года назад +1

      @@praveen26699 I found it particularly easy. I'd picked up most on my own after reading: "Learn R" by Aphalo. I'd taken some DataCamp courses and other paid courses by ppl like Matt Dancho that provided spot-on business applications for it. I also read "Advanced R" by Wichkham and with all of that R is my main powertool in the tool chest.
      R is a lot like Excel and SQL, Python is a lot more like other programming languages. All of the above are interchangeable and as long as you can learn how to provide business value you are golden.

  • @richardaversa7128
    @richardaversa7128 Год назад

    Excellent summary, great balance of conciseness and examples.
    "R is harder to learn, but has more features"... specifically for analytics, right? My understanding is Python has far more features in general. Never heard of someone building a mobile app in R.

  • @gj3933
    @gj3933 3 года назад +2

    There must be a reason behind the growing number of R packages. My clients won't care about if I produce results in R or Python. If they ask me to build an app, then I'll reconsider.

  • @RCasey100
    @RCasey100 3 года назад

    I know absolutely nothing about Python, but your example at ~6:30 is a major giveaway that you are not experienced enough with R programming to form a reliable comparison - the example could be done in base R with two lines of simple code. I've never seen such an overcomplicated way to find the mean as you described..

  • @annoyingprecision2487
    @annoyingprecision2487 3 года назад

    Liked and subscribed! Thank you for the valuable input.

  • @hibou647
    @hibou647 3 года назад +2

    In my opinion the biggest advantages of R are its IDE Rstudio and the capacity to execute only the mouse selected portion of code (no, notebooks are not as convenient). Web deployment is possible through Shiny but it seems much more of a hassle than on Python.

    • @MrMafiale
      @MrMafiale 2 года назад

      Try rmarkdown, sweave or knitr for notebook IDE. They are even better than the python notebooks I worked with so far

  • @RobertR1611
    @RobertR1611 3 года назад +2

    Thanks, Alex. Great video. The right tool for the right job.

  • @planetary-rendez-vous
    @planetary-rendez-vous 2 года назад

    Just calling attention to librarian::shelf(tidyverse)
    You don't need to write 10 lines of library(dplyr), you can write all your package name in a single line code and it will automatically install if needed and load it.

  • @fernando_dominguez
    @fernando_dominguez 2 года назад

    Loved it! Thank you very much for your content, just started following you.
    My advice is just express your opinion like you did, makes content far more unique.
    Cheers!

  • @behrad9712
    @behrad9712 2 года назад +1

    thank you!🙏

  • @joshuaconstantine269
    @joshuaconstantine269 2 года назад

    So which tool y'all think would be better for conducting economic and financial analyses?

  • @anthonysoltero88
    @anthonysoltero88 3 года назад +28

    Use the language your team uses.
    The guess work can be taken out based on the company you work for or the company you want to work for in the future.
    If they use R, use R. If they use Python, use Python. If it’s only up to you, flip a coin.

    • @ArnavRoyRA
      @ArnavRoyRA 3 года назад +1

      LoL Flip a Coin....... that's what I'm gonna do as a Student to start Learning XD

    • @jaqo92
      @jaqo92 3 года назад +1

      Pandas > tidyverse

    • @dominicj7977
      @dominicj7977 3 года назад

      @@jaqo92 R data table > pandas

  • @hernanmorales6681
    @hernanmorales6681 3 года назад +1

    Amazing video!! Thanks!!

  • @LucasPeitton
    @LucasPeitton Год назад

    It's insane how many times you had to ask ahead for forgiveness to avoid potentially offending anyone. We are all different and haver different opinions - get over it people! Very cool video mate. As a statistician I'm very in love with R, but I'm trying to learn Python as I am very aware of it's coverage and power. Cheers

  • @AndyQuinteroM
    @AndyQuinteroM 3 года назад +3

    I like functional programming. I love R for data science. Anything else I’ll just write out some C or JS

  • @uqwang
    @uqwang 3 года назад +5

    They’re just tools to get my work done. I use both on daily basis.

  • @tritiyo_noyon
    @tritiyo_noyon 3 года назад +2

    Do we have something like r studio for python?

  • @Salmanbro96
    @Salmanbro96 3 года назад +15

    SQL VS NOSQL

  • @biswajitdas2999
    @biswajitdas2999 3 года назад

    Why IBM don't give data science certificate with r?

  • @rishimetawala
    @rishimetawala 2 года назад +2

    i actually gave up on R as I moved to a more strategic role and away from hardcore data analysis, i found it harder and harder just to recollect syntax across different libraries. Plus I see Industry is tilting more and more towards Python and learning Python is kind of "future proofing" your time spent on it.

  • @ahmedelsheshtawey438
    @ahmedelsheshtawey438 3 года назад +5

    Learn sql for data analysis from your playlist it’s enough or need to continue with another course

    • @AlexTheAnalyst
      @AlexTheAnalyst  3 года назад +1

      For sure! I think it's a good place to start :D

  • @TheFootballPlaya
    @TheFootballPlaya 3 года назад +1

    question: if you had to choose one background to have to work as a data analyst, business or statistics, which one would you choose and why?

  • @kunqiwang9736
    @kunqiwang9736 Год назад

    R code can be difinitely maintained by markdown for example.

  • @vinn0101
    @vinn0101 3 года назад

    If all you want to do is read a CSV file and see the mean, you could use RStudio and not program anything in either R or Python. Use the right tool for the right job.

  • @andrijamilojevic1891
    @andrijamilojevic1891 8 месяцев назад

    Thank you Alex!

  • @pieterrossouw8596
    @pieterrossouw8596 3 года назад +1

    Underrated skill that's complementary to these is Excel PowerQuery... Poor man's PowerBI and the only thing that makes Microsoft's Office suite irreplaceable by even the best of clones.

  • @Ma-Attia
    @Ma-Attia 2 года назад +1

    U R amazing man ❤️👏

  • @danyos777
    @danyos777 2 года назад +1

    I would like to see a second part video comparison focused on comparing R and Python languages from a business standpoint rather than their more general-purpose, programming capabilities for building applications, and heavy used of sophisticated statistics that do not apply to the average business world. For instance, many of us in business are hoping to learn which language is better for business analysis which, after all, is the trend in using either of these languages.
    What we learn from the video is that R is being highlighted as useful in purely statistical analysis, while the comparison with Python does not provide any insights into Python's capabilities for statistical analysis. R is being highlighted as great for statistical analysis, however, advanced statistics is mostly used by the scientific and academic community mostly as well as sophisticated business environments whereby most of these advanced statistics are not needed in the general business world.
    I would like to see the view from a business analyst/business intelligence professional who has truly used both R and Python for exactly the same purpose, using these languages for business analysis. It would be great to move away from the general-purpose and application development and get more into the business uses for each language and on what statistical and data analysis truly serves the vast majority of business users, business intelligence and data analysts analyzing business related data.
    Looking forward to this second video. Thanks Alex!

    • @kirillshmidt3776
      @kirillshmidt3776 2 года назад

      For business analyst/business intelligence both languages are equal and more about preference rather than advantages. Usually there are no issue with performance, you do not need sophisticated models and packages. You can build up your own functions and make it closer to you field in both languages. Maybe there are better visualisation with ggplot in R (it is more versatile). But if you want to build proper self-service BI then better to go with classical BI tools like Tableau/Power BI and etc. R and Python are for search of deep insides made by hardcore analyst, and BI tools for managers.
      I am actually bilingual in R and Python and do both ways in my work.

  • @BboyKeny
    @BboyKeny 3 года назад

    "R can't be embedded in web-applications"
    I imagine this should be possible with Web Assembly right?

  • @paultoronto42
    @paultoronto42 3 года назад +1

    I think Python is better too, but I do like Hadley Wickham's TidyVerse for R.

  • @Chris_87BC
    @Chris_87BC Год назад

    I learned R and Python and I can say R is much easier to learn but Python is way more robust. I replaced a VBA code that creates MS Excel workbooks from a template, and it took like 3 seconds to complete. Using R took like 45 seconds.. After I saw the benefits and speed of Python, I put R aside and focus on Python.

  • @linnaco9361
    @linnaco9361 3 года назад

    I use both as a digital analyst student. R for data cleaning, structure, and manipulation. Python for ML

  • @JOHNSMITH-ve3rq
    @JOHNSMITH-ve3rq 2 года назад

    no web applications? What about shiny etc/??

  • @Harry-mf6rq
    @Harry-mf6rq 2 года назад +4

    I think the best thing about R is RMarkdown. Being able to hit one button, run my statistical analysis, and output a word document with all the right numbers and figures in it is amazing for reproducible reporting.
    I'm switching to Python soon. Do you have any recommendations for a similar functionality?

  • @vishnuvrv
    @vishnuvrv 3 года назад +3

    Google chose Python for its ML/AI coding. So if you are looking at ML or AI, python is the way to go.

  • @andrewnguyen3312
    @andrewnguyen3312 10 месяцев назад

    I use R, but want to learn python eventually! Thx for this video

  • @mohammedbouchcoucha890
    @mohammedbouchcoucha890 3 года назад +5

    Miss you Alex!! i worked with both and i've one little thing to say, in R you can write mean(nba) or you can use summary(nba)

    • @AlexTheAnalyst
      @AlexTheAnalyst  3 года назад

      Thanks Mohammed! Glad to be back! Is that with R Tidyverse?

    • @mohammedbouchcoucha890
      @mohammedbouchcoucha890 3 года назад +1

      @@AlexTheAnalyst No! it is predefined function.

  • @drmack911
    @drmack911 2 года назад

    The genesis of R actually dates back to circa 1975 at Bell Labs where is was named S. Python had its origin around 1989.

    • @-Jakob-
      @-Jakob- 6 месяцев назад

      and Python was insipred by ABC which was inspired by SETL

  • @nkristianschmidt
    @nkristianschmidt Год назад

    Both are needed once things get a little advanced

  • @kaym7704
    @kaym7704 3 года назад +2

    I’m new to programming and I chose Python as a starting point... easier for a noob like me.

  • @juanfranciscopinerocucolo7211
    @juanfranciscopinerocucolo7211 2 года назад

    So then is better the IBM Course (Python) what Google Course (R) ?

  • @philippmuller2086
    @philippmuller2086 2 года назад

    I dont unterstand the last point: R is for statistics and Python for machine learning. I thought, machine learning is nothing else than statistic?

  • @easydatascience2508
    @easydatascience2508 2 года назад

    Python is a compuer scientist designed language, R is a statistician designed one. Python uses = for assignment, while R use -> as assignment symbol. Python's function is more flexible than R. Deep learning packages is written for Python, but not R. So R is a statistics-lise language, and Python is a data science language.

  • @AaronMOliver
    @AaronMOliver 3 года назад +4

    Hard to go wrong either way. If your job leans more towards data engineering and ETL then probably Python is a good choice to start with first, IMO.
    Thanks Alex!

  • @YlmazDALKIRANscallion
    @YlmazDALKIRANscallion 2 года назад

    Thanks for clarification.

  • @danganahl1682
    @danganahl1682 Год назад

    I am trying to find the best way to build a sports betting model using past statistics to project the outcome of future games/events/etc. I have messed around a little bit on Microsoft Excel doing this but I was just curious if anyone has a suggestion for which program would be the best for my needs between Excel/Python/R. Thank you for the help!

  • @Ottozone1
    @Ottozone1 3 года назад +1

    The Python example seems to be a bit cherry picked to show that Python has one function to apply the function mean to all the columns.
    Also, I'd like to know why R is more difficult to maintain?
    I think the pros for R should include ability for Markdown, better visualisation libraries, and piping is intuitive.
    Python pro should include that it's an actual programming language.

    • @bendirval3612
      @bendirval3612 2 года назад

      I class myself as an R guy, but I do have one problem with R as far as maintainability is concerned: I can't count on it always producing the same answers from the same code. Even on the same version of R, changes in its many packages tend to change my results all the time. And I get slightly different results on different computers. I have spent a lot of time in the last few years trying to overcome this problem but I'm considering sucking it up and porting a lot of my production code to python.

    • @mycrushisachicken
      @mycrushisachicken 2 года назад

      @@bendirval3612 how tf does that happen?

    • @farnsworthsclasses3523
      @farnsworthsclasses3523 2 года назад +3

      @@mycrushisachicken R and python differ in their third party package systems. Python has many packages but, you really only use 2 or 3 of them for data science. They are each large and aren't updated all that often--they seem to have lots of eyes on them and a reluctance to change rapidly. R has many thousands of packages, all of which do data science or statistics/econometrics. And they are all created/maintained/updated by their original authors, so the updates go to CRAN (R's central repository of packages) right away whenever the authors feel like it. You end up using lots more packages in R and the packages are all written by different people, who may not be overly concerned about the effects of updates on end users. So it's a lot easier to get two systems out of sync in R than python. There may also be numerical reasons why you get different answers on one computer versus another in R. I have, many times, had the experience of optimizers getting a slightly different answer on intel versus AMD, despite all my efforts to standardize, in R. I'm not saying this can't happen in python or matlab or whatever, but I haven't seen it as much.

    • @mycrushisachicken
      @mycrushisachicken 2 года назад

      @@farnsworthsclasses3523 damn thats crazy

  • @adrianchong5883
    @adrianchong5883 3 года назад +6

    Debates of Python VS R are pointless imo. They are good in their own ways.
    Most importantly, they are better than SAS.

    • @ponalvsiki2254
      @ponalvsiki2254 3 года назад

      Well, if you ask CS students, what programming language should be learnt first, 99% will tell you Python. CS students just love Python so much that they could have sexy dance with it if it were a girl.
      If anyone tells you to learn C first, you know you find your true lover.

  • @ai.aspirations
    @ai.aspirations 3 года назад +1

    thanks much!

  • @gustavb7193
    @gustavb7193 3 года назад

    So is R a programming language or a program like SPSS? R being close to python according to the comments kinda melts my brain

  • @SL-zn9oh
    @SL-zn9oh 3 года назад +5

    Hey Alex do you mind doing a video on the impact of automation on the future of the data analyst career? It would be really helpful to those who are on the fence about starting/changing their careers.

    • @AlexTheAnalyst
      @AlexTheAnalyst  3 года назад +1

      I definitely plan on making a video on AI and automation :)

    • @SL-zn9oh
      @SL-zn9oh 3 года назад

      @@AlexTheAnalyst Thanks!

    • @idakwiatkowska2862
      @idakwiatkowska2862 3 года назад

      Great topic! I also interested in your thoughts

  • @DaarShnik
    @DaarShnik 3 года назад +2

    If you are a non programmer R is easier to learn compared to python where you have to begin with oops and env etc... Which are way harder to grasp
    And the in built data types of R support data.frame and vector calculations thus making it easier to reason about...
    And i have deployed like dozens of code into production including web apps so almost all of your arguement are biased for what you use...

  • @junhotan2096
    @junhotan2096 3 года назад +1

    Why not both

  • @aldorodriguez7310
    @aldorodriguez7310 Год назад

    Which one would you learn first?

  • @superduper00donstar
    @superduper00donstar 2 года назад

    Have you ever used Eviews?

  • @jos3784
    @jos3784 3 года назад +2

    Can you recommend a R course on Udemy and/or have a promo code for a R course?

    • @veerasekhar8551
      @veerasekhar8551 3 года назад

      i wouldn't recommend any R course in Udemy

    • @veerasekhar8551
      @veerasekhar8551 3 года назад

      go for O'REILLY books

    • @gauravmishra8561
      @gauravmishra8561 3 года назад

      @@veerasekhar8551 bhai aap india se ho? whats your thought on spss?

  • @deniskk2
    @deniskk2 3 года назад +3

    Alex, its been 4 days getting in the Data analyst Game. you are my GOTO guy and the way you started this business story is real. I am following your classes because, they are simple and easy to read. the classes that are taking in LOOOONG and complicating stuff. Please let me know if you have Instagram, its easy to communicate there.Please Explain to your wife why you could to Instagram account.

    • @AlexTheAnalyst
      @AlexTheAnalyst  3 года назад

      Haha I’ll look into it 😁 so awesome to hear you’ve enjoyed the channel 👍

    • @davidil2147
      @davidil2147 3 года назад

      @@AlexTheAnalyst And that's why your wife is on the money about the professor thing xD

  • @jermainecameron6209
    @jermainecameron6209 3 года назад +5

    Once again, thanks for sharing your thoughts with us Alex. Can always count on your fair unbiased opinions.

    • @simonparker4992
      @simonparker4992 2 года назад +1

      It's crap. He has no idea what he's talking about.

  • @renanlolop
    @renanlolop 3 года назад

    For me, it's clear. Python is better for most of people, but, if one have strong math and stats background, R is probably the best.
    It's so much easier to collect data, clean it, put everything to work in python. But R is just THE WAY TO GO for statistical analysis. You get so many stuff out of the box. So many statistics, it is amazing.
    Tl dr: learn both, R for statistical and ML modeling. Python for anything else.
    If learning both is not an option, probably go the python route.

  • @JonMillerCO
    @JonMillerCO 2 года назад

    Thank you for this video Alex. I have always been intrigued by data analysis and want to learn more of the programming side. I was not familiar with either of these programs but your breakdown of the two help. If I wanted to learn both of these, would it be easier to learn Python first, then try to learn R or should I try to learn about R first, then Python?

    • @Rick-ll3jz
      @Rick-ll3jz 2 года назад

      They’re both hard. Start with python