What are the pros and cons between  and Python versus R if I would like to do statistics on Linux? I know that I can use R inside Sage but in what order should I study those programs?
120879
Lots of people use a main tool like Excel or another spreadsheet, SPSS, Stata, or R for their statistics needs. They might turn to some specific package for very special needs, but a lot of things can be done with a simple spreadsheet or a general stats package or stats programming environment.  I've always liked Python as a programming language, and for simple needs, it's easy to write a short program that calculates what I need. Matplotlib allows me to plot it.  Has anyone switched completely from, say R, to Python? R (or any other statistics package) has a lot of functionality specific to statistics, and it has data structures that allow you to think about the statistics you want to perform and less about the internal representation of your data. Python (or some other dynamic language) has the benefit of allowing me to program in a familiar, high-level language, and it lets me programmatically interact with real-world systems in which the data resides or from which I can take measurements. But I haven't found any Python package that would allow me to express things with "statistical terminology" – from simple descriptive statistics to more complicated multivariate methods.  What can you recommend if I wanted to use Python as a "statistics workbench" to replace R, SPSS, etc.?  What would I gain and lose, based on your experience?
108331
Does there exist a program for Linux that can display raw binary data?  Each byte in my binary files represent a pixel, so it would be very useful if something like this exists where I could say  program_name --input=dat001.bin --width=200 --height=100   and it would display the pixels.  I wonder if gnuplot, can be used for this...?
42676
I was wondering if there is something like an interpreter for C.  That is, in a Linux terminal I can type in "python" and then code in that interpreter.  (I'm not sure interpreter the right word).  This is really helpful for testing different things out and I'm curious if something similar exists for C.  Though I doubt it.  The only thing I can think of that would do it would be the C shell...
43502
I have installed Ubuntu 12.10 on my laptop, now i want to use Python 2.5.4 for educational purpose. Can any one help me with step by step instructions... I also need IDLE for 2.5.4.
122850
Is there any Linux command one can use to sample subset of a file? For instance, a file contains one million lines, and we want to randomly sample only one thousand lines from that file.   For random I mean that every line gets the same probability to be chosen and none of the lines chosen are repetitive.  head and tail can pick a subset of the file but not randomly. I know I can always write a python script to do so but just wondering is there a command for this usage.
67580
I am interested in examples of sources (R code, R packages, books, book chapters, articles, links etc) for learning statistical and mathematical concepts through R (it could also be through other languages, but R is my favorite flavor).  The challenge is that the learning of the material relies on the programming, not just on how to run a code that performs the algorithm.  So (for example) a book like  (which is a great book) is not what I am looking for.  This is since this books mainly shows how to implement linear models in R, but it does not revolve around teaching linear models by using R.  The help files for the (wonderful)  is a good example of what I am looking for.  It is an R package which includes functions for learning statistical concepts through various R applets and simulations.  The accompany help files are nice.  Of course, neither are sufficient, and require an external text-book in order to master many of the exact details to learn them (well, the help files do).  All leads will be much appreciated.
94662
What is the difference between Anova(data)and anova(data)?  &gt; anova(res.full) Analysis of Variance Table  Response: Sales                      Df Sum Sq Mean Sq   F value    Pr(&gt;F)     Promotional.Accounts  1   1070    1070   35.0800 0.0001465 *** Active.Accounts       1  44337   44337 1453.2067 3.680e-12 *** Competing.Brands      1  43331   43331 1420.2314 4.124e-12 *** Potential             1     16      16    0.5146 0.4895772     Residuals            10    305      31                         --- Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 &gt; Anova(res.full) Anova Table (Type II tests)  Response: Sales                      Sum Sq Df   F value    Pr(&gt;F)     Promotional.Accounts    275  1    9.0193   0.01327 *   Active.Accounts       27371  1  897.1238 4.025e-11 *** Competing.Brands      42877  1 1405.3398 4.346e-12 *** Potential                16  1    0.5146   0.48958     Residuals               305 10                         --- Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’    I don't understand why in each table the F statistic for each factor is different.
85859
If I call os.stat() on a broken symlink, python throws an OSError exception. This makes it useful for finding them. However, there are a few other reasons that os.stat() might throw a similar exception. Is there a more precise way of detecting broken symlinks with Python under Linux?
113164
I had the understanding that the major difference between machine learning and statistical model is, the later "assumes" certain type of distribution of data &amp; based on that different model paradigm as well as statistical results we obtain (e.g. p-values, F-statistics, t-stat, etc.). But in case of machine learning, we don't bother about distribution of data and more interested in prediction.  When I was going through Mllib doc, I found for linear regression we are specifying a distribution. But Mllib is a machine learning package. So, I've the following questions:  1) Is my understanding between ML &amp; statistical method is wrong?  2) Is spark is using statistical modeling for linear regression and GLMs?  Thanks!  Note: There are lot of wonderful post regarding the difference between machine learning and statistical method. But this more related to spark MLLIB.
41273
I'm trying to put together a self-directed math curriculum to prepare for learning data mining and machine learning. This is motivated by starting  on Coursera and feeling that before proceeding I needed to improve my math skills. I graduated from college a while ago so my algebra and statistics (specifically from political science/psychology classes) are rusty.  The answers in the thread  only suggest books or classes directly related to machine learning; I have already looked into some of those classes and books and do not know exactly what math subject to study (for instance: what field[s] of math address deriving an equation to "minimize a cost function"?). The other thread suggested ()   only mentions broad categories of skills needed for analyzing data. The thread  does not apply because I do not already have a degree in math; a similar thread  has an incredible list of stats books, but again, I'm looking at starting math from a rusty recollection of algebra and moving up from there.  So, for those that work in machine learning and data mining, what fields of math do you find essential to do your job? What math subjects would you suggest to prepare for data mining and machine learning, and in what order? Here is the list and order I have so far:   Algebra Pre-calculus Calculus Linear algebra Probability Statistics (many different sub-fields here, but don't know how to break them out)   As for the data mining and machine learning, through my current job I have access to records on website/app activity, customer/subscription transactions, and real estate data (both static and time-series). I'm hoping to apply the data mining and machine learning to these datasets.  Thank you!  EDIT:  For posterity's sake, I wanted to share a helpful  for Geoffrey Gordon's/Alex Smola's  class at CMU.
75692
I'm new to Linux but not to app development. I come from a RealBasic on a Mac background.   I've accepted that I need to learn a new language to develop for Linux (since RB won't run on 64 bit distros and is a cloed proprietary language) but I want to make sure I pick the right one.   I've been looking at Python and was all set to go until I read that PyGTK is becoming obsolete with the introduction of GTK 3. Is this true? The Ubuntu developer website stills seems to recommend it with Glade for the UI but I want to make sure that I don't learn something that's on the way out!
23808
I'm looking for a full online course on college-introductory level statistics (and beyond). I've seen a few options on statistics.com ($600usd online courses ouch), and coursera (starts over a month from now).   I wonder if there are other good resources that could constitute a course on statistics (books seem to supplement courses well, but not replace them quite perfectly). Academic credit &amp; certification options are a plus, but not necessary.  Thoughts?
71511
I have just migrated from Windows environment. I have installed Python 3.2 in a separate directory. How can I get the python installation path in Ubuntu shell?  Is there any way I can let the shell know/choose at runtime which python version is to be used for further code execution?  Are there any environment variables and search path kind of things in Ubuntu Linux as well?
88780
How to install the R language interpreter? What is the package name? I have tried R, rlang, Rlang, rproject, etc. but nothing works - neither apt-get nor Ubuntu Software Centre found R.  Is it possible that R is not included in the official Ubuntu repositories?
17598
How do I learn where the source file for a given Python module is installed? Is the method different on Windows than on Linux?  I'm trying to look for the source of the datetime module in particular, but I'm interested in a more general answer as well.
10199
During the first half of 2015 I did the  (by Andrew Ng, GREAT course). And learned the basics of machine learning (linear regression, logistic regression, SVM, Neuronal Networks...)  Also I have been a developer for 10 years, so learning a new programming language would not be a problem.  Lately, I have started learning R in order to implement machine learning algorithms.  However I have realized that if I want to keep learning I will need a more formal knowledge of statistics, currently I have a non-formal knowledge of it, but so limited that, for example, I could not properly determine which of several linear models would be better (normally I tend to use R-square for it, but apparently that is not a very good idea).   So to me it seems pretty obvious that I need to learn the basics of statistics (I studied that in uni but forgot most of it), where should I learn, please note that I don't really need a fully comprehensive course, just something that within a month allows me to know enough so I can get eager and learn more :).  So far I have read about "", any other suggestion?
102244
Lately all of my work has been in Python (and Ruby), and I'm in love with those two languages. There are many libraries for game development on Python but the problem I see is that many of those frameworks don't cover the "distribution" aspect of game creation. I'd like to code my game on Python (and any other pure Python extra libraries I need) and be able to distribute an executable for the main PC platforms (Windows, Mac and Linux).  Any options out there or what are the best combinations for this? (maybe pyglet + cx_freeze)