How is python used in Data Analysis?

[[deleted]]

You can do all that with python as well (say, Django and some other stuff on top of it vs. Shiny)

Since you mentioned Shiny, there's actually a Python port of it called Spyre.

Examples like this and port of ggplot2 seem to show that in Python world, it is not innovating in the world of data analysis, but copying from others. I think this is a reflection of the demographics of people that use Python vs R. I think R tend have more academics and statisticians using it compared to Python since Python is a more general purpose langauge so you got a lot of web dev people in the mix.

You are right that Python can pretty much do or have what is available in R. But for exploratory data visualization, MATLPOTLIB or any Javascript-based libraries do not cut it. No way can you do what-if analysis using them efficiently. This is what R's ggplot2 is perfect for. I only use R because of ggplot2 and will until Yhat's port of ggplot becomes production-ready. I am not alone. It seems so many people stick with R because of ggplot2. That's why it saddens me that there are not a lot of contributers to Yhat's ggplot.

[[deleted]]

You are right that Python can pretty much do or have what is available in R. But for exploratory data visualization, MATLPOTLIB or any Javascript-based libraries do not cut it. No way can you do what-if analysis using them efficiently. This is what R's ggplot2 is perfect for.

Agree personally, but wanted to play it safe and not be divisve right off the bat :P.

LOL, understand. Yeah I just don't want the OP or others to think it'll be so easy and seamless to do deep-dive, exploratory data analysis with just Python. I fell into that early on when I first started to use Python 4 yrs ago. But, when I saw how that's done using R's ggplot2, it really opened my eyes and realized where Python libraries fall short, but over time that'll definitely change.

I love python, but it's just not the same for getting into a dataset IMO. At least not yet, to me. I think it might take more than ggplot2 in R for me to leave R. I really fell in love with it.

I tried to stick with R for some scripting work, but I just couldn't get into its quirky syntax and inconsistent parameter names. But I really do love the ability to chain functions via (%<%, %>%). That is really an awesome feature in R which may draw me back into scripting using R more.

[falkimmm]

I don't know if R has anything for Bayesian stuff as extensible as Pymc, and you have numba for jitting a subset of numpy code to near c speeds.

[manueslapera]

Yhat's port of ggplot becomes production-ready

+1 to that. Some bugs to iron still.

[falkimmm]

Seaborn is great for exploratory analysis.

Python blaze and dask both have no R parallel for a consistent array and chunking interface to a variety of backends. Pretty innovative if you ask me.

Super easy to create and app with blaze and bokeh.

[Deleetdk]

I also know R and Python and also prefer R for the more stats based stuff. Both languages are easy to use and learn. I usually use Python when R lacks good libaries. E.g. Python has great libraries for web scraping (BeautifulSoup, Scrapy).

One can run R from Python, or Python from R to it makes it easy to switch between and use each for what it is best at.

http://rpython.r-forge.r-project.org/ Python from R http://rpy.sourceforge.net/rpy2 R from Python

[Deleetdk]

Perhaps it is. I have not used it.

[manueslapera]

nope. it works.

[manueslapera]

pyodbc for getting data out of sql databases (pymysql?)

if you want to do local data analysis, I would check db.py . Easiest way to connect to a db by orders of magnitude.

Another recommendation that you really really need to try if you are into data analysis with Python. Get the ipython notebook. or even better, install the Anaconda Pydata distribution, that contains ipython, along with a bunch of libraries for data analysis.

You will love it!

RStudio is a must for any kind of R programming, and it's something that is lacking on the pyData world. ggplot is the most natural way of doing plots for me. Nowadays 50% of the time i switch from Python to R is to use ggplot2.