Tip (4), Variable Explorer for both R and Python in RStudio

In recent past, frequent usage of both R and Python by Data Scientists are considerably increasing. RStudio is preferred IDE for most of R users, though, there are Editors and Notebooks which serve for both languages, yet, switching between them is not easy. Especially for those who got used to RStudio "Environment" tab for exploring objects in current R sessions; though, writing/execution of Python scripts from RStudio is there from quite some time, missing feature of  "Variable Explorer/Inspector" for python objects was a key concern, this has been addressed now by RStudio in their coming version (1.4), currently available as daily downloads, for all those who want to explore it early.

Happy R & Python Programming!

Views expressed here are from author’s industry experience. Author trains and blog’s on Machine (Deep) Learning applications with various programming languages; for further details, he will be available at mavuluri.pradeep@gmail.com for more details. Find more about author at https://in.linkedin.com/in/pradeepmavuluri

Nimble tweak to use specific python version or virtual environment in RStudio

Reticulate made switch between R & Python easy, and doing its best to facilitate both worlds of data science.

Meanwhile, I noticed that most of my followers or students raised the issues of uneasy switch between

different python versions or virtual environments in RStudio while using repl_python().

Here is my nimble tweak, hope, RStudio will come up with a better solution in coming days as in Spyder’s (pointing to interpreter).

As, most of us use, Rprofile.site which will be available in ~/R/etc folder for setting R environment variables,

exploit the same for setting needed python version or virtual environment:

# python version

Sys.setenv(RETICULATE_PYTHON = "~/python37/python.exe")

# python virtual environment

Sys.setenv(RETICULATE_PYTHON = "~/envs/stan_env/python.exe")

Currently, commenting and un-commenting needed version in Rprofile.site, and restarting session

seems to be not a bad nimble tweak for bringing up needed python environment in RStudio.

Average Expenses for TV across states of USA

This post makes an attempt to depict the averages spent across the states towards their TV channel expenses for a big size country (USA). Though it has been developed using sample data belonging to a particular service provider; this post depicts its interest in regional differences in average spent on said service across the country. Herein, I would like to bring to your notice that economic importance of some USA states being notably better connected with multiple service providers and due to geographical location and population density, results/insights may be specific to this sample data. All the analysis has been carried out using R Programming Language components (R-3.2.2, RStudio (favorite IDE), ggplot2 for mapping).

Average Amount Spent ($) on TV by States in 2015 (till Nov):

The figure below depicts the map of 48 states of USA (for which the data was available) wherein it shows the average TV expense by state for the year 2015 which was available till end of the November; with five different colors (i.e. five different intervals of average spent). 

As it is evident from above map that for given sample North-East (region) states region has highest averages spent on TV. Next best averages (orange color) are noticed in pacific region and few Central and East states. As mentioned earlier this may be due to economic importance or due to service provider geographical spread which the employed sample data fails to take an in-depth note.

Author undertook several projects and programs towards data sciences, views expressed here are from his industry experience. He can be reached at mavuluri.pradeep@gmail for more details.

Preview version of RStudio 0.97 is now available

Rstudio has changed its website extension from rstudio.org to rstuido.com/ide and kept its new preveiw version at below link, few new things as "package development" tools are included in this version that makes job easy to develop new package.

http://www.rstudio.com/ide/download/preview

Enjoy R programming.