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Exporting multiple graphs in same plot to PDF in R – TopBullets.com

Topbullets.comAs being a data scientist, plotting data is one of the first things we generally do. Without studying the behavior of the data we can’t or rather should not move ahead. There can be a lot of analysis which we can perform by plotting the graphs for example univariate, bivariate and residual plots. In my earlier blog, I wrote about how to plot two graphs in the same plot using par () function in R which is very useful when we do bivariate analysis and want to see the behavior of 2 variables across different time duration. Today I will write how to export the plots in PDF and in a tabular format. Generally exporting plots in any format (JPG, PDF) is an easier task but when you have say 50 graphs, you won’t want 50 pages, rather you will want 4 graphs in one page which will be very easier to read or interpret. Continue reading
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How to download data from Weather Underground – TopBullets.com

Topbullets.comWeather is an important factor for fast moving consumer goods product. It is a very interesting case study to read upon. Milk which is the major component for ice cream is heavily produced during winter as cows produce more in this season but consumed more in summer. So dairy products manufacturers have to adjust their storage of raw material and production of final products in such a way which can minimize the operational cost. Forecasting of FMCG products is also very important for manufacturer and temperature play again an important role to understand the demand. To understand the relation between temperature and demand we need historical data. So today I am going to write an R code and some manual trick to download the temperature data for different cities. Continue reading
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How to plot two graphs in the same plot in R and R Shiny

Topbullets.comWe as data analyst always have to do basic EDA or data manipulating before sorting the variable for developing any model. One of the first steps that we follow in EDA is bi-variate analysis. I will not go into details how or why we do bi-variate analysis, as you must know already and just want to learn how to plot 2 graphs in the same plot area in R. So let’s get started. I simply wrote an R code with comments to understand each step. Please check out the code below and comment if any step is not clear. Good luck. Continue reading
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How to permanently disable VLC recent played list on dock /taskbar on Windows 8 and 10

Topbullets.com The most viwed article on my blog till date is how to clear VLC history. I am sure we all love our privacy and can’t have a private laptop if we have friends and family roaming around. So it’s always better to take precuation to avoid unwelcomed problem. Recently I switched to Windows 10 and came across the same problem. I took help from one of my readers’ comment to write this article. If you are using Windows 7 you probably want to visit my last article “Clear VLC recent hisory“. And if using Windows 8 and above, let’s get started. You can also read my blog on sharing college proxy internet with mobile and other devices. Continue reading
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Collinearity and stepwise VIF selection

A good article for my fellow statistician and analyst

R is my friend

Collinearity, or excessive correlation among explanatory variables, can complicate or prevent the identification of an optimal set of explanatory variables for a statistical model. For example, forward or backward selection of variables could produce inconsistent results, variance partitioning analyses may be unable to identify unique sources of variation, or parameter estimates may include substantial amounts of uncertainty. The temptation to build an ecological model using all available information (i.e., all variables) is hard to resist. Lots of time and money are exhausted gathering data and supporting information. We also hope to identify every significant variable to more accurately characterize relationships with biological relevance. Analytical limitations related to collinearity require us to think carefully about the variables we choose to model, rather than adopting a naive approach where we blindly use all information to understand complexity. The purpose of this blog is to illustrate use of some techniques to reduce collinearity…

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