# 1893 search results for "excel"

## Data Science for Operational Excellence (Part-4)

April 27, 2017
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Suppose your friend is a restaurant chain owner (only 3 units) facing some competitors challenges related to low price, lets call it a price war. Inside his business he knows that there’s no much cost to be cut. But, he thinks that, maybe if he tries harder to find better supplier with low freight and Related exercise sets:

## Data Science for Operational Excellence (Part-3)

April 24, 2017
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Optimized transportation planning is a task usually left to the firm’s logistic department. However, it is often difficult to visualize, specially if there are many points involved in the logistic network. R and its packages can help solving this issue. Our goal here is to expand logistics networking visualization. In order to do that, we Related exercise sets:

## Data Science for Operational Excellence Exercises (Part-2)

April 14, 2017
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Network problems are everywhere. We can easily find instances in logistics, telecom, project mangement, among others. In order to attack these problems using linear programming we need to go beyond assign and transportation problems that we saw in part I. Our goal here is to expand the problems we can solve using lpsove and igraph Related exercise sets:

## Data Science for Operational Excellence (Part-1)

April 6, 2017
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﻿ R has many powerful libraries to handle operations research. This exercise tries to demonstrate a few basic functionality of R while dealing with linear programming. Linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. The lpsolve package in R provides a set Related exercise sets:

## The difference between R and Excel

February 22, 2017
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If you're an Excel user (or any other spreadsheet, really), adapting to learn R can be hard. As this blog post by Gordon Shotwell explains, one of the reasons is that simple things can be harder to do in R than Excel. But it's worth perservering, because complex things can be easier. While Excel (ahem) excels at things like...

## Three Tips for Training Excel Users in R

February 10, 2017
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by Merav Yuravlivker, CEO of Data Society “I’m not a coder” or “I was never good at math” is a frequent refrain I hear when I ask professionals about their data analysis skills. Through popular culture and stereotypes, most people who don’t have a background in programming automatically underestimate their ability to create amazing things

## BERT: a newcomer in the R Excel connection

November 30, 2016
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A few months ago a reader point me out this new way of connecting R and Excel. I don’t know for how long this has been around, but I never came across it and I’ve never seen any blog post or article about it. So I decided to write a post as the tool is really

## Introduction to R for Excel Users

May 3, 2016
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When all you have is a hammer...Engineers and scientists, Excel is the hammer. #Rstats is a toolkit. Here's an intro.

## Scoring R Models with Excel

March 17, 2016
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by Joseph Rickert In a post late last year, my colleague and fellow blogger, Andrie de Vries described enhancements to the AzureML R package that makes it easy to publish R functions that consume data frames as Azure Web Services. A very nice consequence is that it is now feasible to develop predictive models in R and enable the...

## Few steps to connect R with Excel: XLConnect!

March 9, 2016
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XLConnect allows to create a formatted spreadsheet usable as a dynamic report of the R analysis. Discover how to link R and Excel with just a few steps The post Few steps to connect R with Excel: XLConnect! appeared first on MilanoR.