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## Posts tagged Git

# Tag: Git

#### Styling DataTables

Feed: R-bloggers. Author: Senthil Thyagarajan. Most of the shiny apps have tables as the primary component. Now lets say you want to prettify your app and style the tables. All you need understand how tables are built using HTML. This is how the default datatable looks like in the app. In order to build the html table I have used a function table_frame which can be used as a container in DT::renderdatatable.This function basically uses htmltools. For more references on the basics of html tables please refer here table_frame Tables might have n number of records and its not feasible ... Read More

#### Happy EasteR! Let’s find some eggs…

Feed: R-bloggers. Author: Jurriaan Nagelkerke. It’s Easter Time! Let’s find some eggs… Hi there! Yes, it’s the most Easterful time of the year again. For some of us a sacret time, for others mainly an egg-eating period and some just enjoy the extra day of spare time. In case you have some time available for some good egg searching business, but no-one seems willing to hide them for you this year, here’s an alteRnative. Hide them yourself and have a nice easteR holyday! As you go, you also get to know the very nice image processing package: magick. Get some ... Read More

#### survivalists [a Riddler’s riddle]

Feed: R-bloggers. Author: xi'an. A neat question from The Riddler on a multi-probability survival rate: Nine processes are running in a loop with fixed survivals rates .99,….,.91. What is the probability that the first process is the last one to die? Same question with probabilities .91,…,.99 and the probability that the last process is the last one to die. The first question means that the realisation of a Geometric G(.99) has to be strictly larger than the largest of eight Geometric G(.98),…,G(.91). Given that the cdf of a Geometric G(a) is [when counting the number of attempts till failure, included, ... Read More

#### Binning with Weights

Feed: R-bloggers. Author: statcompute. After working on the MOB package, I received requests from multiple users if I can write a binning function that takes the weighting scheme into consideration. It is a legitimate request from the practical standpoint. For instance, in the development of fraud detection models, we often would sample down non-fraud cases given an extremely low frequency of fraud instances. After the sample down, a weight value > 1 should be assigned to all non-fraud cases to reflect the fraud rate in the pre-sample data. While accommodating the request for weighting cases is trivial, I’d like to ... Read More

#### FizzBuzz in R and Python

Feed: R-bloggers. Author: Method Matters. In this post, we will solve a simple problem (called “FizzBuzz“) that is asked by some employers in data scientist job interviews. The question seeks to ascertain the applicant’s familiarity with basic programming concepts. We will see 2 different ways to solve the problem in 2 different statistical programming languages: R and Python. The FizzBuzz Question I came across the FizzBuzz question in this excellent blog post on conducting data scientist interviews and have seen it referenced elsewhere on the web. The intent of the question is to probe the job applicant’s knowledge of basic ... Read More

#### Quick Example of Latent Profile Analysis in R

Feed: R-bloggers. Author: R on Will Hipson. Latent Profile Analysis (LPA) tries to identify clusters of individuals (i.e., latent profiles) based on responses to a series of continuous variables (i.e., indicators). LPA assumes that there are unobserved latent profiles that generate patterns of responses on indicator items. Here, I will go through a quick example of LPA to identify groups of people based on their interests/hobbies. The data comes from the Young People Survey, available freely on Kaggle.com. Here’s a sneak peek at what we’re going for: Terminology note: People use the terms clusters, profiles, classes, and groups interchangeably, but ... Read More

#### Control Charts Another Package

Feed: R-bloggers. Author: Analysis of AFL. I got an email from Alex Zanidean, who runs the xmrr package “You might enjoy my package xmrr for similar charts – but mine recalculate the bounds automatically” and if we go to the vingette, “XMRs combine X-Bar control charts and Moving Range control charts. These functions also will recalculate the reference lines when significant change has occurred” This seems like a pretty handy thing. So lets do it. First lets do our graphic from our previous post using ggQC library(fitzRoy) library(tidyverse) ## ── Attaching packages ───────────────────────────────────────────────────────── tidyverse 1.2.1 ── ## ✔ ggplot2 3.1.1 ... Read More

#### Animating the US Treasury yield curve rates by @ellis2013nz

Feed: R-bloggers. Author: free range statistics - R. My eye was caught by this tweet by Robin Wigglesworth of the Financial Times with an Alan Smith animation of the US Treasury yield curve from 2005 to 2009. It’s a nice graphic and it made me wonder what it would look like over a longer period.The “yield curve” is the name given to the graphic showing the different annual rates paid on investors who in effect lend money to the US Treasury. In normal circumstances, investors who are prepared to make the loan on a long term basis demand higher effective ... Read More

#### Edit datatables in R shiny app

Feed: R-bloggers. Author: Senthil Thyagarajan. Tables are very much the standard way of representing data in dashboard along with visualizations. Wouldnt it be more useful if you could edit the values in the tables to trigger some calculations and update the values on the fly . These can be used for adjusting allocations or budgets in a project. Libraries The libraries which we will be using are shiny for the app itself, dplyr and DT for displaying and editing the tables. library(shiny) library(dplyr) library(DT) Data For demo purpose we are creating a dataframe with three brands and few values ... Read More

#### Batch Deployment of WoE Transformations

Feed: R-bloggers. Author: statcompute. After wrapping up the function batch_woe() today with the purpose to allow users to apply WoE transformations to many independent variables simultaneously, I have completed the development of major functions in the MOB package that can be usable for the model development in a production setting. The function batch_woe() basically is the wrapper around cal_woe() and has two input parameters. The “data” parameter is the data frame that we would deploy binning outcomes and the “slst” parameter is the list of multiple binning specification tables that is either the direct output from the function batch_bin or ... Read More

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