R multiple visual in one: Regression Table and Boxplot
In this pbix File, we construct an analysis of Theory of change and create a R visual that gather a regression analysis and a Boxplot visual. Theory of change is a theoritical relation between indicators: Gestion -> Output -> Outcome -> Impact How we do -> What we do -> Why we do -> General Objective
Decision Trees
Description With decision trees, you can visualize the probability of something you want to estimate, based on decision criteria from the historic data. The decision tree classifier automatically finds the important decision criteria to consider. Prerequisites (The sample .pbix files will not work without these prerequites completed) 1. Install R Engine Power BI Desktop does not include, deploy or install the R engine. To run R scripts in Power BI Desktop, you must separately installR on your local computer. You can download and install R for free from many locations, including the Revolution Open download page, and the CRAN Repository. 2. Install the required R packages. Download the R script attached to this message and run it to install all required packages on your local machine. Required R packages: rpart, rpart.plot, RColorBrewer Tested on: CRAN 3.3.1 R, MRO 3.3.0, , powerbi.com Legal Disclaimers: Terms of Service and Third Party Programs.
Matrix Bubble Chart
What A powerful Power BI R visual, matrix bubble chart, to analyze three measures (facts) with two selected dimensions. How One needs to have R installed on the computer or to the server / enabled in the cloud environment. Here is a guide to get started: https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-r-visuals Here is a link to some details: https://docs.microsoft.com/en-us/power-bi/visuals/service-r-visuals Analysis example The edge color of a bubble tells about the margin % of a product. The fill color of a bubble tells about the % of opportunities won (hitrate) of a product. The bubble size illustrates the number of the opportunities. In the X-axis is the product dimension. In the Y-axis is the free feature bundle given together with the product dimension. This could be an example from the car industry. The question could be what bundles we want to offer with what products and how should we price the product & bundle combinations. See my blog post for an example use case: https://www.plainlyresults.com/blog/power-bi-r-matrix-bubble-chart-sales-opportunity-analysis/ CODE Add in your Power BI R visual the code below the "Paste or type your script code here:" text. #change lib path to were you have ggplot2 and scales installed library(ggplot2, lib="D:/Program Files/R/R-3.6.3/library") require(ggplot2) library(scales, lib="D:/Program Files/R/R-3.6.3/library") #change columns Product, Free_feature_bundle, dataset$... to your columns in the Power BI model selected to the R visual ggplot(dataset, aes(x = Product, y = Free_feature_bundle, label = paste(round(dataset$Opportunity_count, digits=0), round(dataset$Hitrate_perc, digits=2)*100, round(dataset$Margin_perc, digits=2)*100, sep=";"))) + geom_point(shape = 21, aes(size = round(dataset$Opportunity_count, digits=0) , fill = round(dataset$Hitrate_perc, digits=2)*100, color = round(dataset$Margin_perc, digits=2)*100, stroke = 3)) + geom_text(hjust = 1, size = 4) + scale_size(range = c(15,50)) + #scaling of the bubbles theme_bw()+ scale_fill_gradient2("Hitrate % (fill)", low=muted("red"), high=muted("green"), midpoint = mean(dataset$Hitrate_perc*100)) +theme_bw()+ scale_color_gradient2("Margin % (edges)", low=muted("red"), high=muted("green"), midpoint = mean(dataset$Margin_perc*100)) + labs(size = "Number of opportunities (size)")COMPARTILHAR
Olá, Pessoal, Quero compartilhar meu painel na web mas a conta pede um administrador... E mesmo seguindo toooodos os vídeos do youtube, não consegui compartilhar meu painel... O que preciso é compartilhar apenas a visualização e filtro de forma que não seja necessário login e senha.... Alguém tem um caminho fácil??? ou até incorporar em alguma plataforma que tenha a funcionalidade que precisoARIMA forecasting
ARIMA forecastin will soon be available as R-powered custom visual. ARIMA modeling is the general class of models for forecasting a time series. ARIMA stands for an Autoregressive Integrated Moving Average and is among the most popular forecasting techniques. You may find rich set of parameters inside R-code behind the R visual. Both user mode and automatic modes are available.Correlation Plot
Description Correlation plots can be used to quickly find insights, showing what otherwise would require lots of iterative slicing and dicing of your data. Download this sample to see how a correlation plot can inform marketing strategies in different market segments. Prerequisites (The sample .pbix files will not work without these prerequites completed) 1. Install R Engine Power BI Desktop does not include, deploy or install the R engine. To run R scripts in Power BI Desktop, you must separately install R on your local computer. You can download and install R for free from many locations, including the Revolution Open download page, and the CRAN Repository. 2. Install the required R packages. Download the R script attached to this message and run it to install all required packages on your local machine. Required R packages: corrplot Tested on: CRAN 3.3.1, MRO 3.3.0, powerbi.com Legal Disclaimers: Terms of Service and Third Party Programs.
