![]() ![]() Some Data preparation to convert the variable Rating to numeric and calculating Review length in len.#loading tidyverse to read input library(tidyverse) # loading itunesr for retrieving itunes review data that we will use in this analysis library(itunesr) #loading the magical esquisse library library(esquisse) # Flipkart Reviews reviews <- getReviews(742044692,'in',1) #converting Rating to numeric type reviews$Rating <- as.numeric(reviews$Rating) #let us say we want to see if there's any correlation between rating and review length reviews$len <- nchar(reviews$Review) To begin with, We will use the R package itunesr to extract some App Reviews (in this case, Indian e-tailer Flipkart’s iOS App) and try to visualize using our Drag and Drop GUI. # with remotes remotes::install_github("dreamRs/esquisse") # or with service (based on remotes) source("") # or with devtools: devtools::install_github("dreamRs/esquisse") Drag and Drop VisualizationĪs we have understood from the beginning, this package esquisse helps us in generating a visualization (ggplot2) with just drag and drop and we will we see how to do the same. Or you can install the development version that’s hosted on github using any of the following codes. ![]() ![]() Installation & LoadingĮsquisse is available on CRAN hence can be installed using the following code: # From CRAN install.packages("esquisse") It allows you to draw bar graphs, curves, scatter plots, histograms, then export the graph or retrieve the code generating the graph. This new R package esquisse is created and open-sourced by the French company DreamRs which has open-sourced multiple useful R packages like this one.Įsquisse allows you to interactively explore your data by visualizing it with the ggplot2 package. (As a side note, this is so intuitive, a Python user also could do!) About esquisse: If you are an R user and you’ve been envying them, Here is a magical tool - esquisse - that sits right inside your RStudio and helps you build ggplot2 with Drag and Drop GUI. The flexibility with which you can simply drag and drop your Dimensions and Metrics is so intuitive that a high school kid with no technical experience can build a decent visualization. One of the the few things that Self-service Data Visualization tools like Tableau and Qlik offer that sophisticated Data Science Languages like R and Python do not offer is - The Drag and Drop GUI to create Visualizations. ![]()
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