We will call the flextable function to view the basic version of the table as shown below: flextable(df)Ħ. library(flextable)įor this library, the main function is flextable. Next, we will import the flextable library package.
You can find more about flextable here.įor installing the flextable package from CRAN, use the following command: install.packages(“flextable”)įor installing the development version of flextable from GitHub, use the following command: devtools::install_github(“davidgohel/flextable”) Tables can also be exported as R plots or graphic files, e.g., png, pdf, and jpeg. Tables can be embedded from R Markdown documents into HTML, PDF, Word, and PowerPoint documents and can be embedded using Package Officer for Microsoft Word or PowerPoint documents. Table content can also contain mixed types of text and image content. You can merge cells, add headers, add footers, change formatting, and set how data in cells is displayed. formattable(df, list( hp = color_bar(“#e9c46a”), cyl = color_bar(“#80ed99”), wt = color_bar(“#48cae4”), disp = color_bar(“#f28482”)))įlextable package helps you to create reporting table from a dataframe easily. To demonstrate this library, we will use the built-in function color_bar() to compare the magnitude of values in given columns of data. Next, we will import the formattable library package. You can find more about formattable here.įor installing the formattable package from CRAN, use the following command: install.packages(“formattable”)įor installing the development version of formattable from GitHub, use the following commands: devtools::install_github(“renkun-ken/formattable”) The package consists of several standard formattable objects, including percent, comma, currency, accounting, and scientific. This package includes techniques to produce data structures with predefined formatting rules, such that the objects maintain the original data but are formatted.
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formattable (License: MIT + file LICENSE ):įormattable data frames are data frames that will be displayed in HTML tables using formatter functions. Below is an illustration of the gt package’s architecture:Ģ. These are the table body, the table footer, the spanner column labels, the column labels, and the table header. The gt philosophy states that a comprehensive collection of table parts can be used to create a broad range of functional tables. The gt package offers a different and easy-to-use set of functions that helps us build display tables from tabular data. Here are a few packages we’ll use to create beautiful tables. Several R packages offer features to create nicely structured tables. Packages for Making Beautiful Data Tables in R In this article, we will discuss seven interesting packages for building colorful tables in R. These packages can not just create tables but also transform the basic tables into beautiful tables that effectively communicate the analysis findings. The CRAN website offers many open-source packages for R users. Although Data visualization in R is a vast topic in itself due to the availability of several robust and easy-to-use plotting libraries, the same can be said about tables in R. With some relevant narrative text, tables can precisely share the analysis findings for decision-making in an organization.
Tables are often used in reports along with supporting data visualizations to communicate the results of data analysis effectively. In the same context, tables are a powerful and efficient way of organizing and summarizing any available dataset, especially containing categorical variables.
Along with the correct choice of tools, a general understanding of the target audience and the goal of the analysis is also expected in any data analysis. Photo by Mahbod Akhzami on Unsplash Introductionĭeveloping meaningful visualizations is an essential yet challenging task in data science.
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