Understanding Variable Names in R Functions As a programmer, it’s often essential to work with functions and their internal workings, especially when dealing with variables passed to these functions. In this article, we’ll delve into the world of R functions, variable names, and how to extract them. Introduction to R Functions and Variables In R, functions are blocks of code that perform a specific task. They can take input parameters, which can be variables or values.

Understanding the Iris Dataset and Machine Learning Model Evaluation In this article, we’ll delve into the world of machine learning model evaluation using the popular iris dataset. We’ll explore how to split a dataset into training and testing sets, use a loop to train and test a machine learning model, and compare the results with a for loop. Introduction The iris dataset is one of the most commonly used datasets in machine learning.

Preventing Dynamic Shiny CSS Files from Overwriting Each Other In this article, we will explore the issue of dynamic CSS file inclusion in Shiny apps and provide a solution to prevent overwriting of CSS elements. Introduction Shiny is an R package used for building web applications. One of its features is the ability to create interactive web pages using R code. However, when it comes to styling these web pages, things can get complicated.

Working with Presto: Unpivoting a Query to Get Column Names Based on Condition Presto is an open-source distributed SQL query language that allows users to execute queries on large datasets stored in various data sources. In this article, we will explore how to unpivot a query in Presto to get column names based on a condition. Introduction to Presto and Unpivoting Unpivoting is a process of transforming a data set from wide format to long format or vice versa.

Understanding RCurl and Setting HTTP Headers Introduction to RCurl RCurl is a popular R package used for making HTTP requests in R. It provides a convenient interface for sending HTTP GET and POST requests, as well as handling authentication, encoding, and other features. One of the key functions in RCurl is getForm, which allows you to pass GET parameters in a single function call. However, it has been observed that this function does not allow you to set custom HTTP headers.

Installing R Package with libstdc++ Introduction As a data scientist or statistician, installing third-party packages in R can be a daunting task, especially if you’re using a system with specific compiler settings. In this article, we’ll delve into the world of R package installation and explore how to overcome common issues related to compiling packages with libstdc++. Background R is an iconic programming language for statistical computing and graphics. It’s widely used in academia and industry for data analysis, visualization, and modeling.

You want to compare the distribution of sensor4_calcstatus across different ranges of ref_conc, but you can’t do that because there are two values greater than 100 in your dataset: 131.4 and 600.0. The way you calculate tbl is correct for ranges of ref_conc, so I assume that’s what you want to keep. Here is the updated R code: # Create the bar chart barplot(table(sample_data$sensor4_calcstatus)) # Calculate a new table with the desired range new_tbl <- table(cut(sample_data$ref_conc, breaks=seq(0, 100, by=5)), sample_data$sensor4_calcstatus) # Print the new table print(new_tbl) The resulting bar chart is not possible to create directly from tbl because it contains values greater than 100.

Understanding the Problem and Finding a Solution in R When it comes to temporarily suspending an internet connection from within R, there isn’t a straightforward way to achieve this directly. However, we can use the curl package’s low-level API to create a makeshift solution. In this article, we’ll delve into how to create a simple script that turns your internet connection offline and then back on again using R. Introduction to Working with Internet Connections in R The curl package is an essential tool for working with HTTP requests from within R.

Customizing ggplot for Multiple Page Layouts in a Single PDF Introduction In this article, we will explore how to create a single PDF file containing multiple pages of ggplots with different page layouts. We will discuss the use of gridExtra and ggsave functions in R, as well as provide examples and code snippets to help achieve this goal. Understanding gridExtra and ggsave The gridExtra package is used for creating complex layouts of plots.

Understanding R CMD Check and Its Output R CMD check is a command used to run checks on an R package, including the package’s documentation, code quality, and test suite. When you run R CMD check on your package, it provides a detailed report of the results, which can be useful for identifying issues and improving the overall quality of your package. What Happens During an R CMD Check When you run R CMD check on your package, the following steps occur: