You can use the lapply/Map function to loop over the columns of ‘data’ and apply the same code as before to each one. Then, you can bind the results together using cbind. Here is an example: library(GSVA) # assuming data is a list of data frames named "name1", "name2", ... out <- do.call(cbind, Map(function(x) { Sig <- unique(x$name) set.seed(8, sample.kind = "Rounding") core <- gsva(expr=as.matrix(data6), gset.idx.list=list(Sig), method="ssgsea") core2 <- as.data.frame(t(core)) colnames(core2)[1] <- names(x)$name core2 }, data, names(data))) out This will create a new data frame out where each row corresponds to one of the original lists (data$name1, data$name2, etc.

Understanding grep and lapply in R: A Deep Dive into Vectorized Operations Introduction R is a popular programming language for statistical computing and graphics. Its extensive use of vectors and matrices enables efficient operations on large datasets. In this article, we will delve into two fundamental functions in R: grep and lapply. We will explore how these functions work together to produce unexpected results when used with lapply, and provide a detailed explanation of the underlying concepts.

Finding Common Dictionaries in Two NSArray In this article, we’ll explore how to find two NSArray instances that have at least one common NSDictionary. We’ll delve into the technical details of this problem and provide a step-by-step solution using Objective-C. Understanding the Problem We’re given two arrays: otherContacts and chatContacts. The otherContacts array contains dictionaries with a single key-value pair, while the chatContacts array contains dictionaries with two key-value pairs. We want to find out if there are any common dictionaries between these two arrays.

Understanding Scoped Services in ASP.NET Core and Their Interactions with Singletons Introduction to Dependency Injection in ASP.NET Core In ASP.NET Core, dependency injection (DI) is a powerful feature that allows developers to decouple their applications from specific implementations of interfaces or abstract classes. The Microsoft.Extensions.DependencyInjection package provides the foundation for building applications with DI, and its services are used throughout this article. When building an application using DI in ASP.NET Core, one must understand how the different lifetime scopes (Transient, Scoped, Singleton) work together to provide services to components within the application.

WKWebView Page Goes Under Transparent Status Bar ===================================================== When building an iOS app with a WKWebView, it’s common to encounter issues with the page layout. In this article, we’ll explore one such issue where the WKWebView page appears under the transparent status bar. Introduction WKWebView is a powerful tool for rendering web content in an iOS app. It provides a high-performance and secure way to display web pages, while also offering features like custom UI delegate handling and web view configuration.

Enabling and Disabling the iOS Screen Programmatically In this article, we’ll explore how to control the screen on an iOS device programmatically using Swift 3. We’ll cover the basics of setting screen brightness, disabling proximity monitoring, and turning off the screen. Understanding the Problem When developing an iOS application that runs indefinitely, it’s essential to consider the battery life and overall stress on the device. By default, Apple disables screen brightness when not in use to conserve power.

Understanding the Pairwise Difference Function in PHP Introduction The pairwise difference function is a mathematical operation that calculates the absolute difference between consecutive numbers in an array. In this article, we will explore how to use this function and create an array from its results. The Problem with the Original Code The original code attempts to use the pairwiseDifference function to calculate the differences between consecutive numbers in an array. However, there are several issues with the original code:

Understanding the Problem and Identifying the Solution Introduction The problem presented involves querying a table with duplicate rows based on the ID column, while aggregating the data in a specific way. The goal is to achieve the following output format: ID Name Cost 1 Peter 10 20 30 2 Lily 10 20 30 In this scenario, we have a table with duplicate rows for each ID, and we want to aggregate the data by only considering the first occurrence of each ID.

Understanding the Problem and Tidyverse Solution The problem presented involves a data frame df created using the tribble function from the tidyr package in R. The data frame is grouped by the “group” column, and for each group, it applies a transformation to the values in the “y” column based on certain conditions. These conditions involve comparing the values of two other columns, “cond1” and “cond2”, with 99. The question asks how to adapt this code to incorporate additional iterations, where after running the initial mutate function, it applies subsequent transformations using nth(y, i) until a specified number of iterations are reached.

Grouping a Query by Each n Minutes Using Read-Only Access ==================================================================== In this article, we will explore how to group a SQL query by each n minutes using read-only access. We will also discuss the challenges of working with limited privileges and provide a solution that generates a list of dates 5 minutes apart between 10:45 and 11:20. Challenges with Read-Only Access When working with read-only access, it can be challenging to perform certain operations, such as grouping data by specific intervals.