Step 1: Extract model data using sjPlot We start by extracting the model data using sjPlot::get_model_data. This function takes in a list of models, along with some options for the output. In this case, we’re interested in the estimated coefficients, so we set type = "est". mod_data <- lapply(list(mod1, mod2), \(mod) sjPlot::get_model_data( model = mod, type = "est", ci.lvl = 0.95, ci.style = "whisker", transform = NULL )) Step 2: Bind rows by model We then bind the results together using dplyr::bind_rows.

Understanding Indexing in SQL: A Deeper Dive into Cumulative Counts As a professional technical blogger, I’d like to take you on a journey to understand the intricacies of indexing in SQL, particularly when it comes to cumulative counts. We’ll dive into the world of window functions, case statements, and partitioning to uncover the secrets behind solving your specific problem. Background: Window Functions in SQL Window functions are a type of SQL function that allow you to perform calculations across a set of rows, rather than just on individual rows.

Understanding initWithNibName, awakeFromNib, and viewDidLoad in iOS Development Introduction As an iOS developer, understanding the nuances of nib file initialization is crucial for writing clean, efficient, and maintainable code. In this article, we’ll delve into the world of initWithNibName, awakeFromNib, and viewDidLoad – three essential methods that play a vital role in setting up your app’s user interface. What are initWithNibName, awakeFromNib, and viewDidLoad? nibFileInitialization When you create an instance of a view controller using Interface Builder (IB) or programmatically, the system uses the associated .

Introduction to Creating a New Column in a DataFrame based on Conditions In this article, we will explore how to create a new column in a pandas DataFrame based on certain conditions. We will use Python and the popular pandas library to achieve this. Background: Understanding DataFrames and Series Before diving into creating a new column, it’s essential to understand what DataFrames and Series are in pandas. A DataFrame is a two-dimensional table of data with columns of potentially different types.

Understanding Zooming Views and Text Rendering =============== When implementing interactive views, such as scroll views or view controllers that display timelines, it’s common to encounter issues with zooming. In this article, we’ll explore how to redraw zoomed text on a transformed UIView without distorting the layout. The Problem Suppose you’re creating an expanding timeline where users can pinch-to-zoom. You’ve implemented a scroll view that handles the zooming, and you want your drawn text labels to remain at their relative locations within the view.

Consolidating IQueryables in ASP.NET: A Step-by-Step Guide ASP.NET developers often find themselves dealing with complex data queries, especially when working with Entity Framework. In this article, we’ll explore how to consolidate three IQueryable objects into one, making it easier to pass the result to a view and print the desired output. Introduction In this article, we’ll focus on using LINQ (Language Integrated Query) to group and aggregate data from multiple IQueryable sources.

Database Transformation: Scheduling Data for Reporting Purposes In today’s fast-paced data-driven world, organizations rely on reliable data transformation processes to extract insights from their data. One common use case is generating reports that require scheduling of data from existing tables in a database. In this article, we’ll explore the process of transforming your data by creating separate tables for daily schedules and provide a step-by-step guide on how to achieve this.

Understanding MS-Access Update SQL Not Null But is Blank (! Date & Number Fields !) MS Access provides a powerful way to interact with databases, but sometimes, the nuances of its SQL syntax can be challenging to grasp. In this article, we’ll delve into the world of MS Access update SQL and explore how to deal with fields that appear null in the database but are actually blank due to input masking or formatting.

Rcpp Deparse Equivalent Introduction As a developer, it’s common to work with both R and C++ in our projects. While the two languages share some similarities, there are instances where we need to interact with R code from C++ or vice versa. This is particularly true when working with R packages that provide an interface between R and C++. In such cases, knowing how to seamlessly switch between these languages can greatly enhance productivity.

Extracting Numbers from Strings in Pandas In this article, we will explore how to extract numbers from strings in a pandas DataFrame and use it to create a new DataFrame with combined balances. Introduction Pandas is a powerful library used for data manipulation and analysis in Python. One of its most useful features is the ability to handle missing or duplicate data. In this article, we will focus on extracting numbers from strings in a pandas DataFrame.