Understanding UIButton Highlighting in iOS When working with UIButton in iOS, one common question arises: how to control the highlighting of a button. While the highlighting feature is useful for various purposes, such as indicating selected state or providing visual feedback during user interaction, sometimes it’s necessary to customize its behavior. In this article, we’ll delve into the world of UIButton highlighting and explore two primary approaches to achieve the desired effect: disabling runtime highlighting and delaying the system’s call to highlight until after your custom logic has executed.

Understanding Alluvial Plots Alluvial plots are a type of data visualization that presents categorical data in a way that highlights the distribution of elements across different categories. They are particularly useful for displaying how different groups contribute to a larger whole, often used in fields like ecology, economics, and sociology. Key Components of an Alluvial Plot An alluvial plot consists of several key components: Origin: Represents the starting point or input side.

Grouping DataFrames by Common Columns and Adding a New Column In this article, we will explore how to add a new column to two dataframes based on common columns. We’ll use the popular pandas library in Python to accomplish this task. Introduction Dataframe merging is an essential operation in data analysis when you have multiple data sources with overlapping information. In many cases, you might want to combine these dataframes based on specific columns.

Understanding the Issue with SVM Plots Not Showing ====================================================== In this article, we will explore why the plot for a Support Vector Machine (SVM) model is not showing up. We’ll go through the code provided in the Stack Overflow question and understand what went wrong. Introduction to SVMs Support Vector Machines (SVMs) are a type of supervised learning algorithm used for classification and regression tasks. In this article, we will focus on binary classification problems where the goal is to predict one of two classes.

Average by Prod if null in R In this article, we will explore a problem involving calculating averages of certain columns based on another column’s presence or absence in R. The question presented involves filtering rows where Amount1 is missing and then averaging the remaining values for each product. Introduction The given problem presents a scenario where we have data with missing values and need to calculate an average value based on the presence or absence of certain values in another column.

Timestamps in Snowflake: Understanding and Formatting Introduction When working with time-stamped data in Snowflake, it’s not uncommon to encounter issues with formatting. In this article, we’ll delve into the world of timestamps and explore how to make a column display as a regular timestamp. Background on Snowflake Timestamps Snowflake is a cloud-based data warehouse that stores data in a tabular format. When working with timestamp columns, Snowflake uses a specific syntax to represent dates and times.

Query Optimization: Counting IDs Only When Matches with Date from Another Table As a technical blogger, I’ve come across numerous database queries that require careful optimization to achieve the desired results. In this article, we’ll delve into a specific query optimization challenge where we need to count the number of customers per status per month, only when a customer registered in that particular month and year. Problem Statement We have two tables: C_Status and Registrations.

Understanding SQL LEFT JOINs and their Limitations Introduction to SQL LEFT JOINs A LEFT JOIN (also known as a LEFT OUTER JOIN) is a type of join in SQL that returns all records from the left table and matching records from the right table. If there are no matches, the result will contain NULL values for the right table’s columns. In this article, we’ll delve into the world of SQL LEFT JOINs and explore why your initial attempt at performing one might be yielding unexpected results.

Understanding the Problem and Requirements The problem presented involves creating Python functions that take in a list of function names as input, evaluate each corresponding function, and then stack their outputs into a pandas DataFrame. The goal is to create a master function that can efficiently handle this task without requiring a series of conditional checks. Background: Function Evaluation and Pandas DataFrames To approach this problem, we need to understand how functions are evaluated in Python and how pandas DataFrames work.

Objective-C Delegate Method Hiding using BOOL Value In Objective-C, delegates are commonly used to implement a protocol that allows one class to notify another of specific events. However, there may be situations where you need to hide an implemented delegate method depending on the value of a certain boolean property. In this article, we will explore how to achieve this in Objective-C. Understanding Delegates A delegate is an object that conforms to a specific protocol and can receive notifications from another object when a particular event occurs.