Notification Service Extension is not working ===================================================== In this article, we’ll explore how to implement a Notification Service Extension for an iOS app using Objective C and xcode 8.3. We’ll also delve into the issues that can arise when integrating push notifications with rich notifications. Introduction Push notifications are a convenient way to notify users of events or updates in their apps. However, the standard way to display a notification is limited by Apple’s guidelines.

Understanding Correlated Subqueries and the Challenge at Hand Correlated subqueries are a powerful tool in SQL that allow us to compare values from two or more tables based on their relationships. However, they can also lead to complex queries and performance issues if not used correctly. In this article, we’ll explore one such challenge: converting an OR condition into a UNION in a correlated subquery. A Look at the Original Query The original query is as follows:

Tallies: Calculating the Number of New Individuals Encountered Over Time Based on ID In this article, we will explore how to tally up the number of new individuals encountered over time based on their unique IDs. This problem is relevant in various fields such as wildlife monitoring, population studies, and epidemiology, where tracking individual subjects over time is crucial. Problem Statement Given a dataset containing individual IDs, dates of encounter, and the number of individuals encountered on each day, we need to calculate the total number of new individuals encountered as days go by.

Understanding the Issue with Feature Engine’s DropHighPSIFeatures Method =========================================================== The question at hand revolves around an error encountered while utilizing the DropHighPSIFeatures method from the feature engineering library, feature_engine. This method is designed to remove highly correlated features ( High PSIF value) in a given dataset. The problem arises when attempting to pass a pandas DataFrame into this method. Background on Feature Engine’s DropHighPSIFeatures Method The DropHighPSIFeatures class from the feature_engine.

Pivoting Data for Bar and Column Plots with Multiple Columns in R In this article, we will explore how to pivot data from a wide format to a long format, perform calculations on the pivoted data, and then create bar and column plots using ggplot2. We’ll focus on creating stacked bar plots where each column represents a percentage of the total value. Introduction Data visualization is an essential part of data analysis.

Understanding Rcpp and Modifying Values within R Lists =========================================================== Introduction Rcpp is a popular package for creating C++ code that can be integrated into R. It provides an easy-to-use interface for calling C++ functions from R and allows for the creation of efficient, high-performance C++ extensions. In this article, we will explore how to modify values within R lists using Rcpp. The Challenge Many users of R are familiar with working with R lists (also known as vectors or arrays).

Understanding the iloc Function in Pandas The iloc function in pandas is used to access a group of rows and columns by integer position(s). It allows you to manipulate specific elements in your DataFrame. In this article, we will explore how to use iloc effectively and provide examples on how to replace values in a range of rows using this method. Why Use iloc? iloc is preferred over other label-based methods (loc) when you need to access by integer position(s).

Installing and Managing Python Modules in Apache NiFi Apache NiFi is a popular open-source data processing tool used for ingesting, processing, and transporting data. It provides a flexible architecture for building data pipelines and integrates with various programming languages, including Python. In this article, we will discuss how to install and manage Python modules, specifically Pandas, within the Apache NiFi framework. Understanding the ExecuteStreamCommand Processor The ExecuteStreamCommand processor is a crucial component in Apache NiFi that allows you to execute external commands or scripts from your data pipeline.

Categorising Date Columns into Seasons In this article, we will explore how to categorize date columns in a pandas DataFrame. Specifically, we will learn how to map month names to season names and create a MultiIndex from the resulting columns. Background When working with dates in pandas, it is often useful to group them by season rather than just month. This can be particularly useful for time-series analysis or when dealing with data that has seasonal patterns.

Pandas Merge with Right-On Conditional ‘OR’ Overview of Pandas Merging Pandas is a powerful Python library for data manipulation and analysis. Its merging functionality allows us to combine data from two or more DataFrames based on common columns. This tutorial will explore how to use the merge method to merge DataFrames, focusing on the right-on conditional ‘OR’ approach. Introduction to the Problem The problem presented involves merging a left DataFrame with a right DataFrame based on multiple possible matching conditions.