Splitting Strings After a Delimiter Without Knowing the Number of Delimiters Available in a New Column Using Pandas In this article, we’ll explore how to split a string after a delimiter without knowing the number of delimiters available. We’ll focus on using Python and Pandas for this task. Understanding the Problem Suppose you have a column in a data frame that contains multiple words separated by dots (.). You want to get the last word after the last dot but don’t know how many dots are in each cell.

Reading CSV Files with Pandas and Writing to New CSV Files In this article, we will explore how to read a CSV file using the popular Python library pandas. We’ll then dive into extracting specific rows based on conditions, such as values divisible by certain numbers. Introduction CSV (Comma Separated Values) is a common format for storing tabular data in plain text files. The pandas library provides an efficient way to manipulate and analyze CSV files.

FMDB and UITableView: A Deep Dive into Managing Large Data Sets =========================================================== In this article, we’ll explore how to efficiently manage large data sets in an iPhone or iPad application using the FMDB wrapper for SQLite3 and UIKit’s UITableView. We’ll delve into the best practices for displaying a large number of records without pagination and discuss the implications of not implementing pagination. Understanding FMDB and SQLite Before diving into the implementation details, let’s quickly review how to use FMDB and SQLite.

Understanding Kerberos Authentication in iOS 6.0 and Older Introduction to Kerberos Authentication Kerberos is a widely used authentication protocol that provides secure authentication for various applications, including enterprise networks. In this post, we will explore the process of implementing Kerberos authentication on iOS devices running version 6.0 and older. What is GSSAPI? GSSAPI (Generic Security Service Application Programming Interface) is a standard API that allows different systems to authenticate each other using mutual authentication protocols like Kerberos.

Reshaping Pandas DataFrame from Categorical to Counts Introduction Pandas is a powerful library for data manipulation and analysis in Python. One of its key features is the ability to handle categorical data, which can be either strings or integers representing different categories. In this article, we will explore how to reshape a pandas DataFrame with two columns: ID and categorical, so that there is a column for each unique categorical value.

Counting Audio Power Peaks on iOS Introduction In this article, we will delve into the world of audio processing on iOS and explore how to count audio power peaks. This involves working with audio queues, processing raw input data, and implementing smoothing techniques to accurately measure peak power levels. Audio Queue Service The Audio Queue Service is a fundamental component in iOS for managing and processing audio streams. It allows developers to create custom audio processing applications that can handle real-time audio data.

Using Cumulative Functions in Dplyr: A Practical Guide to Repeating Values After Identifying a “1” In this article, we will explore how to use the cummax function from the dplyr package to create a new column in a tibble that repeats values after identifying a specific value. We will provide an example of using cummax to repeat “1” until the end of records for a given ID. Introduction The dplyr package provides a range of functions for data manipulation, including group_by, summarise, and mutate.

Exporting Last Four Years’ yfinance Balance Sheet Results Into Single Excel Workbook? Introduction The yfinance library in Python is a popular tool for accessing financial and economic data from Yahoo Finance. One of the key features of this library is its ability to fetch balance sheet data for companies. However, fetching balance sheet data for multiple years can be cumbersome using the yfinance library alone. In this article, we will explore how to export last four years’ yfinance balance sheet results into a single Excel workbook.

Merging Multiple CSV Files with Different Column Names As data becomes increasingly ubiquitous, managing disparate datasets can be a significant challenge. When working with multiple CSV files that contain similar data but with varying column names, merging these datasets into a single cohesive file can be a daunting task. In this article, we will explore various approaches to merge multiple CSV files with different column names, including using pandas and Python.

Plotting Multiple Barplots on One Plot without Overlapping Bars =========================================================== In this article, we will explore how to create multiple barplots on one plot without overlapping bars using R and the ggplot2 library. We’ll discuss various approaches to achieve this, including setting different y-axis limits for each barplot and using faceting. Introduction When working with multiple datasets that have similar characteristics, it’s common to want to visualize them together on the same plot.