Extracting Weekends and Bank Holidays from Stock Price Data Introduction In finance, stock prices are often reported daily, with each day’s price serving as the previous day’s closing price. However, not all days are created equal when it comes to trading and analysis. Weekends and bank holidays can have a significant impact on market behavior, leading to unusual patterns in stock prices. In this article, we will explore how to extract weekends and bank holidays from your stock price data using Python and the pandas library.

Modifying a Subset of a Pandas MultiIndex Pandas DataFrames with MultiIndex are powerful tools for data analysis, but they can be tricky to work with. In this article, we’ll explore one of the most common challenges when working with MultiIndex: modifying a subset of one of its levels. Background A pandas DataFrame with MultiIndex is a 2D labeled array with columns as index labels and rows as data values. The MultiIndex consists of two or more hierarchical levels, which are used to identify unique combinations of index values.

Working with Excel Templates using OpenPyXL and Pandas When it comes to working with Excel templates, especially when dealing with dataframes and worksheets, there are several considerations to keep in mind. In this article, we will explore how to append a dataframe to an Excel template without losing the contents of the template. Understanding the Problem The problem at hand is appending a dataframe to an existing Excel template while preserving its original content.

Understanding Firebase Push Notifications and Their Limitations Background and Context Firebase is a popular backend-as-a-service platform that provides various tools for mobile app development, including push notifications. In this article, we’ll delve into the world of Firebase push notifications, exploring their functionality, limitations, and potential issues. When it comes to push notifications, developers often face challenges in ensuring seamless delivery of notifications to users. This can be due to various factors, such as network connectivity, device configurations, or even testing environments.

Calculating Percent Change in a Pandas DataFrame ===================================================== In this article, we will explore how to calculate the percent change between two consecutive values in a pandas DataFrame. We will cover the basics of pandas and how to use its built-in functions to achieve this. Introduction to Pandas Pandas is a powerful library in Python for data manipulation and analysis. It provides data structures and functions to efficiently handle structured data, including tabular data such as spreadsheets and SQL tables.

Writing Input for .NET Web Services Introduction When building web services, it’s essential to understand how to handle input and output correctly. In this article, we’ll delve into the world of SOAP-based web services and explore a common problem that can arise when working with XML data. XML Basics Before we dive into the details, let’s quickly review some basics of XML (Extensible Markup Language). XML is a markup language used to store and transport data in a structured format.

Understanding the xlrd Error: ValueError: invalid literal for int() with base 10: '' Introduction to Python’s xlrd Library Python’s xlrd library is a popular tool for reading Excel files. It allows users to easily parse and extract data from various Excel file formats, including .xls, .xlsx, and others. However, in some cases, the xlrd library may encounter errors when trying to open or read Excel files. One common error that arises is ValueError: invalid literal for int() with base 10: ''.

SQL VBA - Delete from where not exist Introduction As a professional technical blogger, I’ve encountered numerous scenarios where developers face challenges while integrating their Access databases with Excel using VBA. In this article, we’ll delve into the specifics of deleting records from an Access database table based on data that does not exist in another table. We will explore several approaches to resolve this issue and highlight best practices for database integration using VBA.

Understanding the Problem and Solution In this article, we will discuss how to change the bin size for each subplot when using Dataframe.plot in pandas. This problem has been encountered by many users who have numerical data in their DataFrame but face issues with automatically scaling bins. Why Auto-Bin Scaling Fails The df.plot function uses a heuristic approach to determine the optimal number of bins based on the range of values in each column.

Understanding Background Execution on iOS ==================================================================================== Introduction Background execution on iOS refers to the ability of an app to continue running in the background even when it is not currently in use. This feature allows apps to perform tasks such as syncing data, fetching updates, or executing scheduled tasks without interrupting the user’s experience. In this article, we will explore how to create an iOS app that can take photos automatically every hour or so while running in the background.