One of the most exciting skills to learn in BI tools like Power BI or Tableau is how to create dynamic measures. The idea is that since dashboard space is limited, using dynamic controls—such as allowing users to select which measure to display—keeps the dashboard both compact and ...

In an earlier post, I discussed adding conditional formatting to an Excel chart. One key benefit of using Python in Excel for this—rather than relying on standard Excel charting—is the flexibility it offers. With Python, it’s simpler to adjust the chart when adding new variables or expanding ...

A scatterplot is a chart that displays the relationship between two variables by plotting data points along the X and Y axes, with each point representing a unique pair of values. By conditionally formatting points based on their category, we can reveal patterns, clusters, or outliers, making it easier to ...

Python in Excel significantly enhances the capabilities of Excel users, enabling more sophisticated data analysis and visualization. However, it’s important to note that Python in Excel operates within a pre-configured, pre-installed environment. For a detailed explanation of how this setup functions, you can refer to my previous blog post ...

Waffle charts are a great way to visualize data as a grid of squares where each square represents a portion of the whole. Unlike pie charts, which can be hard to interpret with many categories, waffle charts provide a cleaner, grid-based approach that makes it easy to compare parts of ...

Time series analysis lets analysts identify patterns, trends, and cyclic fluctuations over time. These insights are essential for accurate forecasting, strategic planning, and informed decision-making. Despite its significance, working with dates and times in a sophisticated manner is often hindered by Excel, which has become the butt of many internet ...

Excel has long been a go-to tool for data analysts to crunch numbers and perform data analysis. Traditionally, its ability to handle text data, particularly for advanced analysis tasks like sentiment analysis, was seen as limited. Analysts seeking meaningful insights from text often resorted to more specialized tools or cumbersome ...

When Copilot for Excel was first introduced, it primarily served as a tool to automate basic Excel tasks like sorting, filtering, conditional formatting, and creating formulas. However, as the AI has evolved and more resources have been invested in the product, it now supports more advanced functionalities, including sophisticated data ...

Advanced Analysis with Python in Copilot for Excel can help with many data analysis tasks that would typically be challenging to execute in Excel. From building predictive models using techniques like random forests to uncovering patterns and relationships through clustering and principal component analysis, and even analyzing text data for ...

In a previous blog post I showed how to get over limitations of creating dummy datasets directly in Microsoft 365 Copilot by asking for a Python script instead, particularly the faker package. Technology moves quickly, and since publishing that post, the Faker package has become available directly within the Python in ...