![]() ![]() Using a pivot table makes that super simple, because it transforms the data and aggregates it for us. Let’s say we wanted to count the records grouped by Marital_Status. We can create a chart along with the table using the PivotChart feature under Insert. Pivot tables provide a simple approach to reformatting columns and rows, transforming them into groupings, statistics, or summaries. Pivot charts visualize the data expressed in a pivot table, giving us insight at a glance. One of my favorite features in Excel is pivot charts and, as a close follow-up feature, pivot tables. Here’s our very own senior data scientist, Tom, explaining these functions in a video: I am using the Customer Personality Analysis dataset from Kaggle in these examples. In order to show the power of data analysis in Excel, we need some data to play around with and graph. You can click any of the features to skip ahead to them. In this article, we’ll go over the 10 features and functions for using data analysis in Excel I think every analyst needs to know: One of the reasons Excel is so popular is because it is jam-packed with features and functions that can be used to clean, aggregate, pivot, and graph data. I personally use Excel almost every day because it can sometimes lead to quicker results than spinning up Python or loading the data into a database. ![]() ![]() Today, Microsoft’s ubiquitous spreadsheet program Excel has over 750 million users and is used in some of the largest companies worldwide. Spreadsheets are still in style! The use of electronic spreadsheets date back to 1979 and are still one of the most popular ways to review and manipulate data.
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