For your users, working with big amounts of data has never been easy. Data without insight is worthless, we end up wondering what to do with our pile of rows and records. Fear not, there is an easy way to handle your data without being a data scientist or database guru.
For most people, pivot table is a fancy word, widely used among the Excel spreadsheet lovers. And if you are like me, you have probably Googled the meaning at least once. Well, turns out pivot tables are a really powerful feature that gives the user insight into their data. Their purpose is to summarize large amounts of data by applying operations such as averaging, sorting and grouping. As a result a pile of rows and data can quicly become a well-shaped and beautifully stuctured report.
You are still not sure what's the actual purpose of the pivot tables? No worries, an example is worth a thousand words! Let's have a look at the following example and see how we can use pivot tables.
Plot: We have a dataset with participants in different games. The participants are located in different countries and have different yearly and monthly winnings. This data is part of a bigger dataset but we will use only some of the attributes:
Task: Finding the total winnings for each country.
To solve our task we will use the magic power of pivoting in ag-Grid. So in order to find the total winnings for each country we need to find all participant from a country and sum their winnings. Easy, right?
First we need to enter 'Pivot Mode' or in other words - start a pivot table.
Entering 'Pivot Mode' gives us an empty table and some additional sections. Important here are these two sections:
Row Groups - holds the attributes by which we want to group our data. We can add attributes to this section simply by dragging them.
Values - holds the attributes of which we want to have aggregated values. Attibutes can be included by dragging.
Let's start by presenting a list of all coutries with participants.
Since we want to find the winnings of each country we should group our data by 'Country'.
Piece of cake!
Aggregation is used for presenting sum, average, min, etc. values of attributes with numeric values. We will use aggregation to get the sum of the winnings for each country.
Now we have all the countries with their corresponding total winnings. Beautiful, isn't it? In just a few clicks we have a summarized report of our complexed data.
We can also aggregate our data by different values. Have in mind that the default aggregation value is SUM.
Just as easy we can get summary not only of the total winnings but of the monthly breakdown.
As you already know we don't need to build pivot table from scratch, we can simply use the capabilities of ag-Grid.
Pivoting is, no doubt, one of the top features of ag-Grid Enterprise. Make sure you are using ag-Grid Enterprise in order to use pivoting and other high profile goods. You can find ag-Grid and ag-Grid Enterprise on npm and bower. If you have any difficulties you can refer to our getting started articles.
Once you are packed with ag-Grid Enterprise, you should simply edit the column definitions and add the
enablePivot property with value
This is a simple example of enabling pivoting in ag-Grid. Of course, ag-Grid has more advanced settings for pivoting in complecated scenarios. To find out more about pivoting, read the dedicated article in our documentation.
Congrats, you are a master of the advanced reports now!
Pivot tables are a powerful tool which is fairly simple to use once you know it's tricks.
You can try this by yourself right away, using the ag-Grid demo. If you are in a mood for writing code you can download ag-Grid and build your own grid with pivoting.
Sophia recently switched her carreer path from being a developer to becoming member of the ag-Grid team as a Developer Advocate. She is interested in various areas of the programming but her tech passion is the mobile world and the mobile technologies. In her "not a techie time" you can find her buying plane tickets and planning her next adventures.