How to use the Analytics Pivot Tables in DailyNomie

What is Analytics

The Analytics area is introduced in the DailyNomie version of Nomie6-oss. It will let you drill down your data by making use of Pivot Table capabilities. You can explore correlations, create heat-maps, construct simple and very complex charts.

The Analytics possibilities as part of Nomie are based on the excellent pivottable.js module. PivotTable.js is an open-source Javascript Pivot Table (aka Pivot Grid, Pivot Chart, Cross-Tab) implementation with drag’n’drop functionality written by Nicolas Kruchten.

Navigate to the Analytics Section

When you are using Nomie from a desktop or laptop, you can navigate to the Analytics section via the sitebar menu:

When using Nomie on a smaller screen where the sitebar is not available, please click on the ‘more’ tab and then select Analytics:

Creating your first Pivot

Although you can use Analytics on both desktop and mobile screens, best usage of the capabilities is on large screens. The screenshots used in this documentation are taken from a desktop. The capabilities in both the mobile version as the desktop version are equal.

When navigating to the Analytics section for the first time, you will be presented with an empty screen as you have not yet defined any pivot yet. This documentation assumes that you have already some historical logging data in Nomie, otherwise you will get a message that there is not enough data to use the Analytics option/create a new Pivot. Let’s start creating our first Pivot by clicking on the ‘Create a New Pivot’ button:

After clicking this button, a default Pivot setup will be created with the following options:

Let’s start with choosing an Emoji and name for your new Pivot. I will name mine 💓 Heartrate. Let’s keep the other options as-is and click on the save button. You will be presented with a similar screen as shown below. Your Pivot will contain your personal trackers:

Configure your first Pivot

Now that you have initiated your first Pivot, its time to configure your pivot. As an example I will create a simple heat-map showing the relation between Heartrate and a given Day. You can follow my example or start experimenting already with your own data. The basic is always the same: pick the pivot type at the left site of the screen and start dragging and dropping your trackables in either the row section or the column section. Below screencast will show you my specific example:

That is easy…isn’t it? Now let’s create your second pivot. You can either do this by using the ➕new button from the Analytics menu, or you can decide to 🪞copy/duplicate the current Pivot and to further adjust. Do not forget to 💾Save your current Pivot first:

I will copy the current Pivot. It will bring me to the Pivot settings menu again:

Please change the name of the new Pivot in something you can recognize. I will call mine: 📊Chart. Then click on the save button and your new Pivot will be available. It will look exactly as the first Pivot you duplicated, but it will have the new name. Please also notice that it has been added to the top menu:

Now we will reconfigure this Pivot to show a chart of the data:

You see how easy it is to create a new Pivot. Now that you have the hang of creating a simple pivot, let me introduce some more advanced settings.

Grouping of your data

When using more complex Pivots it is useful to group the results of the Pivot in order to show a more aggregated result. In below example I used the first Pivot we created and dragged an additional field (DayPeriod) into the rows section:

As you can see in above screenshot, the data is now split in dayperiod per day. It contains more detailed information, but you can imagine when you are drilling down on your data you would like to play with it. You can do so by clicking on the grouping option. It will give you the ability to expand/collapse sections as shown in below screencast:

When you have grouping enabled, you can check the other options next to the grouping option to further order your data as you wish.

Filters

In some cases you would like to further drill down in only a subset of the datapoints of a given field. Let’s assume -in my example- that I am only interested in the weekend data (Saturday and Sunday). I can achieve that by clicking the twisty on the draggable datafield. In my example that is the Day datafield. I will get the following popup which let’s me filter only the weekend days:

The selection will then lead to the following filtered Pivot. As you can notice, any filtered datafield is represented by its name shown in italic font:

Even more advanced settings

Now let’s move to even more advanced settings which are available in the Pivot setting dialogue. While still working on the 💓Heartrate Pivot, please make sure to 💾Save and then click on the ✍🏼Edit button in the top menu. The Pivot Settings screen will appear. Next to b able to change the emoji and name there are some more options you can play with:

The first available option gives you the ability to pick the amount of history your dataset should contain. You can create Pivots with data for the last 30 days upto the last 3 years. Please be aware, the more history you choose, the longer it takes for a Pivot to load.

The Second option gives you the ability to reset all the filters. As explained earlier, you can enable filters on your dataset to narrow the data used in your Pivots. When using filters on a lot of different datafields, sometimes you might loose oversight of all the filters you have activated. This option let’s you reset all the filters in the Pivot.

The last option gives you the capability to provide your own search terms which will then be available as datafields for your Pivot, next to the standard created datafields from the trackables. Let me give an example. Personally I use Nomie to reflect on my day regularly by logging some free format text in Nomie. This text might contain keywords about how I felt that day. Now lets define the words ‘stress’ and ‘tired’ as a searchterms. Please make sure to separate your terms by a semicolon.

Click the Save button. Nomie will now count the amount of logs per day which contained the word ‘stress’ or ‘tired’ and add these as a datafields to the Pivot. You can recognize these ‘searchterm’ datafields by there light-blue color:

Now you can use your new datafields as all other datafields.

Set your Default Pivot

Everytime you navigate to the Analytics area in Nomie the Pivot set as default will be loaded. You can easily recognize the default Pivot by the green indicator of that Pivot in the top main menu. All other Pivots do have an amber indicator. As you can see, the indicator also contains a number which represents the amount of history days configured for the specific Pivot. You can switch the default Pivot by just clicking on such an amber indicator:

Well, I guess that is all for now…just start creating those Pivots👌