Nodules

Manipulate Your Data

The Power of Nodules

Tables me be foundational to Lovelace, but Nodules are the power! After you have imported some tables, you can perform some pretty nifty calculations on them. First we will explore the common configuration options that all nodules share. Then we will continue by exploring the three available types of Nodules that are available in the UI of Lovelace.

Just like a Table, a Nodule needs you to give it a label value, so you can find it later. Then we can import the tables that we want to perform our operations on. After that, lets select which type of operation we want to perform!

Quick Note: More than one table can be imported to a Nodule at a time; incase you have data of the same shape spread into several files.

Filter Nodule

A Filter Nodule is something you might want to use if you want to limit your data set by only certain criteria. Choose this option by selecting the Filter Nodule in the create Nodule form.

For example lets look at my current data:

Ticket Number	Equipt Cert #	Debris Type
32M3ZF6	7JVX6PM	VEG
7ZMKT7A	86FAPL8	VEG
3NF2S89	5GVW8QZ	C&D

I want to have a new dataset consisting of rows that only have the Debris Type equaling VEG.

To do this I will start by selecting the Comparison Type of Equal. Then I will enter Debris Type into the Key field. Along with it I will enter VEG into the Value field directly beside it. The Add button must also be selected to confirm that filter option. Now I will select Confirm to create my Nodule.

Now my new Nodule should show up in the Nodule list just as my table did. I can also delete my Nodule and view the data it exports just as I could the Table(s) that I imported into it.

Quick Note: A Filter Nodule may have many Key | Value sets, but only one Comparison Type at a time. Remember that when manipulating your data.

Join Nodule

The Join Nodule is a little more involved than the Filter Nodule. You would use a Join if you have multiple tables that have data that related to one another by some kind of identifier.

Lets build upon the data from earlier. I have this Table called Operations:

Ticket Number	Project Name	Equipt Cert #	Debris Type
EDG5D5	Birmingham Cleanup	56TF9D	VEG
RF567T	Birmingham Cleanup	E4GQ1	C&D
EFBE0R	Birmingham Cleanup	56TF9D	C&D

And I have another Table called Equipment Certifications:

Type	Placard	Active
Grapple Truck	56TF9D	true
Trailer	E4GQ1	false

Now each one of my Operations has a related piece of equipment stored in the Equipment Certification table. I want to be able to merge the row of the related piece of equipment on to each Operation. That is where the Join Nodule comes in handy.

I can see that each Operation has a Equipt Cert # column that correlates with the Placard of the Equipment Certification We will use that in our Join.

After we have selected the Join Nodule type in the form and the imported tables, we need to set what our Primary Table will be. This is the table related rows in other tables will be merged into. For us the Primary Table will be Operations.

Then we will select the Primary Key of Equpt Cert #.

Next lets select the Foreign Table as our Equipment Certifications.

Now lets select the Foreign Key of Placard.

Hold up, lets look at the why of those options again. In an Operation row, we have a, Equipt Cert # and this related to a piece of Equipment Certification by the Placard. So this will give us a new table with Operations combined with related Equipment Certifications like so:

Ticket Number	Project Name	Equipt Cert #	Debris Type	Equipment Certification::Type	Equipment Certification::Placard	Equipment Certification::Status
EDG5D5	Birmingham Cleanup	56TF9D	VEG	Grapple Truck	56TF9D	true
RF567T	Birmingham Cleanup	E4GQ1	C&D	Trailer	E4GQ1	false
EFBE0R	Birmingham Cleanup	56TF9D	C&D	Grapple Truck	56TF9D	true

If you are getting unexpected results, consider switching your Primary and Foreign Tables, you may have confused the direction of the Join.

This is an extremely powerful and sometimes confusing Nodule, lets move on to something a little simpler, but just as useful.

Transform Nodule

The Transform Nodule allows you to see only the data points you want to see and how you want to see them.

For instance, my latest dataset has some complicated column headers. I also do not care to have some of them. I want this:

Ticket Number	Project Name	Equipt Cert #	Debris Type	Equipment Certification::Type	Equipment Certification::Placard	Equipment Certification::Status
EDG5D5	Birmingham Cleanup	56TF9D	VEG	Grapple Truck	56TF9D	true
RF567T	Birmingham Cleanup	E4GQ1	C&D	Trailer	E4GQ1	false
EFBE0R	Birmingham Cleanup	56TF9D	C&D	Grapple Truck	56TF9D	true

To look like this:

Ticket Number	Debris Type	Equipment Type	Equipment Placard
EDG5D5	VEG	Grapple Truck	56TF9D
RF567T	C&D	Trailer	E4GQ1
EFBE0R	C&D	Grapple Truck	56TF9D

So after selecting the Transform Nodule type and importing my previous table, I am going to enter some values into the Initial Key and New Key fields in the form. The Initial Key field is for the name of the header that currently exist in the Table. The New Key field is for what you want it to be called.

Only the columns you enter will be the columns you return, even if you do not want to change the name of any column. This is why I have some Initial Keys identical to the New Keys

This is what i would need to enter to achieve the results I am looking for:

Initial Key	New Key
Ticket Number	Ticket Number
Debris Type	Debris Type
Equipment Certification::Type	Equipment Type
Equipment Certification::Placard	Equipment Placard

Make sure to select Add after each Key set to apply the configuration options.

Other Nodules can not be imported as Tables. To convert Nodules into Table, select the "To Table" option on the Nodule List Item. It will then be an option as a Table to Import as well as appear in the Table List.

That is it for Nodules in the UI of Lovelace. They do not take to long to set up and once you get use to the configuration options you will be able to do outstanding mutations on your data. If you are a JavaScript Developer you can take advantage of the GroupByNodule with the library lovelacejs on NPM!

Next up, lets start visualizing your data as charts!