2. Creating 2-D graphs

We’ve seen some regional stuff, but there’s another question: What’s the average CO2e emissions per industry? Let’s create a new worksheet and explore that.

On a new worksheet, Drag “reported CO2e emissions” onto the Columns shelf and switch the calculation to “Average”.

Then, drag “Industry Type” onto the Rows shelf.

There’s a few too many industries, and many are similar.

2.1. Create some industry type groups (right now, dataset is far too detailed)

We can group these to get a better picture. This time, let’s click on the “Industry Type” Dimension within the Dimensions shelf, and click create -> group:

2.2. Create a bar graph from groups (2-D discrete graph)

Now, swap out the “industry type” on the Rows shelf with our new “Industry groups” dimension.

This menu gives us a lot of control over groups. Let’s create groups: Chemicals; Metals, Minerals; Nat. Gas; Others; Petroleum Products; Petroleum; Power Plants; Pulp and Paper.

To use this menu, you can shift+click or control+click on the industry types you want to group. Then, click the group button. If you want to add one or two types to an existing group, highlight them and click the "Add to:________" box in the top-right.

For this analysis, the only important groups will be Power plants, Others, and Pulp and Paper.

Takeaway: Power plants emit a ton. Well, several tons. We should look into that more later. First, what’re the subcomponents to the GHG emissions we’re looking at?

2.3. Create a scatterplot (2-D)

Our GHG dataset has a few different sub-components. Here’s a question: how does CH4 emissions relate to total GHG emissions? Let’s plot that. New worksheet, drag “reported CO2e emissions” to the rows and “Methane emissions” to the Columns. Switch them both to AVG rather than SUM.

Well, that's kind of weird. Note that we only have a single data-point. We’re averaging across the entire dataset, rather than looking at each facility. We can change this by dragging “Facility Name” onto Marks -> Detail.

Looking better! Note the null values in the corner of the graph. This indicates that 180 line-items have blanks for methane within the data. Let’s click on that null thing.

We’ve got two options: Filter the data or show at default position. If we filter the data, those data-points will be excluded from the graph. Instead, let’s show data at the default position, which is zero methane emissions. (presumably, a blank in the dataset means zero.)

So, we can see two distinct trends in the data. Some facilities have CH4 emissions, some don't. Can we figure out what’s going on? We'll need to add more dimensions to the graph. Onto the next section!

SUBPAGES (10): 1. INTRODUCTION 2. CREATING 2-D GRAPHS 3. 3-D GRAPHS AND MORE! 4. MAPS 5. MERGE IN EIA POWER PLANT DATA 6. DOES THE AMOUNT OF ELECTRICITY GENERATED INFLUENCE GHG EMISSIONS? 7. CALCULATED FIELDS 7. CALCULATED FIELDS 8. TRI DATASET & TABLE CALCULATIONS 9. DASHBOARDS

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