Overview

Teaching: 10 min
Exercises: 10 min

Questions

• How can we convert a column from one data type to another?

• How can we visualize relationships among columns?

Objectives

• Transform a text column into a number column.

• Identify and modify non-numeric values in a column using facets.

• Use scatterplot facet to examine relationships among columns.

Lesson

Numbers

When a table is imported into OpenRefine, all columns are treated as having text values. We saw earlier how we can sort column values as numbers, but this does not change the cells in a column from text to numbers. Rather, this interprets the values as numbers for the purposes of sorting but keeps the underlying data type as is. We can, however, transform columns to other data types (e.g. number or date) using the Edit cells > Common transforms feature. Here we will experiment changing columns to numbers and see what additional capabilities that grants us.

Be sure to remove any Text filter facets you have enabled from the left panel so that we can examine our whole dataset. You can remove an existing facet by clicking the x in the upper left of that facet window.

To transform cells in the recordID column to numbers, click the down arrow for that column, then Edit cells > Common transforms… > To number. You will notice the recordID values change from left-justified to right-justified, and black to green color.

Exercise

Transform three more columns, including period, from text to numbers. Can all columns be transformed to numbers?

Solution

Only observations that include only numerals (0-9) can be transformed to numbers. If you apply a number transformation to a column that doesn’t meet this criteria, and then click the Undo / Redo tab, you will see a step that starts with Text transform on 0 cells. This means that the data in that column was not transformed.

Numeric facet

Sometimes there are non-number values or blanks in a column which may represent errors in data entry and we want to find them. We can do that with a Numeric facet.

Exercise

1. For a column you transformed to numbers, edit one or two cells, replacing the numbers with text (such as abc) or blank (no number or text).
2. Use the pulldown menu to apply a numeric facet to the column you edited. The facet will appear in the left panel.
3. Notice that there are several checkboxes in this facet: Numeric, Non-numeric, Blank, and Error. Below these are counts of the number of cells in each category. You should see checks for Non-numeric and Blank if you changed some values.
4. Experiment with checking or unchecking these boxes to select subsets of your data.

When done examining the numeric data, remove this facet by clicking the x in the upper left corner of its panel. Note that this does not undo the edits you made to the cells in this column. If you want to reverse these edits, use the Undo / Redo function.

Scatterplot facet

Now that we have multiple columns representing numbers, we can see how they relate to one another using the scatterplot facet. Select a numeric column, for example recordID, and use the pulldown menu to > Facet > Scatterplot facet. A new window called Scatterplot Matrix will appear. There are squares for each pair of numeric columns organized in an upper right triangle. Each square has little dots for the cell values from each row.

Exercise

1. Examine the scatterplots overall. Do the patterns make sense?
2. Why does the scatterplot for recordID vs period have the pattern it does?

Examine pair of columns in detail

We can examine one pair of columns by clicking on its square in the Scatterplot Matrix A new facet with only that pair will appear in the left margin.

Exercise

Click in the scatterplot facet in the left margin and drag to highlight a rectangle. This will subset the data to those entries.

Exercise

• Click on the Scatterplot Matrix square for recordID and period to get that as a facet in the left margin.
• Redo the Text filter on scientificName to show only entries including the letters bai. Notice the change in the scatterplot. It might be easier to see if you click export plot to put it on a new browser tab.

Key Points

• OpenRefine also provides ways to get overviews of numerical data.