After you’ve collected environmental data from a sensor, monitor, or other piece of equipment, one of the next steps is to organize and “clean” it!
Cleaning includes making sure the dataset is complete and consistent. Organizing the data into a table in a meaningful way gets it ready for making charts, graphs, and other visualizations. Below are some resources on cleaning data, including making tables of tidy data.
An example of “tidy data” from an air quality sensor might look like this:
Each variable forms a column: sensor ID number, date, time, and the air quality measurement of particulate matter are individual variables. Each variable gets its own column in the table. The column header at the top lists the variable name and its units of measurement.
Each observation forms a row: this sensor took an air quality measurement every minute. Each measurement gets its own row in the table.
Each cell is a single measurement: each block in the table shows one piece of data---one time, one PM measurement, etc.