Query your data

After working through the tutorial you should be able to:

As was discussed in the Intro to the data.world tutorial, a dataset is where data is stored for use in projects. It contains only the basic resources that pertain to the majority of the projects that use it. Queries are generally specific to a project as they pull only the data from the dataset which is needed for analysis for that project. As such, queries are stored, with rare exceptions, in a project. See our overview of the project workspace for more information.

To write a SQL query against data in a project go to the upper left corner of the project workspace and select SQL Query from the + Add menu:

When the query editor comes up in the center panel of the screen, the Project Schema also comes up in the right side panel. If the project schema isn't showing, select the arrow to the right of the Run query button to expand the sidebar:

Click next in the query editor window to begin entering your query text. As you type your query, the editor suggests SQL terms--operators, aggregations, and functions--for you. Arrow down or up to choose another option:

Hitting 'enter' will auto-complete the highlighted suggestion in the list.

You have the option of typing in the table and column names for the data you are querying, but you can also use the click-to-copy feature on the project schema to copy the names for you so you don't have to worry about typos.

Help text is provided for all SQL functions and aggregations when you hover over the function name:

While you can type your SQL query all on one line--it is perfectly legal and will run--it's good practice to split it up based on clauses and punctuation. The line breaks make it easier to see where you may have forgotten a comma or some other element of the query, and it also allows us to give you better error messages if there are problems with your query.

Here's an example of a query before and after running it through our auto-formatter:

To auto-format your query, use the keyboard shortcut Cmd + Option + L . If you forget the command there is a dropdown menu to the right of the Run query button which has a link to a list of all the keyboard shortcuts.

From the dropdown menu you can also manage your query (rename, copy, etc.) as well as get to our SQL tutorial for additional help.

The article on query editor shortcuts also contains a full list of the shortcuts for the query editor.

If you try to auto-format your query and it doesn't work, that's a sign that you have an error in the query. If you run it you'll get an error message telling you what the problem is and where to find it:

In the above example the query was written to search for the number of colonies recorded by year just for the state of Montana. However the way the query is written it looks like it is searching for records where the value in the bee_colony_census_data_by_state.state column matches the value in another column named Montana. For Montana to be recognized as a value, it has to be surrounded by double-quotes. The error message returned from running the query tells you that the problem is in the 3rd line and the 47th character position (column). The 47th character should have been the opening ":

When your query is complete, save it for later use by selecting Save to the left of the Run query button. You'll be prompted to name the query, add a description, determine where to save it, and indicate who can see it:

It's good practice to give the query a short descriptive name for both your own later use and for use by others working on your project. Adding a description also makes your query more usable as the description shows up on the resource card returned from using search on data.world.

SELECT *
FROM bee_colony_census_data_by_county
WHERE bee_colony_census_data_by_county.state = "MONTANA"

There is much more to learn about queries and query languages than will fit into one tutorial, and this one just scratches the surface of how to write and save queries. If you're conversant with SQL or SPARQL, your best next step is use your project to practice writing queries on data.world. If you need more information, both our SQL and SPARQL documentation are great resources. If you don't know either SQL or SPARQL and want to query data.world datasets we recommend you work through our SQL tutorial. More information about queries and how to use them is covered in the tutorial Advanced work with queries.