All of our widgets follow the same pattern. You use the options tab to design your widget, for example pick the variables you want to chart, and then the filters tab to filter for a specific segmentation, if needed.

The table widget follows the same principle but it is a touch more complicated, so a more in-depth explanation is in order.

The table widget can be a simple table or a pivot table.

When setting up a simple table the first thing you do is name your table in the widget name field. Here we have a dataset containing hotel reviews from various countries. I am going to create a table that primarily looks at the average price per country.

Next, you choose which variables to group by. These are the variables the data will be displayed by. In the dropdowns you will find the different metadata variables contained in the original dataset along with the metadata supplied by Keatext: topics, opinion and tags.

To make a simple table choose date from the column dropdown, a field dropdown will now appear, and date from this newly appeared the field dropdown. Make sure your granularity is set to “all time” at the top right of the popup. A simple table is always set to “all time” as it is not breaking the data down into different time periods.

Now choose the variable that will be in the rows of the table. If you want a variable from your metadata choose a field from the row dropdown and the variable of your choice. In our case we have chosen country.

Lastly, you must choose your values, what you want to calculate by. You can calculate by any metadata field in the original dataset, plus Keatext metrics such as comment count, record count or sentiment score etc.

The calculated field options will vary according to the variable chosen.

I have chosen to look at the average room price per country and for fun I threw in the average sentiment score per country.

From the table I can see that the best value - with a very high sentiment score of 10 and the cheapest average room price of $39 - is Greece. Now that's a good argument for going on vacation!

From here you can filter your chart by moving to the filters tab if you want to segment the data to exclude certain information. For example if I only wanted to look at European countries I could filter out the United States, Australia and Canada.

You can also display the values as a percentage if you choose.

Now let’s pivot that table!

You can pivot the table by the field of your choice. I will be looking at room type. I removed the value sentiment score (just to make room on the table, you can keep it if you want to). Now I can see the average room price per room type in each country.

If you want to pivot by date be sure to choose your granularity at the top right.

So there you have it. The table widget is powerful. It can display a lot of information on both the simple table and the pivot table versions and can be tailored to illustrate the point you are emphasizing.

The table widget can be sorted by the two chosen variables by clicking on them.