This article picks up from the end of Part 1: Creating a Details Extractor.
With the details extractor we created, we might want to go back in and add hidden values or clean up other values within Import.io before getting our data output.
You can click Edit to get back to the Edit view of an extractor.
After adding more columns, you can add find values that might be originally by turning off the styling of a page. To this, go to the cog in the top right and disable CSS. The styling can be turned back on by re-enabling CSS.
Training with Additional URLs
To ensure that your extractor is trained to capture data properly from a source, you can train with additional URLs to add one or more pages to train against. For this example, we'll add https://www.yelp.com/biz/los-gatos-coffee-roasting-company-los-gatos to the training to ensure our extractor works for other businesses. Select the settings for the data panel and select Edit inputs/variables. Select the + symbol to add an input and train to load that source into the extractor. The extractor will now use both pages to understand which data point that you are selecting.
Besides adding data columns, you can edit existing data columns as well. Clicking the drop-down arrow next to a column name will reveal the column setting menu.
From the column settings, you can use Set regular expression to match and filter out a string. For example, try selecting all of the text string under "More business info". Then go to Set regular expression and set Match to Google Pay\s+(.+) and Replace to $1. This will match on the string that contains Android Pay and then output the Yes or No value in the data column. We can then use Duplicate column and change the Match to Apple Pay\s+(.+) to create a separate column for Apple Pay.
Before saving the extractor, you can drag-and-drop the data columns to rearrange the order. Once you are done, click the Save Data button and save your updates by clicking Save and run or Save only.
Now with the details extractor finished, you will want to move on to Part 3: Creating a Listings Extractor.