4. How does n8n handle data?
Understanding JSON and lists is essential to building effective workflows in n8n.
Understanding n8n's data structures: JSON and lists
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📊 In the fourth video of the n8n beginner course , we look at how data is transferred between data nodes and the nodes , highlighting the importance of these concepts for creating effective workflows.
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🔑 The two main data structures are JSON, which consists of key-value pairs enclosed in curly brackets, and lists, which are collections of objects enclosed in square brackets .
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🔄 JSON can be embedded within other JSON, allowing for complex data structures, such as grouping individual location information in this example .
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📅 Each node processes the input data one item at a time and is executed once per item, which is very important for building workflows. For example, the Date Formatting node reads and returns a formatted date for each input item .
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📈 When working with JSON lists, each JSON corresponds to a row in a table , with keys acting as column headers, making it easier to visualize the data structure.
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🛠️ Nodes use expressions to filter and manipulate data, so they can be configured dynamically based on input, such as only allowing items with a certain name to pass through .
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💻 This video also shows how to use JavaScript within expressions to modify data types, such as converting the last name to uppercase in a first name field .
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🔍 At the end of this session, I encourage viewers to revisit this video and review the explanations of items, lists, and JSON , as familiarizing themselves with these concepts is essential to building effective workflows in n8n.
LiveWiki, the key content on YouTube in 10 seconds! - https://livewiki.com/ko/content/n8n-beginner-course-data-handling
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This video explains the types of data used in nodes and how data is passed between nodes.
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Describes two main data structures: JSON and lists.
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JSON is a data format written in curly brackets and consisting of key-value pairs, while a list is a collection of objects written in square brackets.
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JSON can be nested, making it useful for structuring complex data.
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An example explanation of JSON and lists.
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Explains how to access data using JSON's dot notation.
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Lists can contain JSON and can be used in a similar way to table format.
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Explaining the correlation between JSON and tables: One JSON corresponds to one row in a table.
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In n8n, data is processed in the form of items, and nodes use item lists as input and output.
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A node processes each item one by one, executing once for each item.
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Example: A node that formats dates and times processes each input entry and returns the formatted result.
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Describes how nodes process data.
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It may also return an empty JSON while running, as illustrated by an example of reading data from a Google Sheet.
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Describes the process of using a filter node to select only items that satisfy a condition.
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When setting a filter, you can use expressions to filter based on specific conditions.
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How to use expressions: You can use specific key values in JSON data as filter conditions.
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As an example, how to filter only items with the name "Emily" in the first item.
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You can use JavaScript functions or methods in expressions, combine multiple expressions, or add plain text.
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Example: How to send a message to Slack that combines a name and email.
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A practical example of using expressions in n8n.
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Shows how to set up a node that combines the first and last name to create a full name.
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Added example of a JavaScript function that converts the last name to uppercase.
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To conclude the video, he teases that in the next video, he will be building an actual workflow.
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It is important to review and understand the concepts of data structures, items, JSON, and lists.