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#CSV

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A comma-separated values (CSV) file is a delimited text file that uses a comma to separate values. Each line of the file is a data record. Each record consists of one or more fields, separated by commas. The use of the comma as a field separator is the source of the name for this file format. A CSV file typically stores tabular data (numbers and text) in plain text, in which case each line will have the same number of fields.

In recent versions of IRIS, a powerful new data loading command has been introduced to SQL: LOAD DATA. This feature has been highly optimized to import data into IRIS extremely fast, allowing hundreds of gigabytes of data to be inserted in seconds instead of hours or days.

This is a very exciting improvement. However, a big problem in the data loading experience still exists. Namely, the time and hassle it takes to:

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We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.

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We have JSON type data in a Dynamic Object. Is there a simple way to export / dump that data to a delimited string or file?

e.g.

Results={"ClassA":{"ClassName":"ClassA","ACount":367191880,"BCount":367191880,"CurrentDiff":0,"PreviousDiff":0,"ReportDate":"2024-03-02 00:00:00"}
"ClassB":{"ClassName":"ClassB","ACount":5352149227,"BCount":5352149227,"CurrentDiff":0,"PreviousDiff":0,"ReportDate":"2024-03-02 00:00:00"}}

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