DataFrame: Difference between revisions

DataFrame (view source)

721 bytes added , 21 February 2023

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 ==Explain Like I'm 5 (ELI5)==
-Imagine you have a large box full of toys, and you want to organize them, so it is easier to locate the toy you want to play with. A DataFrame box with distinct compartments is the ideal solution; it helps organize different types of toys in distinct compartments for quick retrieval.
+DataFrames are like large tables with rows and columns for storing data - just like a spreadsheet does.
+Imagine organizing your toy collection and having a list of all your toys. Each row in the list has the name, type of toy it is and how much it costs. This is similar to DataFrame with each row representing a toy and each column providing different information about it.
+Machine learning uses DataFrames to store the information needed to teach a computer how to do something. For instance, we might have a DataFrame with information about different flower types; each row contains details such as their color, size and shape. This helps the computer learn how to distinguish different flowers based on characteristics like these.
+By storing data in a DataFrame, we can easily access and analyze it to teach the computer how to make accurate predictions. It's like keeping all your toys organized on a list so you can quickly locate what you need while viewing all relevant details about each toy.
 [[Category:Terms]] [[Category:Machine learning terms]]