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{{see also|Machine learning terms}} | |||
==Introduction== | ==Introduction== | ||
[[Data]] is the backbone of [[machine learning models]]. To effectively work with data, it must be organized and formatted for analysis - which is where [[DataFrame]]s come into play. A [[DataFrame]] is a two-dimensional table-like data structure where rows and columns of information are organized. It's an essential concept in [[data analysis]] and widely employed in machine learning applications. | [[Data]] is the backbone of [[machine learning models]]. To effectively work with data, it must be organized and formatted for analysis - which is where [[DataFrame]]s come into play. A [[DataFrame]] is a two-dimensional table-like data structure where rows and columns of information are organized. It's an essential concept in [[data analysis]] and widely employed in machine learning applications. | ||
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==Explain Like I'm 5 (ELI5)== | ==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. | 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. | ||
[[Category:Terms]] [[Category:Machine learning terms]] |