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DataFrame: Difference between revisions
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==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 | [[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. | ||
==Pandas Dataframe== | |||
Dataframe is a popular [[pandas]] [[datatype]] to represent [[datasets]] in memory. A DataFrame can be thought of as a table or spreadsheet. Each column of a DataFrame has a name (a header), and each row is identified by a unique number. A Dataframe column in structured as a 2D array and each column can have its own data type. | |||
==Definition== | ==Definition== | ||
DataFrame is a tabular data structure in which information is organized into rows and columns. It resembles an array, with rows representing instances or | DataFrame is a tabular data structure in which information is organized into rows and columns. It resembles an array, with rows representing instances or [[examples]] and columns representing attributes or [[features]]. Each column has a specific data type like numbers, text or dates and can be labeled with its own unique name for easy identification. The DataFrame is both flexible and powerful - capable of handling both structured and unstructured information alike. | ||
==Features== | ==Features== | ||