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Oleksandr Zaytsev edited this page Jan 10, 2018
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Data frames are the essential part of the data science toolkit. They are the specialized data structures for tabular data sets that provide us with a simple and powerful API for summarizing, cleaning, and manipulating a wealth of data sources that are currently cumbersome to use. The DataFrame and DataSeries collections, stored in this repository, are specifically designed for working with structured data.
DataFrame library consists of two primary data structures:
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DataFrame
is a spreadsheet-like tabular data structure that works like a relational database by providing the API for querying the data. Each row represents an observation, and every column is a feature. Both rows and columns of a data frame have names (keys) by which they can be accessed. -
DataSeries
is an array-like data structure used for working with specific rows or columns of a data frame. It has a name and contains an array of data mapped to a corresponding array of keys. DataSeries is a SequenceableCollection that combines the properties of an Array and a Dictionary, while extending the functionality of both by providing advanced messages for working with data, such as statistical summaries, visualizations etc.