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# DataFrame for Pharo [![Build Status](https://travis-ci.org/PolyMathOrg/DataFrame.svg?branch=master)](https://travis-ci.org/PolyMathOrg/DataFrame) [![Build status](https://ci.appveyor.com/api/projects/status/1wdnjvmlxfbml8qo?svg=true)](https://ci.appveyor.com/project/olekscode/dataframe)
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# DataFrame for Pharo [![Build Status](https://travis-ci.org/PolyMathOrg/DataFrame.svg?branch=master)](https://travis-ci.org/PolyMathOrg/DataFrame) [![Build status](https://ci.appveyor.com/api/projects/status/1wdnjvmlxfbml8qo?svg=true)](https://ci.appveyor.com/project/olekscode/dataframe)[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://raw.githubusercontent.com/PolyMathOrg/DataFrame/master/LICENSE)
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In Smalltalk despite the fact that many important analysis tools are already present (for example, in the [PolyMath](https://github.com/PolyMathOrg/PolyMath) library), we are still missing this essential part of the data science toolkit. These specialized data structures for tabular data sets can 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.
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