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pandas provides NumPy-based data structures and statistical tools for common time series and cross-sectional data sets. It is intended to accomplish the following: * Simplify working with possibly labeled 1, 2, and 3 dimensional heterogeneous data sets commonly found in statistics, finance, and econometrics. * Provide IO utilities for getting data in and out of pandas * Implement common statistical models with a convenient interface, handling missing data and other common problems associated with messy statistical data sets
13 lines
541 B
Text
13 lines
541 B
Text
pandas provides NumPy-based data structures and statistical tools for
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common time series and cross-sectional data sets. It is intended to
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accomplish the following:
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* Simplify working with possibly labeled 1, 2, and 3 dimensional
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heterogeneous data sets commonly found in statistics, finance, and
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econometrics.
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|
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* Provide IO utilities for getting data in and out of pandas
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|
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* Implement common statistical models with a convenient interface,
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handling missing data and other common problems associated with
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messy statistical data sets
|