functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 766 2.18 Group by: split-apply-combine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 781 2.18.3 Selecting a group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 782 2.18.4 Aggregation convenient data handling functionalities similar to pandas. Learn more Already familiar to SELECT, GROUP BY, JOIN, etc.? Most of these SQL manipulations do have equivalents in pandas. Learn more The data

functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 737 2.18 Group by: split-apply-combine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 751 2.18.3 Selecting a group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 752 2.18.4 Aggregation convenient data handling functionalities similar to pandas. Learn more Already familiar to SELECT, GROUP BY, JOIN, etc.? Most of these SQL manipulations do have equivalents in pandas. Learn more The data

functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 767 2.18 Group by: split-apply-combine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 782 2.18.3 Selecting a group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 783 2.18.4 Aggregation convenient data handling functionalities similar to pandas. Learn more Already familiar to SELECT, GROUP BY, JOIN, etc.? Most of these SQL manipulations do have equivalents in pandas. Learn more The data

functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 772 2.18 Group by: split-apply-combine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 787 2.18.3 Selecting a group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 788 2.18.4 Aggregation convenient data handling functionalities similar to pandas. Learn more Already familiar to SELECT, GROUP BY, JOIN, etc.? Most of these SQL manipulations do have equivalents in pandas. Learn more The data

functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 772 2.18 Group by: split-apply-combine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 787 2.18.3 Selecting a group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 788 2.18.4 Aggregation convenient data handling functionalities similar to pandas. Learn more Already familiar to SELECT, GROUP BY, JOIN, etc.? Most of these SQL manipulations do have equivalents in pandas. Learn more The data

Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 760 2.2.17 Group by: split-apply-combine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 781 2.2 convenient data handling functionalities similar to pandas. Learn more Already familiar to SELECT, GROUP BY, JOIN, etc.? Most of these SQL manipulations do have equivalents in pandas. Learn more The data Series, DataFrame, etc. automatically align the data for you in computations • Powerful, flexible group by functionality to perform split-apply-combine operations on data sets, for both ag- gregating and

Series, DataFrame, etc. automatically align the data for you in computations • Powerful, flexible group by functionality to perform split-apply-combine operations on data sets, for both ag- gregating and Grouping By group by we are referring to a process involving one or more of the following steps: • Splitting the data into groups based on some criteria • Applying a function to each group independently c=a-b) df.assign(c=df.a-df.b) Grouping and summarizing R pandas summary(df) df.describe() gdf <- group_by(df, col1) gdf = df.groupby('col1') summarise(gdf, avg=mean(col1, na. rm=TRUE)) df.groupby('col1')

casting rules and indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 10 Group By: split-apply-combine 125 10.1 Splitting an object into groups . . . . . . . . . . . . . . . . http://stackoverflow.com/questions/tagged/pandas Developer Mailing List: http://groups.google.com/group/pystatsmodels pandas is a Python package providing fast, flexible, and expressive data structures Series, DataFrame, etc. automatically align the data for you in computations • Powerful, flexible group by functionality to perform split-apply-combine operations on data sets, for both ag- gregating and

casting rules and indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 717 16 Group By: split-apply-combine 721 16.1 Splitting an object into groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 729 16.3 Selecting a group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 730 16 of “nuisance” columns . . . . . . . . . . . . . . . . . . . . . . . . . . 746 16.9.2 NA and NaT group handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 747 16.9.3 Grouping

casting rules and indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 748 16 Group By: split-apply-combine 751 16.1 Splitting an object into groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 759 16.3 Selecting a group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 760 16 of “nuisance” columns . . . . . . . . . . . . . . . . . . . . . . . . . . 776 16.9.2 NA and NaT group handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 777 16.9.3 Grouping