lightweight portable binary format. See the docs Warning: Since this is an EXPERIMENTAL LIBRARY, the storage format may not be stable until a future release. 28 Chapter 1. What’s New pandas: powerful Python Release 0.13.1 • SciPy: miscellaneous statistical functions • PyTables: necessary for HDF5-based storage • matplotlib: for plotting • statsmodels – Needed for parts of pandas.stats • openpyxl, xlrd/xlwt should be sent to: support@lambdafoundry.com 4.4 Credits pandas development began at AQR Capital Management in April 2008. It was open-sourced at the end of 2009. AQR continued to provide resources for development

lightweight portable binary format. See the docs Warning: Since this is an EXPERIMENTAL LIBRARY, the storage format may not be stable until a future release. In [118]: df = DataFrame(np.random.rand(5,2),columns=list(’AB’)) Release 0.14.0 • SciPy: miscellaneous statistical functions • PyTables: necessary for HDF5-based storage • SQLAlchemy: for SQL database support. Version 0.8.1 or higher recommended. • matplotlib: for should be sent to: support@lambdafoundry.com 4.4 Credits pandas development began at AQR Capital Management in April 2008. It was open-sourced at the end of 2009. AQR continued to provide resources for development

Release 0.12.0 • SciPy: miscellaneous statistical functions • PyTables: necessary for HDF5-based storage • matplotlib: for plotting • statsmodels – Needed for parts of pandas.stats • openpyxl, xlrd/xlwt should be sent to: support@lambdafoundry.com 4.4 Credits pandas development began at AQR Capital Management in April 2008. It was open-sourced at the end of 2009. AQR continued to provide resources for development Foundry, Inc. and PyData Development Team All rights reserved. Copyright (c) 2008-2011 AQR Capital Management, LLC All rights reserved. Redistribution and use in source and binary forms, with or without modification

S3 (GH11070, GH11072). • In pd.read_csv, recognize s3n:// and s3a:// URLs as designating S3 file storage (GH11070, GH11071). • Read CSV files from AWS S3 incrementally, instead of first downloading the (GH11070, GH11073) • pd.read_csv is now able to infer compression type for files read from AWS S3 storage (GH11070, GH11074). 1.1. v0.17.0 (October 9, 2015) 15 pandas: powerful Python data analysis toolkit This is a container around a Categorical (introduced in v0.15.0) and allows efficient indexing and storage of an index with a large number of duplicated elements. Prior to 0.16.1, setting the index of a DataFrame/Series

lightweight portable binary format. See the docs Warning: Since this is an EXPERIMENTAL LIBRARY, the storage format may not be stable until a future release. In [118]: df = DataFrame(np.random.rand(5,2),columns=list(’AB’)) 1 or higher. • SciPy: miscellaneous statistical functions • PyTables: necessary for HDF5-based storage. Version 3.0.0 or higher required. • SQLAlchemy: for SQL database support. Version 0.8.1 or higher should be sent to: support@lambdafoundry.com 4.4 Credits pandas development began at AQR Capital Management in April 2008. It was open-sourced at the end of 2009. AQR continued to provide resources for development

lightweight portable binary format. See the docs Warning: Since this is an EXPERIMENTAL LIBRARY, the storage format may not be stable until a future release. In [118]: df = DataFrame(np.random.rand(5,2),columns=list(’AB’)) 1 or higher. • SciPy: miscellaneous statistical functions • PyTables: necessary for HDF5-based storage. Version 3.0.0 or higher required. • SQLAlchemy: for SQL database support. Version 0.8.1 or higher should be sent to: support@lambdafoundry.com 4.4 Credits pandas development began at AQR Capital Management in April 2008. It was open-sourced at the end of 2009. AQR continued to provide resources for development

dependencies • SciPy: miscellaneous statistical functions • PyTables: necessary for HDF5-based storage • matplotlib: for plotting • scikits.statsmodels – Needed for parts of pandas.stats • pytz – should be sent to: support@lambdafoundry.com 4.4 Credits pandas development began at AQR Capital Management in April 2008. It was open-sourced at the end of 2009. AQR continued to provide resources for development Foundry, Inc. and PyData Development Team All rights reserved. Copyright (c) 2008-2011 AQR Capital Management, LLC All rights reserved. Redistribution and use in source and binary forms, with or without modification

dependencies • SciPy: miscellaneous statistical functions • PyTables: necessary for HDF5-based storage • matplotlib: for plotting • scikits.statsmodels – Needed for parts of pandas.stats • pytz – should be sent to: support@lambdafoundry.com 4.4 Credits pandas development began at AQR Capital Management in April 2008. It was open-sourced at the end of 2009. AQR continued to provide resources for development Foundry, Inc. and PyData Development Team All rights reserved. Copyright (c) 2008-2011 AQR Capital Management, LLC All rights reserved. Redistribution and use in source and binary forms, with or without modification

dependencies • SciPy: miscellaneous statistical functions • PyTables: necessary for HDF5-based storage • matplotlib: for plotting • scikits.statsmodels – Needed for parts of pandas.stats • pytz – should be sent to: support@lambdafoundry.com 4.4 Credits pandas development began at AQR Capital Management in April 2008. It was open-sourced at the end of 2009. AQR continued to provide resources for development Foundry, Inc. and PyData Development Team All rights reserved. Copyright (c) 2008-2011 AQR Capital Management, LLC All rights reserved. Redistribution and use in source and binary forms, with or without modification

S3 (GH11070, GH11072). • In pd.read_csv, recognize s3n:// and s3a:// URLs as designating S3 file storage (GH11070, GH11071). • Read CSV files from AWS S3 incrementally, instead of first downloading the (GH11070, GH11073) • pd.read_csv is now able to infer compression type for files read from AWS S3 storage (GH11070, GH11074). Backwards incompatible API changes Changes to sorting API The sorting API This is a container around a Categorical (introduced in v0.15.0) and allows efficient indexing and storage of an index with a large number of duplicated elements. Prior to 0.16.1, setting the index of a DataFrame/Series