1 / 3

Python Lab Pandas - III

Python Lab Pandas - III. Proteomics Informatics, Spring 2014 Week 11 11 th Apr, 2014 Himanshu.Grover@nyumc.org. Data Aggregation, Transformations & Other Manipulations. Part of most dat a analysis workflows Categorize data into groups, according to keys

stian
Download Presentation

Python Lab Pandas - III

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Python LabPandas - III Proteomics Informatics, Spring 2014 Week 11 11thApr, 2014 Himanshu.Grover@nyumc.org

  2. Data Aggregation, Transformations & Other Manipulations • Part of most data analysis workflows • Categorize data into groups, according to keys • Apply an operation to each group. For ex. • within group means/StDev etc. • within group normalizations, or other transformations etc. • Group-wise modeling (regression etc.)

  3. Pandas’ “groupby” Mechanics:Split-Apply-Combine • Split Pandas objects into pieces (groupby) • Apply: • Compute group statistics • Apply functions group-wise to columns (aggregate, transform) • Other, more generic manipulations (apply) From “Python for Data Analysis”, Chapter 9

More Related