1 / 21

Octave

Using Open Source Software for SWMP Data Analysis. Octave. TTW 2014 : Michelle Cordrey. +. Easy to use for exploratory statistics Great graphics packages ( ggplot ) Helpful community For some is more intuitive than other options Cross disciplinary and very high quality packages

hye
Download Presentation

Octave

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. Using Open Source Softwarefor SWMP Data Analysis Octave TTW 2014 : Michelle Cordrey

  2. + • Easy to use for exploratory statistics • Great graphics packages (ggplot) • Helpful community • For some is more intuitive than other options • Cross disciplinary and very high quality packages • Many packages (>5000 in CRAN) • Rstudio – GUI interactive environment which makes working in R much easier for newcomers to programming

  3. Python • Relatively easy to learn • Popular – many users / help resources • “Real” Language** • Scientific computing packages – NumPy, SciPy, Pandas • Many different ways to work with in excel, arcmap, IDEs , console, ipython

  4. + • The number of packages needed to work with scientific data is daunting: SciPy , NumPy, Pandas, matplotlib etc… • Install a complete solution such as Anaconda To get all necessary pkgs and nice IDE and interactive environments Other option for complete python sci data solution:

  5. 15 minute analysis:simple examples Owl

  6. 15 minute analysis: R simple example

  7. 15 minute analysis: R simple example

  8. 15 minute analysis: R simple example

  9. 15 minute analysis: R simple example

  10. 15 minute analysis: Python example

  11. 15 minute analysis: Python example

  12. 15 minute analysis: Python example

  13. 15 minute analysis: Python example

  14. Resources • Python • Install Anaonda: https://store.continuum.io/cshop/anaconda/ • R • Install R: http://cran.r-project.org • Install Rstudio: http://www.rstudio.com All code used in the will be at: http://trnerr.org/opensourcetools/

More Related