Python Open Labs – Session 6

Hi

In the 6th session of Python Open Labs, today we covered the concepts on comparison operators, logical operations and complex logical expressions. If you attended today’s session, I encourage you all to try out the practice problems from the slides on the google drive link given below.

Python Open Labs Slides: https://goo.gl/YP0c2E

Tip of the day: Practise! Practise! Practise!  (It’s one thing that remains constant)

Hope to see you next Friday, 11:00 AM at DSSC

R Open Labs – Time Series Analysis (contd)

This Wednesday we continued to talk about some broad ideas of time series analysis. We explored seasonal trend decomposition, which can be used to show the seasonal fluctuation and main trend of the dataset.

It’s a very involved topic, so thank you and a round of applause to everyone who showed up today. Next week we would talk about something much less complicated.

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See you next Wednesday 11/09/2016 10:00-12:00 at DSSC!

Map Club — Dynamic Mapping with OpenLayers

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The latest session of Map Club focused on OpenLayers, a high-performance library for rendering geographic information in the browser. OpenLayers enables users to visualize a diverse range of geospatial data formats, while offering intuitive links to external web-based mapping resources such as CARTO, OpenStreetMap, Stamen, and D3.js.

Participants explored OpenLayers functionality for importing KML and GeoJSON data, experimented with linking to different tile sets, and tried out the customizable interactive capabilities of the library in JavaScript.

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From top: imported KML data, Stamen toner labels tile set, Frank Nitsche

Next week will be the second guided workshop of the semester. We will be digging into QGIS, a free and open source geographic information system that offers powerful tools for data editing, viewing, and analysis. Hope to see you there!

Sign up here if you would like to receive updates on future Map Club sessions. For this session’s resources and materials, visit the Map Club Github repository.

Python Open Labs – Session 5

 

 

 

 

 

Hi

Thanks for stopping by this post. In the 5th session of Python Open Labs, today we covered the concept of for loops in python along with a quick revision of concepts from the previous sessions. If you attended today’s session, I encourage you all to try out the practise problems from the slides on the google drive link given below.

Python Open Labs Slides: https://goo.gl/YP0c2E

A quick note about the course material:

  1. If you want to get set up with Python 2.7 installation on your system, check out the Session-1 slides.
  2. Practise! Practise! Practise!

Hope to see you next Friday, 11:00 AM at DSSC 🙂

Python Open Labs- Session 4

Hi everyone

In the fourth session of Python Open Labs, we covered the basics of loops and iterations. Today’s session covered the basics of using a while loop and also introduce the csv python library.

Please check out the course material on: https://goo.gl/YP0c2E

See you next week !

Survey Documentation and Analysis (SDA)

Survey Documentation and Analysis (SDA) is a web based interface that allows access and analysis of data. The data can be accessed from IPUMS or from  the Inter-university Consortium for Political and Social Research (ICPSR).

SDA allows you to:

  • Browse the codebook describing a datasetsda
  • Calculate frequencies or crosstabulation (with charts)
  • Do comparison of means
  • Calculate a correlation matrix
  • Compare correlations
  • Perform multiple regression
  • Perform logit/probit regression
  • List values of individual cases
  • Recode variables (into public work area)
  • Compute a new variable
  • List/delete derived variables
  • Download a customized subset

SDA allows you to analyze data at a level appropriate to your level of experience. SDA can only analyze datasets that reside on an SDA server. If you would like to test drive SDA, or to see if SDA is useful for your research check out their General Information page.

R Open Labs – Data Manipulation

Today we introduced merge(), factor() and some basic techniques for handling missing values during the first 30 minutes of the open lab. For the rest of the open lab, there were free discussions about personal projects the participants are working on.

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We also introduced package swirl. Swirl package teaches you R programming interactively.

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Thank you to everyone who showed up! For next session, we would explore time series analysis and car package.

 

See you next Wednesday 10/26/2016 10:00-12:00! Welcome to drop by anytime in between!