Data analysts should always be skeptical of their data, because it very often goes bad. The Quartz bad data guide is a summary of the most common data flaws, from automatic Excel conversions to inappropriate use of Margins of Error.
Next week we’ll be kicking off two new data projects, and a big part of these projects will be finding data, documenting it, and preparing it in a consistent way for analysis, a process known as data wrangling. I’ve been developing software for wrangling social data for a few years, and have collected many of the best ideas into a new metadata system called Metatab. Metatab is a system for storing structured metadata in a CSV file, often alongside data, making it easier to create and publish metadata.
In the next two data projects, we will using the Metatab Google Spreadsheet Add-On to document data we locate for the two projects. Once a metatab specification is created for a dataset, it can be uploaded to CKAN, our data repository software directly from the Google spreadsheet system. And I’m currently working on other tools for finding and manipulating data.
When we are done with the main data wrangling, there will be collections of datasets in our main data repository related to food access and assisted living, and then we can start on data analysis, most likely using Pandas and Tableau, but we may also tackled using a few AWS tools like AWS Athena and AWS Quicksight.Register for the Meeting
The Library has been quiet lately, mostly because the Director doesn’t have time to properly manage projects, and because he’s not very good at it. So, we’d like to find a volunteer to manage projects. This is a volunteer role that would involve:
- Talking to nonprofits and journalists about data needs
- Recruiting other volunteers for data projects
- Setting up meetings and finding rooms
- Participating in data projects
If you are interested in data and have good organizational skills, please apply by sending email to Eric Busboom, firstname.lastname@example.org.
Collect and analyze data about the food system in San Diego county.
The San Diego Food System Alliance’s Healthy Food Access Working Group is developing an indicator library to analyze food access issues, and we need your help to locate datasets, wrangle them into useable shape, and create visualizations.
The work is similar to the topics of our March 2015 Data Contest, with additional work of building a reusable data library to perform additional analysis.
This project needs volunteers with a range of skills, including:
- Administration and logistics: Call potential data providers, locate datasets, and arrange meetings and events.
- Data wranglers: People skilled with either Excel or Python to manipulate datasets.
- Data analysts: Data analysis who know R or Python/Pandas.
We will be starting with a list of potential datasets, from which we will construct Ambry Data Bundles. We can load the bundles into a data library. Then we can do visualizations and analysis, such as this map from a project at Palomar College.
How To Participate
To announce the arrival of a new set of crime data, our next meetup will be a mini data contest, with a $100 prize for the best student analysis. In this meeting, we will present the new Crime Incident dataset and talk about how to link it to other social datasets. After the presentation, we’ll challenge you to do you own analysis, with a $100 prize for the best analysis from a student, undergraduate or lower.
Then, for the next meeting, we’ll invite the best analysts to present their findings and techniques.