I thought the graffiti look was appealing and adds a bit of energy to the icon.
Monthly Archives: November 2013
I have developed a first version of computer-assisted qualitative data analysis software called PyQDA. The software is free to use, open source and is available from GitHub.
PyQDA uses the same database format as used by the R software RQDA, allowing you to open your RQDA projects in PyQDA, and vice versa.
What is qualitative data analysis?
It is a research technique to help answer questions of how and why, to be able to understand and interpret various points of view. Data typically comes from subject interviews, focus groups, observations of situations and survey responses. Data may be written, audio-taped or video-recorded.
Data is assigned codes which label concepts of interest. Codes can then be grouped into categories. Reading and re-reading the data in the context of the coding schemes you use allows you to get a better understanding of the issues involved. This understanding allows themes to develop; that is an analytical interpretation of the data.
What does PyQDA offer?
PyQDA is really designed for written textual data, so video or audio recordings need to be transcribed before use. Data can be in one large file or in many separate files; for example one file per subject interview. Codes can be assigned to the text and codes can be assigned to one or more categories. Categories cannot be assigned to higher or lower categories.
Memos can be assigned to files and codes to help with the interpretative process. Journals can record your thoughts as you proceed with your analysis.
Cases usually representing individual interview can be assigned to text within files and to whole files. Cases can have attributes such as age and gender to allow for improved interpretation.
Several reports can be produced including network visualization of codes and categories, frequencies of codes and selection of coded text using a range of selection options.