Doing some time-series style plots with it.Doing this extraction in a Jupyter/IPython notebook and saving it into a Pandas dataframe.Exporting a group chat as a CSV file, including the sender and type of message (text or attachment).So in this post I will give some basic recipes for The slick iMessage Analyzer app can handle group chats, and even allows you to export the chat as an easy-to-play-with CSV - but there is a limited menu of queries, it doesn’t differentiate between members of the chat, and it doesn’t make explicit distinction between text vs. So I thought I was in luck.īut I found that these resources tended to neglect group chats (for example this excellent tutorial or many nice Github repos like these PHP scripts). Questions like: who sends the most texts by hour, most used words, circadian rhythms, maybe some modeling … It turns out that (1) iOS archives all iMessages in a convenient SQL database on your Mac and (2) there is a ton of code out there to read and manipulate this data. I wanted to do some data science-y analysis of some group conversations I’ve been in for years over iMessage (the Apple ecosystem message app).
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