What cool stuff can I do with the data from my mood tracking app?
September 14, 2018 7:36 AM   Subscribe

I use Mood Log to track my feelings, and have 2 years of data. The app allows you to export to a CSV file with columns for Date, Time, Mood (a number from 1 to 10), Tags (which is a list of adjectives separated by commas for each entry) and Notes. How can I garner insights from this data, like what days or months I am most or least happy? I have average proficiency in Excel and am willing to consider a use a paid service if one exists.
posted by ITheCosmos to Computers & Internet (10 answers total) 11 users marked this as a favorite
 
Response by poster: I'm interested both in ways to technically do this, and in interesting insights I might want to try looking for in this data. Thanks!
posted by ITheCosmos at 7:44 AM on September 14, 2018


The first one that comes to mind is local weather data. Also available in CSV/Excel, so should be fairly easy to add. Air quality info would also be interesting. If you also track your exercise in any way, that info would be a good fit.

... And, uh, given the last two years, might be illuminating to add What the Fuck Just Happened Today? summaries if that seems relevant to you, though that might not be quite as quick to extract all in one go.
posted by asperity at 8:39 AM on September 14, 2018 [3 favorites]


How can I garner insights from this data, like what days or months I am most or least happy?

For those specific queries: add a Day column with a formula like =WEEKDAY(A2), and a Month column with a formula like =MONTH(A2) (assuming your dates are in column A). Then you can do an X-Y scatterplot chart of Day vs Mood, and another of Month vs Mood, and look for clusters.
posted by flabdablet at 9:04 AM on September 14, 2018 [3 favorites]


If you are a person who has a menstrual cycle, you can correlate with that. Also birthdays, anniversaries of significant life events, and holidays.
posted by matildaben at 11:12 AM on September 14, 2018 [2 favorites]


Seconding that, if physically relevant, tracking mood to menstrual cycle can be fascinating.

Consider downloading data and cross-checking your mood against:
- average daily outdoor temperature / pressure / humidity
- phases of the moon
- the dates of major news stories in 2018

On a personal level, track against
- major work/personal deadlines
- travel dates
- if you had visitors / family in town
- major illnesses
- big life changes such as job change, moving or loss
posted by samthemander at 1:35 PM on September 14, 2018 [3 favorites]


Have you started with the basics like creating separate histograms based on just single factors like individual tags, times of day, days of week and so forth? If you're looking for real trends, trying to determine distributions based on the simplest of factors is a good place to start because you'll have the most data for them.
posted by Cogito at 6:09 PM on September 14, 2018


My first stop would be the basics - chart mood against date, day of the week, and time of day, and see if there are any noticeable patterns. That should all be easy enough to do with Excel's built-in charts. Seeing if there's a correlation between mood and tags would be fun too.

Another fun thing to play with if your city releases open data sets would be to track your mood against things like the number of tickets issued in a day or the number of traffic accidents or street closures.
posted by Basil Stag Hare at 6:24 PM on September 14, 2018 [1 favorite]


Response by poster: Whoa, thanks for all the great ideas! I track menstrual cycle info in Clue, but unfortunately, while you can export a backup of your data, it doesn't output into a format that allows you to open it up and poke around.
posted by ITheCosmos at 5:49 AM on September 15, 2018


I assume if you have Excel you are Windows-capable? Maybe download the free (desktop) version of PowerBI from MSoft and have a play - it does great visuals and will happily use a spreadsheet as a source.
posted by Ilira at 1:47 PM on September 15, 2018


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posted by Little Dawn at 9:48 PM on September 15, 2018


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