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sh_123 | 5 years ago

Can you share more about your process? I'm very interested in learning more. How do you track your daily data points?

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jvanderbot|5 years ago

I have a text file in a known location. It's backed up on git.

I can open and edit that file quickly using bash. From within VIM I can quickly commit to reduce the # keystrokes. More details: https://github.com/jodavaho/bashlog#git-integration

(Really though, you can just save as an environment variable your file location)

The text file is structured with space-delimited text, like this: https://github.com/dkogan/vnlog

My current structure for tracking a contribution to an OKR item (e.g. "meditate") by date (e.g., 2020-01-15) and amount (e.g., "1") is simply:

"# date item amount"

Easy to open, easy to plop down today's date and the item / amount. Save multiple date/item entries and add them inscripts ... Easy to save. Done.

The work came in building stuff to plot it:

I have other files that link "items" to goals or other metadata like categories, etc. Like a relational database, but easily edited in text.

For example, to make a link from daily items to Key Results

"# item okr"

The OKR categories are usually Fighting (I box), Tech, Mental health, and Social, but YMMV

Another example is "workout-mapping.vnl" with structure: "# item muscle-group factor"

etc etc.

vnlog has nice vnl-join commands that quickly build the table and all linked metadata and output formatted text (one command). Then reading that in R is easy ...

``` data <- read.table('../2020-Q4-OKR.vnl',skip=2,stringsAsFactors = FALSE) ```

Aggregating by date is easy:

``` data.agg<- aggregate(x=data$Amount,by=list(data$Date),FUN=sum) ```

Then plot using ggplot2.

Examples from 2020 Q4 (just ran the numbers yesterday!)

https://josh.vanderhook.info/media/okr.png

https://josh.vanderhook.info/media/workouts.png

https://josh.vanderhook.info/media/mood.png

thelittleone|5 years ago

Thanks for sharing. Would you consider writing a blog post on your process?