Combating perfectionism: An unexpected data science project
By: Morgan Kelley
Tags: Naturallanguageprocessing, Python, Data Science, Perfectionism, Machine Vision

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Combating perfectionism: An unexpected data science project

A few months ago a potential relationship I was excited about ended. I had feelings of being judged too quickly and the sadness of what might have been. In the hours following, I kept replaying our last conversations in my head and wondering what I might have done or said differently. The perfectionist in me needed all the answers and I also had to find the perfect way to “treat yo self,” as the kids say.

I’ve spent most of my life being a perfectionist, and self-care is no different. I typically go through the mental checklist of all the things people do: calling a friend, doing yoga, crafting, watching TV, etc. I spend hours analyzing the potential benefits of each, and by the time I pick something it is a chore. Decisions are impossible when they carry the weight of being “right” 100% of the time.

What I’ve been failing to do all this time is very simple: I haven’t been considering what it is I actually want to do before passing judgement on if it is “good enough.”

A few months ago when I stopped to consider what I truly wanted to do for the night, it was to watch home videos. Reasons quickly popped in my head about why I shouldn’t watch them: “I should save them for when I really need them,” “if people knew they would think it was weird,” “I don’t need this, it is self-pitying,” and “I will be sad because some people in those videos have died.” I thought of what I might say to a friend if they wanted to watch home videos, and it certainly wasn’t what I was saying to myself. I wrote down a response to every reason why I thought I shouldn’t watch the videos, and then I watched them. It felt great. I laughed and cried, and once I had my fill, I went to bed.

In the 30 days following that night, I journaled about doing at least one thing I really wanted to do that day. I wrote down what I did, what inspired it, why I didn’t do it before, and how it felt. I also took a picture of whatever it was. For efficiency and because I love data, I experimented with some natural language processing and basic computer vision, two areas I previously had no experience in.

To analyze the pictures I took over the 30 days, I generated a histogram (created with OpenCV) detailing the number of red, green, and blue pixels at each intensity. I’ve put callouts on the plot using knowledge of what I did to explain the peaks shown at various intensities for each color. By and large, what I chose to do was outside and most frequently in the early morning or evening hours. Given the excellent fall weather and my full-time PhD schedule, this checks out.

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To further explore what I chose to do, I’ve also analyzed the text directly. I used Python to sort and standardize my journal entries and the Wordcloud package to visualize them. The figure below summarizes what I did each day.

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Something I repeatedly chose to do was write. In the 30-day timespan, I wrote over 18,000 words. A common reason I told myself I shouldn’t write was that whatever I wrote wouldn’t be good, or conversely, that I would want to share it and risk rejection. The second most frequent thing I did was read, setting aside the fear of judgement for what or how often I was reading. I read books I’d been avoiding out of fear, and I read books for fun. I finished the reading list I’ve had for months, substituting my free time I normally spend aimlessly scrolling social media or watching TV with something fulfilling.

If I look holistically at the reasons why I thought I shouldn’t do things, the most common words were heavily related to fears of judgement:

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Looking at the word cloud above, I can almost read out perfectly: “People will think I’m weird,” which is a huge fear of mine. I also had fears of feeling sad if I didn’t pick the right thing, or of looking back when I felt I should be looking forward (as in the case with the home videos).

This whole thing started out as self-care, but quickly evolved into something more. When I began, my fear of being rejected or judged was so strong it was keeping me from doing very basic things like eating lunch in the park or skipping nightly TV to write. My fear of being judged was also keeping me from doing big things, like sharing my struggles with chronic illness on social media, or having difficult conversations with friends and family. I found that once I started leaning into the small things I was afraid to do, the big things seemed approachable.

What I set out to do was very simple, and for me, it made a huge difference. Doing what I want to do without imposing judgement or over-analyzing has made me a significantly happier and more grounded person. I’m more productive and focused than I was before. I’m also more decisive than I was even a few months ago. I’m less focused on analyzing and controlling all possible outcomes and more focused on the connection between want and action.

I’ve still got work to do, but investing free time in things I actually want to do made a much larger impact than I anticipated. I’m also willing to acknowledge the irony in me trying to combat my perfectionism but then turning around and making a data science project out of my journals. At least my need for information evolved into something fun and productive.

If you would like access to the code used to do the analysis seen here (and some additional analysis I didn’t include), it is available on my GitHub.