Even therapy seemed like too much effort. I had been going every week, and on one particular day, I didn’t have much to

In academia, there is a great emphasis on Python with regard to data science. Professors and instructors teach how to leverage Python libraries such as NumPy, Pandas, and Scikit-learn to make sense of data.

A few days later, I folded my laundry and put my clothes wherever the fuck they fit. As I reveled in my newfound freedom, I stopped seeing each day as a series of arbitrary rules to follow. Eventually, I felt free enough to set goals again, on my own terms.

Unfortunately, this task exceeds Python capabilities, and here when SQL (Structured Query Language) comes to play. That is why, understandably, SQL is present in almost all data science-related job posts. For example, roles as a data analyst, business analyst, and data scientist.

A few days later, I folded my laundry and put my clothes wherever the fuck they fit. As I reveled in my newfound freedom, I stopped seeing each day as a series of arbitrary rules to follow. Eventually, I felt free enough to set goals again, on my own terms.

The top of the list was dominated by web development languages such as Javascript, HTML/CSS with 69.7%, 62.4% respectively. Right below lies SQL with a strong 56.9%. Then on the 4th rank stands Python with 41.6% which is roughly 15% less than SQL.

I felt like an idiot just saying it out loud. What kind of grown-ass adult is undone by a stack of dishes? There are people out there with actual problems, and I’m whining to my therapist about a basic household chore?

When our son was only a few weeks old, my husband let slip that he no longer wants any more children. I admit I brushed this off a little as it was in the early days, and I thought he might need to adjust.

While Python alone is sufficient to apply data science in some cases, unfortunately, in the corporate world, it is just a piece of the puzzle for businesses to process their large volume of data.

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tle minutiae, the tiny steps, you lock into the present moment for a length of time you can handle, no matter how small. Then, you do it the next day. Get a streak going — a week, two weeks, a month, 90 days. Next thing you know, a year has passed and you’re well on your way.

“Honestly?” I said. “The dishes. It’s stupid, I know, but the more I look at them, the more I can’t do them because I’ll have to scrub them before I put them in the dishwasher, because my dishwasher sucks, and I just can’t stand to scrub the dishes.”

Not satisfied with my answer, he said, “No, what exactly are you worried about right now? What feels overwhelming? When you go home today, what issue will be staring at you?”

SQL again is even more popular among professionals than Python. The results of the latest 2020 StackOverflow survey conducted with the participation of 47,184 professional developer on the most important coding languages was concluded with the following:

It is true that data science jobs mushroomed. But at the same time, landing a decent position in this field remains notoriously challenging especially for novices. This is because of the subtle difference between data science in theory and real-life data science that is correlated with the problems businesses deal with on a day-to-day basis.

Obviously, being a parent is hard, and I find it incredibly challenging sometimes, but I genuinely love being a mom. We always said we’d have lots of kids, and that’s something I still want.

First, online courses on SQL are scarce compared to those on Python. For example, Edx produces 31 courses when typing the word “SQL” in the search bar unlike “Python” which yields 94.