Nobody likes doing routine repeatable tasks. Well, maybe somebody does, but it is definitely not a common trait for anal

This produces neat-looking avatar stacks built using Tailwind. These common avatar stacks are found in many alleys of the internet. I’m sure you’ve seen them before somewhere already — why not create your own?

If this article gets some traction, I plan to publish a few more stories sharing (as much as I am allowed to) some useful details and pieces of code for particular examples I’ve been working on at Bain.

The Black community’s dining issues will improve when both our percentages of diners and premium eateries are competitive to our race counterparts — a much larger elephant to mount. In the meantime, the Black restaurateur and patron each must take a look in the mirror. The owner must be clear on what setting they are offering their people. There’s absolutely nothing wrong with a customer being made to feel at home. It is the establishment’s responsibility to make clear whether the vibe is the customer’s living room or dining area. It’s the customer’s job to read the room. Also to adhere to the vision of a Black business (even if said vision is still a bit blurry). The last thing it needs is public defacement at the hands of its base. That makes for one less Black business and more Black dollars into other culture’s communities to not be returned. So let’s not shoot ourselves in the foot. In fact, when in any dining area, best to keep both feet off the furniture. And for heaven’s sake, tip like an adult.

The list can go on and on, but the point is that instead of doing the same task several times (maybe even doing it manually each time), we develop a robust, reusable pipeline. It can be used by ourselves in the future or handed over to our colleagues (obviously, if they know Python). Moreover, Python script is usually transparent and readable if created properly, so it should be easy for our colleagues or supervisors to go through each step of our analysis and get what is going on there. That is a great advantage compared to Excel, as Excel does not allow us to see all these intermediate steps.

It happened many times in my practice when I simply needed to draw some charts based on such large databases as ticket sales distribution, customer information, SKU data, and so on. It was crucial to show the full picture instead of some sample, so Big Data-processing skills were necessary.

That’s the most exciting part for me, but the least often used, to be honest. Nevertheless, sometimes it could be quite important for success. The underlying reason is the same as for the previous argument — corporations have data and want insights. Some of these insights could not be uncovered without machine learning, as they are too complex to be manually found by human analysts. Some tasks of this type I have been doing:

If you want to know about the gendered domestic divide in American households, there are plenty of books to read, studies to peruse, and women’s stories — exponentially more of them since the pandemic started — to hear out. But the most fascinating look at inequality at home, and within heterosexual relationships more broadly, doesn’t come from traditional sources; it’s hiding in plain sight, on a Reddit forum called “Am I The Asshole.”

Here I am talking not only about the traditional definition of Big Data (3 Vs) but also about any data too big to fit into Excel (over ~1 mln rows). This is something that I also have encountered a lot. The majority of large corporations (not only digitally-advanced ones) have already generated enough data to call it “Big”, and they predictably want to get insights from this data. So when traditional business analysts are unable to do it, these corporations turn to data scientists for answers. I understand that some of these questions may be extremely complicated and indeed require the data specialists’ involvement, but is it always the case? I believe that it’s not. Sometimes the task is as easy as to open a few 5Gb datasets, merge them, make some pivots, and draw the slides/ charts on their base. Of course, it may sound like a problem if you only know how to use Excel, but if you are a Python-user, you would have easily cracked this task and saved some money and time for your organization.

What concerned me about Kelly’s TMZ statement is him saying he’s mindful of how both women and his race are perceived when patrons twerk. He also said a woman devalues herself whenever she twerks. First off, WTF?! Second, the respectability of his male customers shouldn’t depend on whether or not women dance. Kelley needs to hold men to a higher standard. Furthermore, it appears that he’s mostly concerned with the optics of twerking from an outsider’s lens. “How we all look as a people,” eludes to him being embarrassed by the potential of outsider judgement towards African-American women twerking. As if the dance is a dirty action that should be kept confined to segregated Black circles — at the very least, hidden from customers of other races. Being ashamed of your culture is a deeper psychological issue. That’s the White gaze Toni Morrison spoke so fiercely on.

The Black community’s dining issues will improve when both our percentages of diners and premium eateries are competitive to our race counterparts — a much larger elephant to mount. In the meantime, the Black restaurateur and patron each must take a look in the mirror. The owner must be clear on what setting they are offering their people. There’s absolutely nothing wrong with a customer being made to feel at home. It is the establishment’s responsibility to make clear whether the vibe is the customer’s living room or dining area. It’s the customer’s job to read the room. Also to adhere to the vision of a Black business (even if said vision is still a bit blurry). The last thing it needs is public defacement at the hands of its base. That makes for one less Black business and more Black dollars into other culture’s communities to not be returned. So let’s not shoot ourselves in the foot. In fact, when in any dining area, best to keep both feet off the furniture. And for heaven’s sake, tip like an adult.

On a closing remark, one of the things I love about Python is its open-source principles. There is a wide community of professionals who openly share their ideas and groundwork, help others, and create some great projects together. This idea was confusing for me at first as for a person from the traditional corporate world, but later I have realized its enormous potential. That is why I am trying to motivate people to learn Python and join this great community.

Could these tasks be solved in Excel using linear regression? Well, with some degree of creativity, maybe…but I will not be sure about the quality of such work. More advanced modeling in Python will certainly give us higher flexibility and very likely better results.

Become proficient at understanding 3D modeling and 3D physics for the animations — You’ll need the latter to understand how to create smooth transitions for the flame that feel intuitive.

If this article gets some traction, I plan to publish a few more stories sharing (as much as I am allowed to) some useful details and pieces of code for particular examples I’ve been working on at Bain.

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on that thinks a bit of jealousy is fine in a relationship. I don’t mean the over the top, “you can’t ever hang out with that person you’ve known for 20 years because you might sleep with them” jealousy. But a subtle riling up in the chest is fine as long as it doesn’t manifest into make-believe thoughts.