Black Friday

Sunday, December 1, 2019

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I was always excited about Black Friday. The day I wake up really early to get in line at my favorite stores before they open to get the best deals of the day. Plus being super early means you get the best parking spots too! I finish 95% of my Christmas shopping on this day. But this year, for the first time in ten years, I stayed home! I got turned off at stores who started opening the evening of Thanksgiving day. I feel sorry for the workers who have to leave their families to go to work. All for more profit.

The data below shows the potential number of shoppers over the Thanksgiving weekend according to the National Retail Federation. Black Friday still shows as the most popular day to shop. Based on NRF's analysis, the top reasons consumers are planning to shop include:

1) The deals are too good to pass up (65 percent)
2) Tradition (28 percent)
3) It's when they like to start their holiday shopping (22 percent)
4) It's something to do over the holiday (21 percent)
5) It's a group activity with friends/family (17 percent)




So why did I skip the most popular day of shopping? In my experience, retail pricing have changed over the years on the items that I purchased the most - clothing, accessories and shoes. I find the sales throughout the year better than the Black Friday sales. One perfect example is Old Navy. They offered a 50% sale everything on Friday. They do this throughout the year already. Not for everything all at once, but at staggered times on different categories. They may have added an additional 10% off for early birds, but is it all worth the 5am wake up call? Driving in the dark, cold weather? Standing in long lines to checkout? I don't think so. Not anymore at least.

I've noticed the "before" pricing were purposely raised so even with a 50% discount (which sounds very appealing) looks like you are getting a deal, when in reality you are actually paying an amount very close to retail price. I know this because I've observed the pricing differences of certain items I was very interested in.

Bottomline is, shoppers are drawn to a sale. Advertising has led to the belief that Black Friday sales are the best. Perhaps for certain electronics, yes. But for regular items, you need to observe what sale you are actually getting. It really is not that great. I find the after Christmas sales are actually better if you were shopping solely for yourself.

Cyber Monday is coming up. Maybe I will browse to see some deals in my pajamas with a nice cup of coffee. Maybe I will be one of the 68.7M online shoppers. But really, the one question you should be asking yourself before buying anything is: Do I really need this??



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Where do i begin?

Tuesday, November 19, 2019

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It took me a little over four hours straight to generate an output of SEVEN lines in Python! Two lines was just plain text, three lines were computations, and another two lines was formatting the output. On top of that, the script needed to include creating a text file with the output. 

  Financial Analysis
  ----------------------------
  Total Months: 86
  Total: $38382578
  Average  Change: $-2315.12
  Greatest Increase in Profits: Feb-2012 ($1926159)
  Greatest Decrease in Profits: Sep-2013 ($-2196167)

We just wrapped up the first week of learning the language. Before starting the bootcamp, I spent a good amount of time learning the basics of Python through online courses, YouTube tutorials, and web articles. I have a degree in Computer Science so picking up the concepts wasn't too difficult. But for someone who has absolutely no STEM background, I would understand how challenging it can get to grasp so much information in so little time. So I was asked, "Where do I begin?".

I am a complete beginner to Python as well and below are the steps I did to perform the task:

1) Know the basics. I've already done so as I mentioned above. There are so many free resources online. One YouTube channel I particularly liked was: CS Dojo. The Python Tutorial documentation is a good one. You can also try courses on Udacity or Codecademy for hands-on learning. The Coding Bat site is great practice! These are just a few of hundreds of resources online. 

2) Solve the problem one line at a time. The text output was pretty straightforward. To do the computations, I did the next step.

3) The data source only contained two columns and about 270 rows. So I used Excel to solve the computational problems to make sure I am getting the correct solution. Obviously, if the data set was too large this would not be possible. But since this is a beginner assignment I took the Excel route. Now that I have the correct solution, next step was how to convert that into Python code.

4) For the most part, I used lists and list comprehension. I knew what I wanted to do, but I didn't have the knowledge yet on what functions existed (if there were any) to get a specific output. So if there is something you do not know, Google or Stack Overflow is your best friend. If you ask the right questions, you will find what you are looking for. And to know the right questions, you will have known what it is you specifically want to happen. 

The four hours was time well spent, my Python knowledge just increased. Assignment number one is done! I continue to try to improve my script so off to code some more.



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Kickstart your chart

Saturday, November 16, 2019

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Over $2 billion has been raised using the massively successful crowdfunding service, Kickstarter, but not every project has found success. Of the more than 300,000 projects launched on Kickstarter, only a third have made it through the funding process with a positive outcome.

Getting funded on Kickstarter requires meeting or exceeding the project's initial goal, so many organizations spend months looking through past projects in an attempt to discover some trick for finding success.

Based on a database of 4,000 past projects between 2009 to 2017, the two charts below (using Microsoft Excel) shows a count of how many campaigns were successful, failed, canceled, or are currently live.

Let's focus on the labeling, which do you think is more effective to your audience?

The Horizontal Bar Chart:

The Vertical Bar Chart:



Did you tilt your head to the left to read the labels on the bottom on the second image? Can you imagine your audience suddenly tilting their heads as soon as you present this data? That would be a funny sight. The horizontal bar chart on the other hand is a lot easier to read. This chart is especially useful if the category names are long such as those above. The text is written from left to right, as most people read, making the graph more legible for your audience. By the time they get to the data, they already know what it represents. I've also decluttered the chart by removing the border.

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