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Data Dashboard for StockX Contest

Wed, 21 Aug 2019 21:13:14 -0500

StockX Data Contest 2019

StockX Challenge is a call for data and sneakers nerds to have fun.

source: stockX

The basic idea is this: they give you a bunch of original StockX sneaker data, then you crunch the numbers and come up with the coolest, smartest, most compelling story you can tell. It can be literally anything you want. A theory, an insight, even just a really original data visualization. It could be a novel hypothesis about resale prices you’ve always wanted to test. Or maybe it’s just a beautiful chart to visualize the data. It can be on any subject – sneakers, brands, buyers, or even StockX itself. Whatever you find interesting, just follow your bliss.

I also gave a shot on trying to come up with something useful. Below is my finished data dashboard.

My Data Dashboard for StockX

Dashboard

The link for tableau worksheet is here

Calculations on the Dashboards

Price ratio: Ratio of Sales to Retail Price for Each Sneakers
Weeks: (Order Date - Release Date) Converted in Weeks.
Median Price ratio is chosen to eliminate the effect of asymmetrical range of dates(2017-2019 not complete as 2018) and counts of sneakers sales.
Color Scale for two brands are consistent whenever there is plot relating to brands.

1) Order of Sneakers by brand for weeks from Release Date

This plot shows the total count of orders for different sneakers of two brands Both Brands are ordered before the release date. Off white has more orders than yeezy on the datasets.

It’s interesting how the demand of yeezy increased at around `90 weeks` after the release of the shoes.

2)Ratio of Sales Price to Retail Price For each Brand by Weeks

This plot look at the relation of ratio of sale price to retail price for each brands and weeks after release date. Clearly,Both Brand’s sale price is more than the retail price. The ratio of off-White increases in general regardless of the individual sneakers while the ratio of yeezy brands is somewhat noisy but it has a trend like off white. Both brand’s price ratio is increased after the release date.

3)Distribution of Median Sales price given the retail price for each brand
This plot looks in detail on how the median sale price is distributed for each sneaker. The distribution of median sale price for top 28 sneakers which were sold as least as 5 times over retail price are plotted.

4) Median Price and States

This plot is looking at the median price ratio for all the states. The color scale is chosen for the ratio and the size of the sneakers shows total sales relative to others. Which states usually pays more for sneakers? Clearly, Delaware,Vermont,Utah had some sales with high price ratio. States like California and Newyork have a lot of sales as shown by their relative sizes. The relative size is calculated by taking the log of total sales in each states. States like Wyoming have less Sales and also with lower sales ratio.

Winona Area Public Schools: Community Contribution

Wed, 21 Aug 2019 21:13:14 -0500

Winona Area Public Schools Data Visualization

Introduction:
This Project addresses the need of communication of public school data to community members in an meaningful way.Also, making the data available to general public in a proper and useable format.

There has been a wider discussion regarding the budget issue in Winona area schools. Here is the article

Primarily, this Project was focused on cleaning and visualizing the Enrollment,Expenditures and Staffing History reports of the Winona Area Public District(WAPS) available publicly through Minnesota department of education, Data Center Link:http://education.state.mn.us/MDE/Data/

Methods and Steps of Projects

1)Data Inspection/Acquisition:.
Public Data was collected by Alison Quam (Representative from WAPS District). The Data were made available in different pdf/excel files. Also, the information were scattered in different files.

2)Data Cleaning and Formatting
First,most of the pdf files were converted to excel by Tabula(Link:http://tabula.technology/) and online tool(http://pdftoexcel.com) then, they were cleaned up in proper format and stacked using Python (Pandas).

3)Data Exploration and Visualization
This part of the project is focused on addressing the questions provided by representative of WAPS(Alison Quam). Tableau was used extensively to explore the data and visualize it. Primarily, i focused on answering following questions.
1. I was curious about,how does the enrollment and capture rate(rate of new born enrolling to Kindergarten)is changing on WAPS district?.

After few meetings with representative, i realized she was more curious about how schools spends on across different programs.

2.How the expenditure per average daily membership (count of student daily served in schools) and spending on various category is changing?.

The link to the tableau file and the data is here

Now, Visual Story Begins….

This project actually helped inform the decision makers in local level. Thus, i was able to contribute to something meaningful with my python and tableau skills.

Acknowledgement

I would like to thank WAPS representative and Prof.Silas Bergen on helping and guiding me to understand the terms and calculations already done in the reports and Prof.Todd Iverson to help figure out Python code for cleaning the data.

Animation:Internet Usage

Thu, 15 Aug 2019 21:13:14 -0500

How internet is eating the world? Internet Usage animation

Internet Usage is the world bank development indicator. In this project i grabbed the world bank dataset(which is in the link provided below).

Link to the tableau worksheet