Strategy Analysis for shoes values

As a part of interview assessments I had a task to analyze data about shoes and their values.

Attribute — refers to things like color, material, and style.

Value — refers to grey, red, and black being example values for color. Cotton, nylon, and polyester are example values for the attribute material. Classic, Casual, and Sport are values for the attribute style.

First we will import the libraries:

Then we will read the dataset:

Now we have to try to generate values for Q:material and Q:style:

After finishing above we will generate more columns. For example gender/ front style of the shoe and whether it has laces or no.

Now that we have all possible values we can see the counts and understand what is happening.

In conclusion we can say that there are more men shoes with laces which are leather and athletic.

Hope you find this article helpful and if you have any questions please contact me @kristinelpetrosyan@gmail.com.