In this post we would look at another Data Manipulation scenario. The nature of the task as well as resources have been summarized in the following sections:
Problem Statement: There is a sports accessories company ABC that sells sports gear across the globe. The data has fields such as Revenue, Quantity, Gross Margin, Order Method, Time, Country etc spread from 2012 to 2014 across 4 Quarters (Q1 through Q4). Based on the Global Outlook and growth forecasts made by economist at ABC, the company has decided to sell total units equal to 211,555,475 in 2015. However, this is an overall number and Product Managers for individual countries don't know how this number would drill down to individual Product. Your job as a Business Analyst is to help the Product Managers get the numbers so that they can plan effectively
Data Download Link:
Learning Objectives:
- Using Pandas for data manipulation
- Getting records and column names
- Handle NA
- Using Groupby to sum up numbers at different levels
- Using 'apply' function on certain columns
- Using lambda along with apply to get Percentage Share
- % formatting
Please download the jupyter file from the following link
Jupyter File link: https://drive.google.com/file/d/1yH2LkcuWYNPmGrLA2Up2t6OnfoKZewvo/view?usp=sharing
Link to Html version:
https://drive.google.com/file/d/1l1ewyfLpXVrtyrlfh_JBW_EW0xbkgVsX/view?usp=sharing
Link to Html version:
https://drive.google.com/file/d/1l1ewyfLpXVrtyrlfh_JBW_EW0xbkgVsX/view?usp=sharing
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