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Homework answers / question archive / R CASE STUDY 3: DATA VISUALIZATION IN R DATA VISUALIZATION: Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context

R CASE STUDY 3: DATA VISUALIZATION IN R DATA VISUALIZATION: Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context

Computer Science

R CASE STUDY 3:

DATA VISUALIZATION IN R

DATA VISUALIZATION:

Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization software.

It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns.

 

WHY IS DATA VISUALIZATION IMPORTANT?

Using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports because human brain perceives, understands and grasps visuals better and faster than numbers or alphabets. Data visualization is a quick, easy way to convey concepts in a universal manner – and you can experiment with different scenarios by making slight adjustments.

Data visualization can:

 

  • Identify areas that need attention or improvement.

 

  • Clarify which factors influence customer behavior.

 

  • Help you understand which products to place where.

 

  • Predict sales volumes.

 

CASE STUDY IN R:

 

The objective of this dashboard is to understand sales trends for one of the leading pharmaceutical company.

The client would like to come see a dynamic dashboard with different KPI's at different levels (National, Region & Territory etc). Create the below charts as these would help us explore the past data in a better manner and give a good picture of the progress and failures. This in turn would catalyse the decision-making process, making it easier, simpler and accurate.

ABOUT DATA:

The data attached is a two-year sales data of a pharma company which talks about sales in 2015 and 2016 across various regions and time frames.

Account Id          : Customer ID Account Name    : Customer Name Tier                     : Customer Segment

Sales 2015           : Sales for the year 2015 Sales 2016                   : Sales for the year 2015 Units 2015                   : No of Units sold for 2015 Units 2016                   : No of Units sold for 2016

  1. Compare Sales by region for 2016 with 2015 using bar chart
  2. Pie charts for sales for each region in 2016
  3. Compare sales of 2015 and 2016 with Region and Tiers
  4. In East region, which state registered a decline in 2016 as compared to 2015?
  5. In all the High tier, which Division saw a decline in number of units sold in 2016 compared to 2015?
  6. Create a new column Qtr -
    • Jan - Mar : Q1
    • Apr - Jun : Q2
    • Jul - Sep : Q3
    • Oct - Dec : Q4
  7. Compare Qtr wise sales in 2015 and 2016 in a bar plot
  8. Determine the composition of Qtr wise sales in and 2015 with regards to all the Tiers in a pie chart.

(Draw 4 pie charts representing a Quarter for each Tier)

SAMPLE OUTPUTS:

  1. Compare Sales by region for 2016 with 2015 using bar chart
  2. Pie charts for sales for each region in 2016
  1. Compare sales of 2015 and 2016 with Region and Tiers
  1. In East region, which state registered a decline in 2016 as compared to 2015?
  1. In all the High tier, which Division saw a decline in number of units sold in 2016 compared to 2015?
  2. Compare Qtr wise sales in 2015 and 2016 in a bar plot
  1. Determine the composition of Qtr wise sales in and 2015 with regards to all the Tiers in a pie chart. (Draw 4 pie charts representing a Quarter for each Tier)

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