Data Analysis and Visualization
- 1. SHOPPING MALL DATA VISUALISATION AND ANALYSIS
- 2. PROBLEM STATEMENT The dataset has over 8000 rows and 14 columns. It a collection of data about approximately1550 products across 10 stores in different cities of Canada. Analyze the patterns related to product sales. Use this data to explore functions in Tableau and Python for data analysis.
- 4. Tableau It is a data visualization tool. Every operations can be performed using drag and drop functionality. No coding required. It can connect with different data sources such as files, relational databases and others. .xls files used in this analysis. It can modify the data. For instance, new fields can be created using different operations. It can split, join, concatenate, change data type and perform other such tasks. Provides numerous types of graphs and can perform sum, average, median, mode and other such functions on data provided.
- 5. Setting up Tableau Download Tableau: https://www.tableau.com/products/desktop/download The next step will be set up the Tableau and import the data set:
- 6. Creating New Columns New fields can be created from existing ones. Calculations like divide, multiply, addition, subtraction and others can be performed on numerical fields.
- 8. After Split
- 9. Functions Apply various functions on numeric value columns while plotting.
- 10. Annotation Annotate the marks on trend lines.
- 11. Trend Prediction Across all the stores, Low Fat items had greater sales and Visibility. As the number of low fat items will increase, the sales of that item and store will also incline.
- 12. Types of graphs in Tableau Histogram Scatter Plot Packed Bubbles Line Graph Horizontal Histogram Tree Map Pie Chart Gantt Chart Box Plot and others.
- 13. Trend 1 Features Toronto has maximum Sales and Population City with second highest sales is Ottawa and Barrie has lowest sales.
- 14. Trend 2 Prediction Low Fat items marked by blue circles are bought more than regular items. As the number of low fat items will increase, the sales of that item and store will also incline.
- 15. Trend 3 Features Toronto store sells almost 35K Snack food items and 15K Soft Drink items in a month. Barrie and Waterloo sell least number of items.
- 16. Trend 4 Prediction It shows the variety of items available at each store type. Increasing the variety of items at a store will increase its sales.
- 17. Trend 5 Features Item Prices compared for different cities. Fruits and vegetables most expensive in London. Frozen foods being most affordable in Barrie.
- 18. THANK YOU!!
Editor's Notes
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