The business model Customer to Customer (C2C) allows customers to do business with each other. This model is growing fast with e-commerce platforms where sellers may be required to pay some amount and buyer can buy it without paying anything. E-Commerce website brings the seller and buyer to the same platform. 

Analyzing the user's database will lead to understanding the business perspective. Behavior of the users can be traced in terms of business with exploration of the user’s database. 

Dataset: One .csv file with name users_data with 98913 rows and 27 columns

Tasks to be performed

1. Create new schema as ecommerce
2. Import .csv file users_data into MySQL
3. Run SQL command to see the structure of table
4. Run SQL command to select first 100 rows of the database
5. How many distinct values exist in table for the field "country" and "language"
6. Check whether male users are having maximum followers or female users.
7. Calculate the total number of users that
1. Uses Profile Picture in their Profile
2. Uses Application for Ecommerce platform
3. Uses Android app
4. Uses ios app
8. Calculate the total number of buyers for each country and sort the result in descending order of total number of buyers.
9. Calculate the average number of sellers for each country and sort the result in ascending order of total number of sellers.
10. Display name of top 10 countries having maximum products pass rate.
11. Calculate the number of users on an ecommerce platform for different language choices.
12. Check the choice of female users about putting the product in a wishlist or to like socially on an ecommerce platform.
13. Check the choice of male users about being seller or buyer.
14. Which country is having maximum number of buyers?
15. List the name of 10 countries having zero number of sellers.
16. Display record of top 110 users who have used ecommerce platform recently.
17. Calculate the number of female users those who have not logged in since last 100 days.
18. Display the number of female users of each country at ecommerce platform.
19. Display the number of male users of each country at ecommerce platform.
20. Calculate the average number of products sold and bought on ecommerce platform by male users for each country.

Once a student is passed out from a Institute or College, he/she is known as Alumni of the Institute. Alumni’s career growth plays important role in Institute’s ranking and other networking activities. In this project, career choices of alumni of two Universities will be analyzed with respect to their passing year as well as the course they completed. 

Dataset: Six .csv file (Alumni record of College A and College B) Higher Studies, Self Employed and Service/Job record 

• College_A_HS ~ Higher Studies Record of College A
• College_A_SE ~ Self Employed Record of College A
• College_A_SJ ~ Service/Job Record of College A
• College_B_HS ~ Higher Studies Record of College B
• College_B_SE ~ Higher Studies Record of College B
• College_B_SJ ~ Higher Studies Record of College B

Tasks to be performed

1. Create new schema as alumni
2. Import all .csv files into MySQL
3. Run SQL command to see the structure of six tables
4. Display first 1000 rows of tables (College_A_HS, College_A_SE, College_A_SJ, College_B_HS, College_B_SE, College_B_SJ) with Python.
5. Import first 1500 rows of tables (College_A_HS, College_A_SE, College_A_SJ, College_B_HS, College_B_SE, College_B_SJ) into MS Excel.
6. Perform data cleaning on table College_A_HS and store cleaned data in view College_A_HS_V.
7. Perform data cleaning on table College_A_SE and store cleaned data in view College_A_SE_V.
8. Perform data cleaning on table College_A_SJ and store cleaned data in view College_A_SJ_V.
9. Perform data cleaning on table College_B_HS and store cleaned data in view College_B_HS_V.
10. Perform data cleaning on table College_B_SE and store cleaned data in view College_B_SE_V.
11. Perform data cleaning on table College_B_SJ and store cleaned data in view College_B_SJ_V.
12. Make procedure to use string function/s for converting record of Name, FatherName, MotherName into lower case for views (College_A_HS_V, College_A_SE_V, College_A_SJ_V, College_B_HS_V, College_B_SE_V, College_B_SJ_V) 
13. Import the created views (College_A_HS_V, College_A_SE_V, College_A_SJ_V, College_B_HS_V, College_B_SE_V, College_B_SJ_V) into MS Excel and make pivot chart for location of Alumni. 
14. Make data summary for all six views (College_A_HS_V, College_A_SE_V, College_A_SJ_V, College_B_HS_V, College_B_SE_V, College_B_SJ_V) for demographic analysis through SQL. 
15. Make data summary for views (College_A_SJ_V, College_B_SJ_V) for company choices of Alumni through SQL. 
16. Make data summary for the decision of being entrepreneur of Alumni of particular domain through SQL. 
17. Analyze the choice of course after being graduated from College for College A and College B through SQL. (Use the cleaned data only)
18. Analyze the choice of Institute after being graduated from College for College A and College B through SQL (Use the cleaned data only)
19. Analyze the choice of higher studies in India and abroad for College A and College B through SQL (Use the cleaned data only)
20. Calculate the percentage of career choice of College A and College B Alumni (w.r.t Higher Studies, Self Employed and Service/Job)