Project 1
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. Behaviour 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
-- Q1.Create new schema as ecommerce
CREATE SCHEMA ecommerce;
USE ecommerce;
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-- Q2. Import .csv file users_data into MySQL
(right click on ecommerce schema -> Table Data import Wizard -> Give path of the file -> Next -> choose options :
Create a new table , select delete if exist -> next -> next)
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-- Q3.Run SQL command to see the structure of table
DESC users_data;
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-- Q4.Run SQL command to select first 100 rows of the database
SELECT * FROM users_data LIMIT 100;
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-- Q5.How many distinct values exist in table for field country and language
SELECT DISTINCT country,language FROM users_data;
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-- Q6.Check whether male users are having maximum followers or female users.
SELECT 'Male Users',SUM(socialNBFollowers) Followers FROM users_data WHERE gender = 'M' UNION
SELECT 'Female User', SUM(socialNBFollowers) FROM users_data WHERE gender = 'F';
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-- Q7.Calculate the total users those 1.Uses Profile Picture in their Profile 2.Uses Application for Ecommerce platform 3.Uses Android app 4.Uses ios app
SELECT 'Uses Profile Picture in their Profile' Parameters,COUNT(*) USERS FROM users_data WHERE hasProfilePicture = 'TRUE' UNION
SELECT 'Uses Application for Ecommerce platform',COUNT(*) FROM users_data WHERE hasAnyApp = 'TRUE' UNION
SELECT 'Uses Android app',COUNT(*) FROM users_data WHERE hasAndroidApp = 'TRUE' UNION
SELECT 'Uses ios app',COUNT(*) FROM users_data WHERE hasIosApp = 'TRUE';
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-- Q8.Calculate the total number of buyers for each country and sort the result in descending order of total number of buyers. (Hint: consider only those users having at least 1 product bought.)
SELECT SUM(productsBought)number_of_buyers ,country FROM users_data WHERE productsBought <> 0 GROUP BY country ORDER BY SUM(productsBought) DESC;
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-- Q9.Calculate the total number of sellers for each country and sort the result in ascending order of total number of sellers. (Hint: consider only those users having at least 1 product sold.)
SELECT SUM(productsSold)number_of_buyers ,country FROM users_data WHERE productsSold <> 0 GROUP BY country ORDER BY SUM(productsSold) ASC;
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-- Q10.Display name of top 10 countries having maximum products pass rate.
SELECT country,SUM(productsPassRate) FROM users_data GROUP BY country ORDER BY SUM(productsPassRate) DESC LIMIT 10;
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-- Q11.Calculate the number of users on an ecommerce platform for different language choices.
SELECT language,COUNT(identifierHash) Users FROM users_data GROUP BY language;
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-- Q12.Check the choice of female users about putting the product in a wishlist or to like socially on an ecommerce platform. (Hint: use UNION to answer this question.)
SELECT 'F'GENDER,' Product wish'Product, SUM(productsWished) Sum FROM users_data WHERE gender ='F' UNION
SELECT 'F ','Product Like' ,SUM(socialProductsLiked) FROM users_data WHERE gender ='F';
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-- Q13.Check the choice of male users about being seller or buyer. (Hint: use UNION to solve this question.)
SELECT 'M' ,'Product Sell',SUM(productsSold) FROM users_data WHERE gender ='M' UNION
SELECT 'M' ,'Product Bought',SUM(productsBought) FROM users_data WHERE gender ='M';
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-- Q14.Which country is having maximum number of buyers?
SELECT country,SUM(productsBought) FROM users_data GROUP BY country ORDER BY SUM(productsBought) DESC;
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-- Q15.List the name of 10 countries having zero number of sellers.
SELECT country,productsSold FROM users_data WHERE productsSold = 0 LIMIT 10;
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-- Q16.Display record of top 110 users who have used ecommerce platform recently.
SELECT identifierHash,daysSinceLastLogin FROM users_data ORDER BY daysSinceLastLogin ASC LIMIT 110;
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-- Q17.Calculate the number of female users those who have not logged in since last 100 days.
SELECT identifierHash, gender,COUNT(daysSinceLastLogin) FROM users_data WHERE gender ='F' AND daysSinceLastLogin >100 GROUP BY gender ;
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-- Q18.Display the number of female users of each country at ecommerce platform.
SELECT country,COUNT(*) FROM users_data WHERE gender ='F' GROUP BY country ORDER BY country;
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-- Q19.Display the number of male users of each country at ecommerce platform.
SELECT country,COUNT(*) FROM users_data WHERE gender ='M' GROUP BY country ORDER BY country;
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-- Q20.Calculate the average number of products sold and bought on ecommerce platform by male users for each country.
SELECT country,AVG(productsSold),AVG(productsBought) FROM users_data WHERE gender ='M' GROUP BY country;
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