Project 1

1.

create database ecommerce;

2.

Imported the data from .csv file successfully

3.

use ecommerce;
desc users_data;

4.

select * from users_data limit 100;

5.

select distinct country,language from users_data;

6.

select gender,sum(socialNbFollowers) from users_data group by gender;

7.

select count(*) from users_data where hasProfilePicture = 'True';
select count(*) from users_data where hasAnyApp = 'True';
select count(*) from users_data where hasAndroidApp = 'True';
select count(*) from users_data where hasIosApp = 'True';

8.

select country, sum(productsBought) from users_data where productsBought > 0 group by country order by sum(productsBought) DESC;

9.

select country, sum(productsSold) from users_data where productsSold > 0 group by country order by sum(productsSold) DESC;

10.

select country from users_data group by country order by sum(productsPassRate) desc limit 10;

11.

select language,count(hasAnyApp) from users_data where hasAnyApp = 'True' group by language ;

12.

select count(gender) from users_data where gender ='f' and (productsWished > 0 or socialProductsLiked > 0 );

13.

select count(gender) from users_data where gender ='m' and (productsSold > 0 or productsBought > 0);

14.

select country from users_data where productsBought > 0 group by country order by sum(productsBought) desc limit 1;

15.

select country from users_data where productsSold = 0 group by country limit 10;

16.

select * from users_data order by daysSinceLastLogin asc limit 110;

17.

select count(gender) from users_data where daysSinceLastLogin > 100 and gender='f';

18.

select country,count(gender) from users_data where gender='f' and hasAnyApp = 'True' group by country;

19.

select country,count(gender) from users_data where gender='m' and hasAnyApp = 'True' group by country;

20.

select country,avg(productsSold)as avgSold,avg(productsBought) as avgBought from users_data where gender='m' and hasAnyApp='True' group by country;