Project 1

Solutions

create database ecommerce;

---- imported .csv file users_data into MySQL----

Desc users_data;

select * from users_data limit 100;

select count(distinct country), count(distinct language) from users_data;

select count(socialNbFollowers), gender from users_data

group by gender;

select count(hasProfilePicture) from users_data

where hasProfilePicture ='true';

select count(hasanyapp)from users_data

where hasanyapp = 'true';

select count(hasandroidapp)from users_data

where hasandroidapp = 'true';

select count(hasiosapp) from users_data

where hasiosapp = 'true';

select country, sum(productsbought) from users_data

where productsbought >= 1 group by country

order by sum(productsBought) desc;

select country, sum(productssold) from users_data

where productssold >= 1 group by country

order by sum(productssold) asc;

select distinct country,productspassrate from users_data ------

where any(country) = max(productspassrate)

group by country

order by max(productspassrate);

select distinct language, sum(language) from users_data -----

group by language;

order by sum(all language);

select socialproductsliked, productswished from users_data ----

where socialProductsLiked >=1 or productsWished >=1

group by gender;

#### 13####

select country, max(productsBought),sum(productsBought) from users_data

where productsBought>=0

group by country

order by sum(productsbought) desc;

select country,sum(productssold) from users_data ------

where sum(productssold) = 0

group by country

order by sum(productssold) limit 10;

select country, count(gender) total_female from users_data

WHERE gender = 'f'

group by country

order by count(gender);

select country, count(gender) total_male from users_data

WHERE gender = 'm'

group by country

order by count(gender);

select country, avg(productsSold), avg(productsBought), count(gender) from users_data

WHERE gender = 'm'

group by country;