Project 1

SELECT * FROM ecommerce.users_data;

#ANS 3

desc users_data;

# ANS4

select*from users_data limit 100;

# ANS5r

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

#ANS6r

select gender,count(socialNbFollowers) as socialNbFollowers from users_data where socialNbFollowers >=1 group by gender;

# ANS7r

select count(hasprofilepicture) as profilepicture from users_data where hasprofilepicture=true;

select count(hasAnyApp) as hasAnyApp from users_data where hasAnyApp=true;

select count(hasAndroidApp) as AndroidApp from users_data where hasAndroidApp=true;

select count(hasIosApp) as IosApp from users_data where hasIosApp=true;

# ANS8r

select country,count(productsBought) as buyers from users_data where productsBought >=1 group by country order by buyers desc;

#ANS 9r

select country,count(productsSold) as sellers from users_data where productsSold >=1 group by country order by sellers asc;

# ANS10r

select country,count(productspassrate) as ProductsRate from users_data group by country order by ProductsRate  desc limit 10;

# ANS11r

select count(hasAnyApp),language from users_data group by language;

#ANS12r

select 'product in a wishlist', count(productsWished) choices

 from users_Data where gender='F' and productsWished>0

 union

 select 'product liked socially', count(socialProductsLiked) choices2

 from users_Data where gender='F' and socialProductsLiked>0;

#ANS 13r

select 'Selling', count(productsSold) choices

 from users_Data where gender='M' and productsSold>0

 union

 select 'Buying', count(productsBought) choices2

 from users_Data where gender='M' and productsBought>0;

#ANS14r

select country,max(productsBought) as max_buyer from users_data;

#ANS15r

select country,productssold from users_data where productssold=0 limit 10;

# ANS16r

select hasAnyApp from users_data where hasAnyApp=0 order by hasAnyApp desc limit 110;

#ANS17r

select count(gender) as female from users_data where gender="f" and daysSinceLastLogin !=100;

#ANS18r

select country,count(gender) as female from users_data where gender="f"  group by country;

#ANS19r

select country,hasAnyApp,gender from users_data where gender="m";

#ANS20r

select country,avg(productsSold) Sold,avg(productsBought) Bought

from users_data  

where gender='M' and hasAnyApp='True' group by country;