Project 1
1. Create new schema as ecommerce
create database ecommerce;
2. 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)
use ecommerce;
3. Run SQL command to see the structure of table
desc users_data;
| identifierHash | bigint | YES | |||
| type | text | YES | |||
| country | text | YES | |||
| language | text | YES | |||
| socialNbFollowers | int | YES | |||
| socialNbFollows | int | YES | |||
| socialProductsLiked | int | YES | |||
| productsListed | int | YES | |||
| productsSold | int | YES | |||
| productsPassRate | double | YES | |||
| productsWished | int | YES | |||
| productsBought | int | YES | |||
| gender | text | YES | |||
| civilityGenderId | int | YES | |||
| civilityTitle | text | YES | |||
| hasAnyApp | text | YES | |||
| hasAndroidApp | text | YES | |||
| hasIosApp | text | YES | |||
| hasProfilePicture | text | YES | |||
| daysSinceLastLogin | int | YES | |||
| seniority | int | YES | |||
| seniorityAsMonths | double | YES | |||
| seniorityAsYears | double | YES | |||
| countryCode | text | YES |
4. Run SQL command to select first 100 rows of the database
select * from users_data limit 100;
5. How many distinct values exist in table for field country and language
select count(distinct country) as distinct_country, count(distinct language) as distinct_language from users_data;
distinct_country = 200
distinct_language = 5
6. Check whether male users are having maximum followers or female users.
select sum(socialNbFollowers), gender from users_data group by gender;
| F | 262458 |
| M | 77038 |
7.Calculate the total users those
a. Uses Profile Picture in their Profile
select count(hasProfilePicture) from users_data where hasProfilePicture= "TRUE"; '97018'
b. Uses Application for Ecommerce platform
select count(hasAnyApp) from users_data where hasAnyApp= "TRUE"; '26174'
c. Uses Android app.
select count(hasAndroidApp) from users_data where hasAndroidApp= "TRUE"; '4819'
d. Uses ios app
select count(hasIosApp) from users_data where hasIosApp = "TRUE"; '21527'
8. 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 country, sum(productsBought) as Total_no_of_buyers from users_data group by country having Total_no_of_buyers >=1
order by Total_no_of_buyers desc;
| France | 3573 | |
| Etats-Unis | 2370 | |
| Royaume-Uni | 2174 | |
| Allemagne | 1635 | |
| Italie | 1221 | |
| Espagne | 1028 | |
| Belgique | 718 | |
| Suède | 566 | |
| Pays-Bas | 537 | |
| Danemark | 438 | |
| Australie | 398 | |
| Finlande | 331 | |
| Autriche | 242 | |
| Luxembourg | 162 | |
| Roumanie | 162 | |
| Canada | 155 | |
| Pologne | 150 | |
| Suisse | 137 | |
| Hong Kong | 112 | |
| Chine | 111 | |
| Bulgarie | 95 | |
| Irlande | 79 | |
| Singapour | 75 | |
| Portugal | 72 | |
| Japon | 67 | |
| Grèce | 53 | |
| Hongrie | 42 | |
| Croatie | 39 | |
| Slovénie | 39 | |
| Cambodge | 39 | |
| Macau | 19 | |
| Ukraine | 18 | |
| Émirats arabes unis | 13 | |
| Corée du Sud | 11 | |
| Norvège | 11 | |
| Nouvelle Zélande | 9 | |
| Chypre | 9 | |
| Taiwan | 9 | |
| Estonie | 9 | |
| Israel | 8 | |
| Russie | 8 | |
| République tchèque | 8 | |
| Malaisie | 5 | |
| Mexique | 4 | |
| Bahreïn | 4 | |
| Lituanie | 4 | |
| Monaco | 4 | |
| Brésil | 4 | |
| Turquie | 4 | |
| Guadeloupe | 3 | |
| Puerto Rico | 3 | |
| Géorgie | 3 | |
| Egypte | 3 | |
| Indonésie | 2 | |
| Slovaquie | 2 | |
| Arabie Saoudite | 2 | |
| Islande | 2 | |
| Qatar | 1 | |
| Colombie | 1 | |
| Serbie | 1 | |
| Pakistan | 1 | |
| Malte | 1 |
9. 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 country, sum(productsSold) as Total_no_of_sellers from users_data group by country having Total_no_of_sellers >=1
order by Total_no_of_sellers;
| ÃŽles Canaries | 1 |
| Japon | 1 |
| Bahamas | 1 |
| Kazakhstan | 1 |
| Islande | 2 |
| Chine | 2 |
| Ukraine | 3 |
| Lituanie | 4 |
| Estonie | 4 |
| Serbie | 5 |
| Slovénie | 6 |
| Canada | 7 |
| Russie | 10 |
| Singapour | 11 |
| Irlande | 16 |
| Finlande | 20 |
| Pologne | 23 |
| Slovaquie | 28 |
| Grèce | 31 |
| Portugal | 33 |
| Australie | 35 |
| Luxembourg | 43 |
| Suisse | 45 |
| Danemark | 50 |
| Hong Kong | 50 |
| Chypre | 56 |
| Taiwan | 57 |
| Autriche | 67 |
| Roumanie | 68 |
| Lettonie | 83 |
| Croatie | 107 |
| Belgique | 114 |
| Bulgarie | 170 |
| Monaco | 190 |
| Pays-Bas | 214 |
| Suède | 336 |
| Allemagne | 536 |
| Etats-Unis | 967 |
| Espagne | 990 |
| Royaume-Uni | 1806 |
| Italie | 2820 |
| France | 3014 |
10. Display name of top 10 countries having maximum products pass rate.
select country, sum(productsPassRate) as Max_Pass_Rate from users_data group by country order by Max_Pass_Rate desc limit 10;
| France | 24572.8 |
| Italie | 17669 |
| Royaume-Uni | 10899.1 |
| Etats-Unis | 5865.1 |
| Espagne | 5006.6 |
| Allemagne | 3821 |
| Pays-Bas | 2219.8 |
| Suède | 1611.6 |
| Belgique | 1304 |
| Autriche | 871 |
-------------------------------------------------- OR --------------------------------------------------
select country from users_data group by country order by sum(productsPassRate) desc limit 10;
| France |
| Italie |
| Royaume-Uni |
| Etats-Unis |
| Espagne |
| Allemagne |
| Pays-Bas |
| Suède |
| Belgique |
| Autriche |
11. Calculate the number of users on an ecommerce platform for different language choices.
select language, count(type) as no_of_users from users_data group by language;
| en | 51564 |
| de | 7178 |
| fr | 26372 |
| es | 6033 |
| it | 7766 |
12. 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 'Products wishlisted', sum(productsWished) from users_data where gender = "F"
union
select 'Products liked', sum(socialProductsLiked) from users_data where gender = "F";
| Products wishlisted | 129498 | |
| Products liked | 373600 |
13. Check the choice of male users about being seller or buyer. (Hint: use UNION to solve this question.)
select 'Seller(M)', count(productsListed) from users_data where gender = "M" and productsListed>0
union
select 'Buyer(M)', count(productsBought) from users_data where gender = "M" and productsBought>0 ;
| Seller(M) | 314 | |
| Buyer(M) | 1471 |
14. Which country is having maximum number of buyers?
select country, count(type) as Buyers from users_data where productsBought > 0 group by country limit 1;
| France | 1251 |
15. List the name of 10 countries having zero number of sellers.
select country from users_data group by country having sum(productsSold) = 0 limit 10;
| Turquie | |
| Réunion | |
| Chili | |
| Djibouti | |
| Congo | |
| Martinique | |
| Sénégal | |
| Maroc | |
| Panama | |
| Équateur |
16. Display record of top 110 users who have used ecommerce platform recently.
select * from users_data order by daysSinceLastLogin asc limit 110;
17. Calculate the number of female users those who have not logged in since last 100 days.
select count(type) from users_data where gender = "F" and daysSinceLastLogin > 100;
| 70189 |
18. Display the number of female users of each country at ecommerce platform.
select country, count(type) from users_data where gender = "F" group by country;
| Etats-Unis | 17079 |
| Allemagne | 4577 |
| Turquie | 85 |
| Royaume-Uni | 8732 |
| Italie | 5984 |
| Espagne | 4527 |
| Danemark | 1414 |
| France | 18085 |
| Suisse | 667 |
| Chili | 37 |
| Congo | 11 |
| Irlande | 379 |
| Suède | 1257 |
| Martinique | 24 |
| Canada | 1289 |
| Australie | 2203 |
| Belgique | 1374 |
| Pays-Bas | 1360 |
| Chine | 368 |
| Maroc | 113 |
| Panama | 10 |
| Portugal | 166 |
| Équateur | 10 |
| Hong Kong | 748 |
| Colombie | 35 |
| Nouvelle Zélande | 90 |
| Pologne | 161 |
| Bulgarie | 67 |
| Japon | 108 |
| Inde | 96 |
| Trinidad et Tobago | 5 |
| Rwanda | 1 |
| Émirats arabes unis | 112 |
| Singapour | 198 |
| Mexique | 136 |
| Corée du Sud | 107 |
| Brunei Darussalam | 10 |
| Le Salvador | 2 |
| République dominicaine | 6 |
| Brésil | 77 |
| Argentine | 26 |
| Algérie | 47 |
| Finlande | 494 |
| Grèce | 197 |
| Qatar | 40 |
| Malaisie | 93 |
| Tunisie | 55 |
| Azerbaïdjan | 18 |
| Mali | 2 |
| Autriche | 536 |
| Russie | 426 |
| Niger | 1 |
| Hongrie | 47 |
| Lettonie | 40 |
| Croatie | 104 |
| Serbie | 48 |
| Malte | 21 |
| Roumanie | 250 |
| Luxembourg | 86 |
| Angola | 3 |
| Egypte | 25 |
| Indonésie | 54 |
| Pakistan | 8 |
| Slovaquie | 42 |
| Albanie | 25 |
| Philippines | 85 |
| Puerto Rico | 15 |
| Norvège | 134 |
| Afrique du Sud | 62 |
| Nouvelle Calédonie | 13 |
| Iles Cayman | 3 |
| Chypre | 49 |
| Arabie Saoudite | 130 |
| Sri Lanka | 1 |
| Guyane | 10 |
| Bolivie | 3 |
| Cote D'Ivoire | 15 |
| Taiwan | 99 |
| Pérou | 14 |
| Thailande | 60 |
| Israel | 87 |
| Polynésie Française | 7 |
| Ouganda | 3 |
| Moldavie | 19 |
| Bosnie et Herzegovine | 12 |
| Bahreïn | 22 |
| Cameroun | 12 |
| Kowait | 69 |
| Togo | 1 |
| Macau | 11 |
| Lituanie | 36 |
| République tchèque | 45 |
| Svalbard et Jan Mayen Islands | 1 |
| Arménie | 15 |
| Guernsey | 1 |
| Myanmar | 7 |
| Réunion | 40 |
| Slovénie | 27 |
| Géorgie | 21 |
| Samoa américaines | 7 |
| Monaco | 31 |
| Ukraine | 87 |
| Venezuela | 12 |
| Mongolie | 10 |
| Guinée | 3 |
| Madagascar | 8 |
| Guatemala | 3 |
| Anguilla | 1 |
| Nigeria | 21 |
| Kenya | 8 |
| Costa Rica | 5 |
| Jamaique | 2 |
| Viet Nam | 46 |
| Cambodge | 14 |
| Biélorussie | 8 |
| Oman | 8 |
| Estonie | 28 |
| Liban | 33 |
| Îles Turques-et-Caïques | 1 |
| Kazakhstan | 33 |
| Islande | 20 |
| Afghanistan | 5 |
| Gabon | 7 |
| Érythrée | 1 |
| Antigua et Barbuda | 2 |
| Jordanie | 13 |
| République centrafricaine | 1 |
| Benin | 3 |
| Bangladesh | 5 |
| Iran | 12 |
| Zimbabwe | 4 |
| Bermude | 3 |
| Guadeloupe | 25 |
| Guam | 1 |
| Syrie | 1 |
| Saint Vincent et les Grenadines | 1 |
| Gibraltar | 1 |
| Géorgie du Sud / Iles Sandwich | 1 |
| Ghana | 1 |
| Nepal | 1 |
| Grenade | 2 |
| ÃŽle Bouvet | 2 |
| Sénégal | 6 |
| Botswana | 2 |
| Namibie | 2 |
| Laos | 2 |
| Maldives | 3 |
| Îles Féroé | 1 |
| Jersey | 8 |
| Cuba | 1 |
| Gambie | 1 |
| Sainte Lucie | 1 |
| Uruguay | 3 |
| Andorre | 8 |
| Barbade | 2 |
| Nicaragua | 3 |
| ÃŽles Vierges britanniques | 2 |
| Irak | 3 |
| Bahamas | 2 |
| Tajikistan | 2 |
| Macédoine | 6 |
| ÃŽles Vierges (U.S.) | 2 |
| Djibouti | 1 |
| Iles mineures éloignées des États-Unis | 1 |
| Tanzanie | 2 |
| Fidji | 2 |
| Liechtenstein | 2 |
| Maurice | 3 |
| Corée du Nord | 1 |
| ÃŽle Norfolk | 1 |
| Kirghizistan | 4 |
| Haiti | 2 |
| Antilles néerlandaises | 1 |
| ÃŽles Malouines | 1 |
| Honduras | 8 |
| Burkina Faso | 2 |
| Palau | 1 |
| Paraguay | 2 |
| Mauritanie | 2 |
| Vanuatu | 1 |
| ÃŽles Canaries | 2 |
| Aruba | 1 |
| Kiribati | 3 |
| Suriname | 1 |
| Uzbekistan | 2 |
| Guyana | 1 |
| Samoa | 1 |
| Mayotte | 1 |
| Saint Kitts et Nevis | 1 |
| Dominique | 1 |
| Swaziland | 1 |
| ÃŽle de Man | 1 |
19. Display the number of male users of each country at ecommerce platform.
select country, count(type) from users_data where gender = "M" group by country;
| Suède | 569 |
| France | 7050 |
| Allemagne | 1990 |
| Réunion | 11 |
| Danemark | 478 |
| Djibouti | 5 |
| Italie | 2031 |
| Etats-Unis | 3523 |
| Royaume-Uni | 2578 |
| Espagne | 1179 |
| Canada | 288 |
| Sénégal | 9 |
| Australie | 516 |
| Suisse | 192 |
| Belgique | 292 |
| Singapour | 62 |
| Brésil | 18 |
| Japon | 57 |
| Kowait | 8 |
| Martinique | 7 |
| Corée du Sud | 31 |
| Hong Kong | 106 |
| Thailande | 18 |
| Mexique | 55 |
| Finlande | 167 |
| Pakistan | 9 |
| Viet Nam | 18 |
| Russie | 64 |
| Nouvelle Zélande | 23 |
| Pays-Bas | 169 |
| Mongolie | 2 |
| Liban | 3 |
| Albanie | 12 |
| Guadeloupe | 13 |
| Cameroun | 8 |
| Roumanie | 79 |
| Paraguay | 2 |
| Colombie | 15 |
| Irlande | 73 |
| Malaisie | 26 |
| Portugal | 46 |
| Inde | 61 |
| Nigeria | 11 |
| Philippines | 13 |
| Chine | 60 |
| Maroc | 54 |
| Autriche | 88 |
| Cote D'Ivoire | 15 |
| Afrique du Sud | 21 |
| Tunisie | 30 |
| Indonésie | 21 |
| Taiwan | 34 |
| Norvège | 44 |
| Tajikistan | 2 |
| Cuba | 1 |
| Grèce | 32 |
| Luxembourg | 25 |
| Émirats arabes unis | 19 |
| Malte | 5 |
| Moldavie | 1 |
| Algérie | 29 |
| Guinée | 2 |
| Îles Turques-et-Caïques | 2 |
| Israel | 18 |
| Argentine | 13 |
| Qatar | 7 |
| République tchèque | 11 |
| Tanzanie | 3 |
| Pérou | 12 |
| Turquie | 20 |
| Belize | 4 |
| Pologne | 32 |
| Bulgarie | 15 |
| Guyane | 4 |
| Géorgie | 2 |
| Arabie Saoudite | 13 |
| Chili | 12 |
| Slovaquie | 12 |
| Anguilla | 1 |
| Lettonie | 8 |
| Ukraine | 23 |
| Bolivie | 1 |
| Jordanie | 4 |
| Chypre | 6 |
| Aruba | 2 |
| Congo | 10 |
| Monaco | 5 |
| Syrie | 1 |
| Ghana | 3 |
| Afghanistan | 5 |
| Angola | 3 |
| Polynésie Française | 1 |
| Azerbaïdjan | 4 |
| Éthiopie | 1 |
| Bahreïn | 3 |
| Macau | 5 |
| Panama | 2 |
| Kenya | 3 |
| Benin | 3 |
| Estonie | 5 |
| Myanmar | 4 |
| Croatie | 12 |
| Barbade | 1 |
| Ouganda | 1 |
| Le Salvador | 1 |
| Puerto Rico | 4 |
| Lituanie | 4 |
| Gabon | 4 |
| Liechtenstein | 1 |
| Chad | 1 |
| Bermude | 4 |
| République dominicaine | 4 |
| Andorre | 1 |
| Hongrie | 13 |
| Islande | 5 |
| Irak | 5 |
| Maurice | 2 |
| Togo | 2 |
| Équateur | 3 |
| Cambodge | 9 |
| ÃŽles Vierges britanniques | 1 |
| St Barthélémy | 1 |
| Bosnie et Herzegovine | 2 |
| Antigua et Barbuda | 1 |
| Serbie | 6 |
| Brunei Darussalam | 2 |
| Mali | 3 |
| Egypte | 3 |
| Bahamas | 1 |
| Jersey | 2 |
| Bangladesh | 4 |
| Kazakhstan | 1 |
| Îles Féroé | 1 |
| Biélorussie | 2 |
| Guam | 1 |
| Zaire | 1 |
| Macédoine | 2 |
| Zambie | 1 |
| Dominique | 1 |
| Venezuela | 2 |
| Costa Rica | 3 |
| Zimbabwe | 1 |
| Guernsey | 2 |
| Gambie | 1 |
| Libye | 1 |
| Fidji | 2 |
| Arménie | 1 |
| Madagascar | 2 |
| Samoa américaines | 2 |
| Slovénie | 1 |
| Antarctique | 1 |
| Oman | 1 |
| Guatemala | 1 |
| ÃŽle Bouvet | 1 |
| ÃŽles Vierges (U.S.) | 1 |
| Uruguay | 1 |
| Burkina Faso | 1 |
| Laos | 1 |
20. Calculate the average number of products sold and bought on ecommerce platform by male users for each country.
select country, avg(productsSold) as Sold_average, avg(productsBought) as Bought_average from users_data
where gender = "M" group by country;
| Suède | 0.0615 | 0.2179 |
| France | 0.0921 | 0.1901 |
| Allemagne | 0.0342 | 0.2196 |
| Réunion | 0.0000 | 0.0000 |
| Danemark | 0.0293 | 0.1444 |
| Djibouti | 0.0000 | 0.0000 |
| Italie | 0.4702 | 0.1709 |
| Etats-Unis | 0.0426 | 0.1425 |
| Royaume-Uni | 0.1412 | 0.2203 |
| Espagne | 0.1730 | 0.1527 |
| Canada | 0.0000 | 0.0972 |
| Sénégal | 0.0000 | 0.0000 |
| Australie | 0.0349 | 0.1492 |
| Suisse | 0.0313 | 0.1458 |
| Belgique | 0.0856 | 0.0890 |
| Singapour | 0.0000 | 0.6774 |
| Brésil | 0.0000 | 0.1111 |
| Japon | 0.0000 | 0.7018 |
| Kowait | 0.0000 | 0.0000 |
| Martinique | 0.0000 | 0.0000 |
| Corée du Sud | 0.0000 | 0.0323 |
| Hong Kong | 0.1415 | 0.2358 |
| Thailande | 0.0000 | 0.0000 |
| Mexique | 0.0000 | 0.0000 |
| Finlande | 0.0000 | 0.2455 |
| Pakistan | 0.0000 | 0.1111 |
| Viet Nam | 0.0000 | 0.0000 |
| Russie | 0.0000 | 0.0156 |
| Nouvelle Zélande | 0.0000 | 0.0000 |
| Pays-Bas | 0.4379 | 0.8225 |
| Mongolie | 0.0000 | 0.0000 |
| Liban | 0.0000 | 0.0000 |
| Albanie | 0.0000 | 0.0000 |
| Guadeloupe | 0.0000 | 0.0769 |
| Cameroun | 0.0000 | 0.0000 |
| Roumanie | 0.3038 | 0.4430 |
| Paraguay | 0.0000 | 0.0000 |
| Colombie | 0.0000 | 0.0000 |
| Irlande | 0.0000 | 0.1507 |
| Malaisie | 0.0000 | 0.0000 |
| Portugal | 0.0652 | 0.4348 |
| Inde | 0.0000 | 0.0000 |
| Nigeria | 0.0000 | 0.0000 |
| Philippines | 0.0000 | 0.0000 |
| Chine | 0.0000 | 0.0667 |
| Maroc | 0.0000 | 0.0000 |
| Autriche | 0.0909 | 0.5795 |
| Cote D'Ivoire | 0.0000 | 0.0000 |
| Afrique du Sud | 0.0000 | 0.0000 |
| Tunisie | 0.0000 | 0.0000 |
| Indonésie | 0.0000 | 0.0476 |
| Taiwan | 0.0000 | 0.1176 |
| Norvège | 0.0000 | 0.0000 |
| Tajikistan | 0.0000 | 0.0000 |
| Cuba | 0.0000 | 0.0000 |
| Grèce | 0.0313 | 0.1250 |
| Luxembourg | 0.0400 | 0.1200 |
| Émirats arabes unis | 0.0000 | 0.0000 |
| Malte | 0.0000 | 0.0000 |
| Moldavie | 0.0000 | 0.0000 |
| Algérie | 0.0000 | 0.0000 |
| Guinée | 0.0000 | 0.0000 |
| Îles Turques-et-Caïques | 0.0000 | 0.0000 |
| Israel | 0.0000 | 0.0000 |
| Argentine | 0.0000 | 0.0000 |
| Qatar | 0.0000 | 0.0000 |
| République tchèque | 0.0000 | 0.1818 |
| Tanzanie | 0.0000 | 0.0000 |
| Pérou | 0.0000 | 0.0000 |
| Turquie | 0.0000 | 0.1500 |
| Belize | 0.0000 | 0.0000 |
| Pologne | 0.4688 | 0.3750 |
| Bulgarie | 0.9333 | 2.8000 |
| Guyane | 0.0000 | 0.0000 |
| Géorgie | 0.0000 | 0.0000 |
| Arabie Saoudite | 0.0000 | 0.0000 |
| Chili | 0.0000 | 0.0000 |
| Slovaquie | 2.3333 | 0.0000 |
| Anguilla | 0.0000 | 0.0000 |
| Lettonie | 0.0000 | 0.0000 |
| Ukraine | 0.0000 | 0.0000 |
| Bolivie | 0.0000 | 0.0000 |
| Jordanie | 0.0000 | 0.0000 |
| Chypre | 0.0000 | 0.0000 |
| Aruba | 0.0000 | 0.0000 |
| Congo | 0.0000 | 0.0000 |
| Monaco | 0.0000 | 0.6000 |
| Syrie | 0.0000 | 0.0000 |
| Ghana | 0.0000 | 0.0000 |
| Afghanistan | 0.0000 | 0.0000 |
| Angola | 0.0000 | 0.0000 |
| Polynésie Française | 0.0000 | 0.0000 |
| Azerbaïdjan | 0.0000 | 0.0000 |
| Éthiopie | 0.0000 | 0.0000 |
| Bahreïn | 0.0000 | 0.0000 |
| Macau | 0.0000 | 0.0000 |
| Panama | 0.0000 | 0.0000 |
| Kenya | 0.0000 | 0.0000 |
| Benin | 0.0000 | 0.0000 |
| Estonie | 0.2000 | 0.6000 |
| Myanmar | 0.0000 | 0.0000 |
| Croatie | 0.0000 | 0.2500 |
| Barbade | 0.0000 | 0.0000 |
| Ouganda | 0.0000 | 0.0000 |
| Le Salvador | 0.0000 | 0.0000 |
| Puerto Rico | 0.0000 | 0.2500 |
| Lituanie | 0.0000 | 0.0000 |
| Gabon | 0.0000 | 0.0000 |
| Liechtenstein | 0.0000 | 0.0000 |
| Chad | 0.0000 | 0.0000 |
| Bermude | 0.0000 | 0.0000 |
| République dominicaine | 0.0000 | 0.0000 |
| Andorre | 0.0000 | 0.0000 |
| Hongrie | 0.0000 | 0.0000 |
| Islande | 0.2000 | 0.2000 |
| Irak | 0.0000 | 0.0000 |
| Maurice | 0.0000 | 0.0000 |
| Togo | 0.0000 | 0.0000 |
| Équateur | 0.0000 | 0.0000 |
| Cambodge | 0.0000 | 4.3333 |
| ÃŽles Vierges britanniques | 0.0000 | 0.0000 |
| St Barthélémy | 0.0000 | 0.0000 |
| Bosnie et Herzegovine | 0.0000 | 0.0000 |
| Antigua et Barbuda | 0.0000 | 0.0000 |
| Serbie | 0.0000 | 0.0000 |
| Brunei Darussalam | 0.0000 | 0.0000 |
| Mali | 0.0000 | 0.0000 |
| Egypte | 0.0000 | 0.3333 |
| Bahamas | 0.0000 | 0.0000 |
| Jersey | 0.0000 | 0.0000 |
| Bangladesh | 0.0000 | 0.0000 |
| Kazakhstan | 0.0000 | 0.0000 |
| Îles Féroé | 0.0000 | 0.0000 |
| Biélorussie | 0.0000 | 0.0000 |
| Guam | 0.0000 | 0.0000 |
| Zaire | 0.0000 | 0.0000 |
| Macédoine | 0.0000 | 0.0000 |
| Zambie | 0.0000 | 0.0000 |
| Dominique | 0.0000 | 0.0000 |
| Venezuela | 0.0000 | 0.0000 |
| Costa Rica | 0.0000 | 0.0000 |
| Zimbabwe | 0.0000 | 0.0000 |
| Guernsey | 0.0000 | 0.0000 |
| Gambie | 0.0000 | 0.0000 |
| Libye | 0.0000 | 0.0000 |
| Fidji | 0.0000 | 0.0000 |
| Arménie | 0.0000 | 0.0000 |
| Madagascar | 0.0000 | 0.0000 |
| Samoa américaines | 0.0000 | 0.0000 |
| Slovénie | 0.0000 | 0.0000 |
| Antarctique | 0.0000 | 0.0000 |
| Oman | 0.0000 | 0.0000 |
| Guatemala | 0.0000 | 0.0000 |
| ÃŽle Bouvet | 0.0000 | 0.0000 |
| ÃŽles Vierges (U.S.) | 0.0000 | 0.0000 |
| Uruguay | 0.0000 | 0.0000 |
| Burkina Faso | 0.0000 | 0.0000 |
| Laos | 0.0000 | 0.0000 |