SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'canakkale' and action like 'hairdresser_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where city like 'canakkale' and action like 'hairdresser_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT 	sVal FROM `joe_settings` where sTopic like 'hairdresser' and sName like 'color'
ROWS: 5
ROW 0: {"sVal":"'25' => '#f2b434'"}
ROW 1: {"sVal":"'>25' => '#990099'"}
ROW 2: {"sVal":"'20' => '#259c5d'"}
ROW 3: {"sVal":"'10' => '#4882ef'"}
ROW 4: {"sVal":"'0' => '#d7483f'"}
SQL: SELECT 	sVal FROM `joe_settings` where sTopic like 'hairdresser' and sName like 'nice'
ROWS: 1
ROW 0: {"sVal":"a Hairdresser (or Barber, Hair stylist, etc.)"}
SQL: SELECT 	sVal FROM `joe_settings` where sTopic like 'hairdresser' and sName like 'niceTagline'
ROWS: 0
SQL: SELECT CASE
        WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30
        ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED)
    END AS action,sum(events) events FROM joe where lower(city) like 'canakkale' and country like '%' and action like 'hairdresser_%' group by 1 order by action desc
ROWS: 0
SQL: SELECT CASE
        WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30
        ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED)
    END AS action,sum(events) events FROM joe where country like '%' and action like 'hairdresser_%' group by 1 order by action desc
ROWS: 5
ROW 0: {"action":"30","events":"20802"}
ROW 1: {"action":"25","events":"19308"}
ROW 2: {"action":"20","events":"126359"}
ROW 3: {"action":"10","events":"137544"}
ROW 4: {"action":"0","events":"395482"}
SQL: SELECT region, sum(action*events) action, sum(events) events from (SELECT CASE
        WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30
        ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED)
    END AS action, region,sum(events) events FROM joe where country like '%' and action like 'hairdresser%' group by 1,2) g group by 1
ROWS: 638
ROW 0: {"region":"(not set)","action":"66365","events":"18155"}
ROW 1: {"region":"Aargau","action":"30","events":"5"}
ROW 2: {"region":"Abruzzo","action":"0","events":"1"}
ROW 3: {"region":"Abu Dhabi","action":"16730","events":"1342"}
ROW 4: {"region":"Adana","action":"0","events":"1"}
ROW 5: {"region":"Administrative unit Maribor","action":"0","events":"1"}
ROW 6: {"region":"Aguascalientes","action":"0","events":"1"}
ROW 7: {"region":"Aichi","action":"1260","events":"381"}
ROW 8: {"region":"Aichi Prefecture","action":"0","events":"2"}
ROW 9: {"region":"Akershus","action":"10","events":"7"}
SQL: SELECT country, sum(action*events) action, sum(events) events from (SELECT CASE
        WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30
        ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED)
    END AS action, country,sum(events) events FROM joe where country not like '(not set)' and action like 'hairdresser%' group by 1,2) g group by 1 having sum(events)>4
ROWS: 100
ROW 0: {"country":"Algeria","action":"10","events":"40"}
ROW 1: {"country":"Argentina","action":"4210","events":"249"}
ROW 2: {"country":"Armenia","action":"0","events":"321"}
ROW 3: {"country":"Aruba","action":"20","events":"55"}
ROW 4: {"country":"Australia","action":"95735","events":"68880"}
ROW 5: {"country":"Austria","action":"8645","events":"1110"}
ROW 6: {"country":"Bahrain","action":"2880","events":"290"}
ROW 7: {"country":"Bangladesh","action":"55","events":"339"}
ROW 8: {"country":"Belgium","action":"1135","events":"5256"}
ROW 9: {"country":"Bermuda","action":"420","events":"21"}
SQL: SELECT lat, lon,t.city city, sum(action*events) action, sum(events) events from (SELECT CASE
        WHEN LOWER(action) LIKE 'hairdresser_>25' THEN 30
        ELSE CAST(REPLACE(LOWER(action),'hairdresser_','') AS UNSIGNED)
    END AS action, city,sum(events) events FROM joe where country like '%' and action like 'hairdresser%' group by 1,2) t left join citiesLatLon ltln on t.city = ltln.city where lat is not null and t.city not like '(not set)' group by 1,2,3 having sum(events)>2
ROWS: 888
ROW 0: {"lat":"","lon":"","city":"Cebu City","action":"3960","events":"392"}
ROW 1: {"lat":"-12.0734497","lon":"-77.0162899","city":"La Victoria","action":"60","events":"4"}
ROW 2: {"lat":"-15.7666707","lon":"35.0167866","city":"Blantyre","action":"20","events":"219"}
ROW 3: {"lat":"-16.9185514","lon":"145.7780548","city":"Cairns","action":"40","events":"854"}
ROW 4: {"lat":"-19.2589635","lon":"146.8169483","city":"Townsville","action":"0","events":"1385"}
ROW 5: {"lat":"-23.5505199","lon":"-46.6333094","city":"Sao Paulo","action":"2150","events":"264"}
ROW 6: {"lat":"-25.4244287","lon":"-49.2653819","city":"Curitiba","action":"40","events":"3"}
ROW 7: {"lat":"-25.7478676","lon":"28.2292712","city":"Pretoria","action":"45","events":"41"}
ROW 8: {"lat":"-26.1075663","lon":"28.0567007","city":"Sandton","action":"65","events":"4"}
ROW 9: {"lat":"-26.1201355","lon":"27.9014654","city":"Roodepoort","action":"0","events":"83"}
SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'canakkale' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where city like 'canakkale' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT * FROM joe where lower(city) like 'canakkale' and country like '%' and action like '{$action_string}__%' order by events desc ROWS: 0 How much should I tip a hairdresser in canakkale? | Joe tips, be like Joe

How much do you tip a Hairdresser (or Barber, Hair stylist, etc.)?

In canakkale, % ?


Sadly, only 0% said they would tip a Hairdresser (or Barber, Hair stylist, etc.).


Find out what to tip your: Hairdresser, food delivery person, taxi driver




In all of %?


Sadly, only 43% said they would tip a Hairdresser (or Barber, Hair stylist, etc.).
20802 people tip 30% 19308 people tip 25% 126359 people tip 20% 137544 people tip 10% 395482 people tip 0%

Tipping around the world



SQL: Select count(distinct country) countries,count(distinct city) cities,sum(case when action not in (select min(action) from joe where  action like 'hairdresser_%') then events else 0 end) as love, sum(events) users from joe where action like 'hairdresser_%' ;
ROWS: 1
ROW 0: {"countries":"145","cities":"4093","love":"304013","users":"699495"}

How big is our data?


4093

CITIES

145

Countries

699495

USERS

304013

Tip more than 0%

Tipping by city

Looking for other cities in %?

SQL: SELECT city from (SELECT city,sum(events) FROM ( SELECT * FROM joe) a  left join ( select country country_2  FROM joe  where lower(city) like 'canakkale'  order by events desc limit 1 ) b   on a.country = b.country_2 where country_2 is not null  and city not like 'canakkale' and city not like '(not set)' group by 1 order by 2 desc ) yo  limit 25
ROWS: 14
ROW 0: {"city":"Istanbul"}
ROW 1: {"city":"Izmir"}
ROW 2: {"city":"Ankara"}
ROW 3: {"city":"Antalya"}
ROW 4: {"city":"Denizli"}
ROW 5: {"city":"Samsun"}
ROW 6: {"city":"Kayseri"}
ROW 7: {"city":"Fethiye"}
ROW 8: {"city":"Bursa"}
ROW 9: {"city":"Adana"}
Istanbul   -  Izmir   -  Ankara   -  Antalya   -  Denizli   -  Samsun   -  Kayseri   -  Fethiye   -  Bursa   -  Adana   -  Gebze   -  Mersin   -  Manisa   -  Sanliurfa   -  

Other resources



SQL: SELECT * FROM joe_serp WHERE city like 'canakkale'
ROWS: 0

Why even tip?



Looking to download our data?

You can find the latest file here latest.csv (208.5 kb)

Looking for other cities in the world?

SQL: SELECT city from ( SELECT city,sum(events) FROM joe  WHERE city not like '(not set)' and city not like 'canakkale' group by 1 order by 2 desc  limit 100) c ORDER BY RAND() limit 20
ROWS: 20
ROW 0: {"city":"Edmonton"}
ROW 1: {"city":"Saskatoon"}
ROW 2: {"city":"Glasgow"}
ROW 3: {"city":"Nottingham"}
ROW 4: {"city":"Munich"}
ROW 5: {"city":"Riga"}
ROW 6: {"city":"Washington"}
ROW 7: {"city":"Adelaide"}
ROW 8: {"city":"Victoria"}
ROW 9: {"city":"Copenhagen"}
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