SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'waldkraiburg' 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 'waldkraiburg' and action like 'hairdresser_%'  group by 1,2 order by ev desc limit 1
ROWS: 1
ROW 0: {"city":"Waldkraiburg","country":"Germany","ev":"610"}
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 'Waldkraiburg' and country like 'Germany' and action like 'hairdresser_%' group by 1 order by action desc
ROWS: 1
ROW 0: {"action":"0","events":"610"}
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 'Germany' and action like 'hairdresser_%' group by 1 order by action desc
ROWS: 5
ROW 0: {"action":"30","events":"621"}
ROW 1: {"action":"25","events":"296"}
ROW 2: {"action":"20","events":"1166"}
ROW 3: {"action":"10","events":"5363"}
ROW 4: {"action":"0","events":"7262"}
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 'Germany' and action like 'hairdresser%' group by 1,2) g group by 1
ROWS: 15
ROW 0: {"region":"Baden-Wurttemberg","action":"13660","events":"2058"}
ROW 1: {"region":"Bavaria","action":"3550","events":"2009"}
ROW 2: {"region":"Berlin","action":"7980","events":"2219"}
ROW 3: {"region":"Brandenburg","action":"20","events":"614"}
ROW 4: {"region":"Bremen","action":"10","events":"2"}
ROW 5: {"region":"Hamburg","action":"27210","events":"2607"}
ROW 6: {"region":"Hesse","action":"17365","events":"2061"}
ROW 7: {"region":"Lower Saxony","action":"130","events":"650"}
ROW 8: {"region":"North Rhine-Westphalia","action":"310","events":"702"}
ROW 9: {"region":"Rhineland-Palatinate","action":"26800","events":"1151"}
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 'Germany' 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: 19
ROW 0: {"lat":"44.4686696","lon":"-71.1850768","city":"Berlin","action":"7980","events":"2219"}
ROW 1: {"lat":"48.1351253","lon":"11.5819805","city":"Munich","action":"115","events":"514"}
ROW 2: {"lat":"48.3705449","lon":"10.89779","city":"Augsburg","action":"450","events":"45"}
ROW 3: {"lat":"48.7074558","lon":"9.0044053","city":"Sindelfingen","action":"0","events":"81"}
ROW 4: {"lat":"49.0068901","lon":"8.4036527","city":"Karlsruhe","action":"6100","events":"611"}
ROW 5: {"lat":"49.3987524","lon":"8.6724335","city":"Heidelberg","action":"35","events":"3"}
ROW 6: {"lat":"49.4521018","lon":"11.0766654","city":"Nuremberg","action":"1510","events":"77"}
ROW 7: {"lat":"49.8728253","lon":"8.6511929","city":"Darmstadt","action":"0","events":"426"}
ROW 8: {"lat":"50.1109221","lon":"8.6821267","city":"Frankfurt","action":"6725","events":"964"}
ROW 9: {"lat":"50.3569429","lon":"7.5889959","city":"Koblenz","action":"0","events":"123"}
SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'Waldkraiburg' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where city like 'Waldkraiburg' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT * FROM joe where lower(city) like 'Waldkraiburg' and country like 'Germany' and action like '{$action_string}__%' order by events desc ROWS: 0 How much should I tip a hairdresser in Waldkraiburg? | Joe tips, be like Joe

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

In Waldkraiburg, Germany ?


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

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




In all of Germany?


Amazingly enough, 51% said they would tip a Hairdresser (or Barber, Hair stylist, etc.).
621 people tip 30% 296 people tip 25% 1166 people tip 20% 5363 people tip 10% 7262 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 Germany?

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 'Waldkraiburg'  order by events desc limit 1 ) b   on a.country = b.country_2 where country_2 is not null  and city not like 'Waldkraiburg' and city not like '(not set)' group by 1 order by 2 desc ) yo  limit 25
ROWS: 25
ROW 0: {"city":"Berlin"}
ROW 1: {"city":"Hamburg"}
ROW 2: {"city":"Frankfurt"}
ROW 3: {"city":"Munich"}
ROW 4: {"city":"Stuttgart"}
ROW 5: {"city":"Cologne"}
ROW 6: {"city":"Nuremberg"}
ROW 7: {"city":"Hanover"}
ROW 8: {"city":"Freiburg im Breisgau"}
ROW 9: {"city":"Heidelberg"}
Berlin   -  Hamburg   -  Frankfurt   -  Munich   -  Stuttgart   -  Cologne   -  Nuremberg   -  Hanover   -  Freiburg im Breisgau   -  Heidelberg   -  Wiesbaden   -  Bonn   -  Gottingen   -  Essen   -  Herne   -  Dresden   -  Koblenz   -  Karlsruhe   -  Dreieich   -  Mannheim   -  Detmold   -  Weiden   -  Gera   -  Muhldorf   -  Erkner   -  

Other resources



SQL: SELECT * FROM joe_serp WHERE city like 'Waldkraiburg'
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 'Waldkraiburg' group by 1 order by 2 desc  limit 100) c ORDER BY RAND() limit 20
ROWS: 20
ROW 0: {"city":"Houston"}
ROW 1: {"city":"Bangkok"}
ROW 2: {"city":"Prague"}
ROW 3: {"city":"Auckland"}
ROW 4: {"city":"Sofia"}
ROW 5: {"city":"London"}
ROW 6: {"city":"Dallas"}
ROW 7: {"city":"Victoria"}
ROW 8: {"city":"San Antonio"}
ROW 9: {"city":"Hamburg"}
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