SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'neckarsulm' 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 'neckarsulm' 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 action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as  action,sum(events) events FROM joe where lower(city) like 'neckarsulm' and country like '%' and action like 'hairdresser2_%' group by 1 order by action desc
ROWS: 0
SQL: SELECT case when action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as  action,sum(events) events FROM joe where country like '%' and action like 'hairdresser2_%' group by 1 order by action desc
ROWS: 0
SQL: SELECT region, sum(action*events) action, sum(events) events from (SELECT case when action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as  action, region,sum(events) events FROM joe where country like '%' and action like 'hairdresser2%' group by 1,2) g group by 1
ROWS: 0
SQL: SELECT country, sum(action*events) action, sum(events) events from (SELECT case when action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as  action, country,sum(events) events FROM joe where country not like '(not set)' and action like 'hairdresser2%' group by 1,2) g group by 1 having sum(events)>4
ROWS: 0
SQL: SELECT lat, lon,t.city city, sum(action*events) action, sum(events) events from (SELECT case when action like '%_20' then 10 when action like '%_15' then 5 when action like '%_13' then 2 when action like '%_12' then 1 else 0 end as  action, city,sum(events) events FROM joe where country like '%' and action like 'hairdresser2%' 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: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'neckarsulm' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where city like 'neckarsulm' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT * FROM joe where lower(city) like 'neckarsulm' and country like '%' and action like '{$action_string}__%' order by events desc ROWS: 0 How much should I tip a hairdresser in neckarsulm? | Joe tips, be like Joe

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

In neckarsulm, % ?


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

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 'hairdresser2_%') then events else 0 end) as love, sum(events) users from joe where action like 'hairdresser2_%' ;
ROWS: 1
ROW 0: {"countries":"0","cities":"0","love":null,"users":null}

How big is our data?


0

CITIES

0

Countries

USERS

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 'neckarsulm'  order by events desc limit 1 ) b   on a.country = b.country_2 where country_2 is not null  and city not like 'neckarsulm' 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   -  Muhldorf   -  Gera   -  Erkner   -  Oberkochen   -  Walldorf   -  

Other resources



SQL: SELECT * FROM joe_serp WHERE city like 'neckarsulm'
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 'neckarsulm' group by 1 order by 2 desc  limit 100) c ORDER BY RAND() limit 20
ROWS: 20
ROW 0: {"city":"Burnaby"}
ROW 1: {"city":"Christchurch"}
ROW 2: {"city":"Tallinn"}
ROW 3: {"city":"Phoenix"}
ROW 4: {"city":"Brussels"}
ROW 5: {"city":"Victoria"}
ROW 6: {"city":"Philadelphia"}
ROW 7: {"city":"Orlando"}
ROW 8: {"city":"Kuala Lumpur"}
ROW 9: {"city":"Berlin"}
Tipping in Zagreb , Tipping in Boston , Tipping in Riga , Tipping in Wellington , Tipping in Ottawa , Tipping in Munich , Tipping in Tallinn , Tipping in Brussels , Tipping in Vancouver , Tipping in Denver , Tipping in Glasgow , Tipping in Sacramento , Tipping in Sandton , Tipping in Irvine , Tipping in Burnaby , Tipping in Brisbane , Tipping in Beirut , Tipping in Los Angeles , Tipping in Miami , Tipping in Nottingham ,

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