SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'simpang_ampat' 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 'simpang_ampat' 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 'simpang_ampat' 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 'simpang_ampat' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT city,country,sum(events) ev FROM `joe` where city like 'simpang_ampat' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0
SQL: SELECT * FROM joe where lower(city) like 'simpang_ampat' and country like '%' and action like '{$action_string}__%' order by events desc ROWS: 0 How much should I tip a hairdresser in simpang_ampat? | Joe tips, be like Joe

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

In simpang_ampat, % ?


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 'simpang_ampat'  order by events desc limit 1 ) b   on a.country = b.country_2 where country_2 is not null  and city not like 'simpang_ampat' and city not like '(not set)' group by 1 order by 2 desc ) yo  limit 25
ROWS: 25
ROW 0: {"city":"Kuala Lumpur"}
ROW 1: {"city":"Shah Alam"}
ROW 2: {"city":"Kota Kinabalu"}
ROW 3: {"city":"Petaling Jaya"}
ROW 4: {"city":"Kuching"}
ROW 5: {"city":"Subang Jaya"}
ROW 6: {"city":"Johor Bahru"}
ROW 7: {"city":"Kajang"}
ROW 8: {"city":"Miri"}
ROW 9: {"city":"Ampang Jaya"}
Kuala Lumpur   -  Shah Alam   -  Kota Kinabalu   -  Petaling Jaya   -  Kuching   -  Subang Jaya   -  Johor Bahru   -  Kajang   -  Miri   -  Ampang Jaya   -  Puchong   -  George Town   -  Sungai Petani   -  Batu Caves   -  Malacca   -  Butterworth   -  Bayan Lepas   -  Klang   -  Ipoh   -  Seremban   -  Bandar Tun Razak   -  Kuantan   -  Rawang   -  Seri Kembangan   -  Bukit Mertajam   -  

Other resources



SQL: SELECT * FROM joe_serp WHERE city like 'simpang_ampat'
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 'simpang_ampat' group by 1 order by 2 desc  limit 100) c ORDER BY RAND() limit 20
ROWS: 20
ROW 0: {"city":"Berlin"}
ROW 1: {"city":"Orlando"}
ROW 2: {"city":"Birmingham"}
ROW 3: {"city":"Warsaw"}
ROW 4: {"city":"Helsinki"}
ROW 5: {"city":"Wellington"}
ROW 6: {"city":"Ottawa"}
ROW 7: {"city":"Bristol"}
ROW 8: {"city":"Istanbul"}
ROW 9: {"city":"Chicago"}
Tipping in Christchurch , Tipping in London , Tipping in Canberra , Tipping in Munich , Tipping in Oslo Municipality , Tipping in Nottingham , Tipping in Nashville , Tipping in Calgary , Tipping in Cape Town , Tipping in Zurich , Tipping in Winnipeg , Tipping in Bangkok , Tipping in Sydney , Tipping in Liverpool , Tipping in Vienna , Tipping in New York , Tipping in Irvine , Tipping in Copenhagen , Tipping in Edinburgh , Tipping in San Francisco ,

Talk about tipping