SQL: SELECT city,country,sum(events) ev FROM `joe` where country like 'pijnacker' 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 'pijnacker' 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 'pijnacker' 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 'pijnacker' 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 'pijnacker' and action like '{$action_string}_%'  group by 1,2 order by ev desc limit 1
ROWS: 0

Colorlib app

C

Everything You Need. To Start Selling Online Beautifully

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

In pijnacker, % ?

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 by state or region

Touch anywhere on the map for stats

We know this becuase you told us!

The data you see here is driven by users like you, answering a simple question on a different website. Do you drink the tap water where you live?

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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}

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 'pijnacker'  order by events desc limit 1 ) b   on a.country = b.country_2 where country_2 is not null  and city not like 'pijnacker' and city not like '(not set)' group by 1 order by 2 desc ) yo  limit 25
ROWS: 25
ROW 0: {"city":"Amsterdam"}
ROW 1: {"city":"The Hague"}
ROW 2: {"city":"Eindhoven"}
ROW 3: {"city":"Rotterdam"}
ROW 4: {"city":"Groningen"}
ROW 5: {"city":"Utrecht"}
ROW 6: {"city":"Almere"}
ROW 7: {"city":"Breda"}
ROW 8: {"city":"Alkmaar"}
ROW 9: {"city":"Katwijk aan Zee"}

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

Why even tip?

“ I have been using it for a number of years. I use Colorlib for usability testing. It's great for taking images and making clickable image prototypes that do the job and save me the coding time and just the general hassle of hosting. ”

Aigars Silkalns

Ceo Colorlib

“ I use Colorlib for usability testing. It's great for taking images and making clickable image prototypes that do the job and save me the coding time and just the general hassle of hosting. ”

Jennifer

Developer

“ I have been using it for a number of years. I use Colorlib for usability testing. It's great for taking images and making clickable image prototypes that do the job.”

Helen

Marketer

“ I have been using it for a number of years. I use Colorlib for usability testing. It's great for taking images and making clickable image prototypes that do the job and save me the coding time and just the general hassle of hosting. ”

Henry smith

Developer

SQL: SELECT city from ( SELECT city,sum(events) FROM joe  WHERE city not like '(not set)' and city not like 'pijnacker' group by 1 order by 2 desc  limit 100) c ORDER BY RAND() limit 20
ROWS: 20
ROW 0: {"city":"Istanbul"}
ROW 1: {"city":"Philadelphia"}
ROW 2: {"city":"Toronto"}
ROW 3: {"city":"Nottingham"}
ROW 4: {"city":"Mississauga"}
ROW 5: {"city":"Sacramento"}
ROW 6: {"city":"Kuala Lumpur"}
ROW 7: {"city":"Canberra"}
ROW 8: {"city":"San Francisco"}
ROW 9: {"city":"Stockholm"}