My Goal: To find out which University has the larger amount of user (DISTINCT and COUNT in MySQLi).
I've been developing a survey website for Portugal, England and France.
In the survey some questions answer has predefined answer options.
For example: Gender, Living Country, Graduation Level (undergraduate, graduate, PhD, BBA etc)
But I also have questions where users need to write down the answers.
For example, University Name (where the user studied).
Two users filled the form as follow:
In this case the text "University of Glasgow" in English and the text "Universidade of Glasgow" in Portuguese is difference but it's the same institute.
So, these two institute has one user but the truth is this (as both are originally same University) University has two users.
My Question: How can I get the expected result?
I was planning to use Google translate but I it won't be accurate.
I also thought about to have all the University name in 3 languages but there are more than thousands of University, so it may not be efficient.
The structre I thought for table is,
survey_table
id, que_en, que_fr, que_pt, university_name
statistics_table
id, university_name, count
You could use localization for the university name. Check the docs here:
https://laravel.com/docs/5.7/localization
Make your users choose from a drop down list based on their locale (language)
Related
I have a column with a lot of rows more than 150k, each cell has a text, there is some cells has problems of having some sentences with capital letters I wanna fix this issue how can I filter them to know how many of them I have for example I have some cells like that I wanna detect the cells that has some capital sentences to be able to fix them:
Each year, They carefully curate the finest gifts to fill our Baskits
from new and wellloved brands, to unique products made exclusively for
us. They specialize in helping busy professionals give thoughtful,
impactful gifts for business development, colleague/employee
recognition, holiday gifts and more. Here are the top three things to
know about us: 1) They ARE CANADA'S LEADING GIFT DELIVERY SERVICE 30+
years of experience and 20, 000 customers 2) They MAKE THOUGHTFUL
GIFTING QUICK AND EASY Online and Mobile Webstore (Open 24/7) Call
Centre Gift Specialists Two Retail Stores (Downtown + North Toronto)
3) They HAVE DELIVERY OPTIONS TO SUIT YOUR NEEDS Delivery Across North
America sameday (and Saturday) Delivery in the GTA
try in A2:
=INDEX(REGEXMATCH(A2:A; "(.*)[A-Z]{2}(.*)")
or if you want a count:
=SUMPRODUCT(1*REGEXMATCH(A2:A; "(.*)[A-Z]{2}(.*)"))
Since it looks like you're in Google Sheets, just do a REGEXMATCH() for two capital letters in a row (as a review flag):
=BYROW(A2:A, LAMBDA(x, REGEXMATCH(x, "(.*)[A-Z]{2}(.*)"))
The BYROW() makes it a one-liner for the entire column. Ditch that if needed.
I'm creating a body-wax comparison website for my own project with cakephp4 and I'm stuck with a problem right now and I dunno what to do.
Situation:
There are multiple body-waxing companies, each company has many options for waxing like legs, arms,
beard etc. And each company has different price range for each waxing part.
CompanyA->arms = $60
CompanyA->legs = $30
CompanyB->arms = $50
I already connected to the Companies-table and Parts-table like the image below. Additionally, I came up with the idea of Prices-table too but I'm not sure if it's doable or I need to come up with something else.
Hopefully, I want to edit the price in the companies edit/add pages.
Any help I would appreciate.
(revised) I have a web app where information will be entered for a user. First and last name as well as 3 Affiliations (primary, secondary, and tertiary) associated with the person. Each affiliation has 3 components (title, department, and university). So for example one record could be for:
User: Bob, Robertson
Affiliation1: Professor, Chemistry, U. Florida
Affiliation2: Director, Amazing Chemistry Institute, U. Florida
Affiliation3: Affiliated Faculty, BioChemistry, Florida Tech.
Also, Title and Department are text input fields but Univ. refers to a specific list of about 3000 university names 'univ_name' which is why it has it's own table. also affiliationOrdinal would be something like (1st, 2nd, 3rd)
Users Affiliation Univ.
======= ============ =========
id_user id_affiliation id_univ
FirstName id_user univ_name
LastName affiliationOrdinal
title
department
id_univ
Thanks Sean for your feedback, I started thinking of this more as a user with multiple addresess type of problem and that has been solved many times over it seems. I picked this one as a reference. Mysql database design for customer multiple addresses and default address. So the above should be a bit closer to workable right?
I am new to database programming and am using sqlite and python. As an example lets say I have a database named Animals.db which I open with and get the cursor for in python. Now if I wanted to separate the animals by species I would have a different table per species and since it can get even more specific I would likely need something more specific than just a table of species.
I am a bit confused on how one allocates the correct data to the correct area of a database, how is it separated. Are there tables of tables?
if I wanted to lets say have a table for every land animal and another for every animal of the sea, but each table would need further specification(homo sapiens, etc), how can I do that?
Now if I wanted to separate the
animals by species I would have a
different table per species
Maybe. Maybe not. You might use a table that looked like this. It depends entirely on what you mean by "separate the animals by species". Here's one reasonable interpretation.
Animal_name Sex Species
------
Jack M Leopardus pardalis
Susie F Leopardus pardalis
Kimmie M Leopardus pardalis
Susie F Stenella clymene
Ginger F Stenella clymene
Mary Ann F Stenella clymene
To find all the Clymene dolphins, you might use a query along these lines.
select Animal_name
from animals
where species = 'Stenella clymene'
order by Animal_name
Animal_name
--
Ginger
Mary Ann
Susie
Start by collecting data. Your goal is to collect a set of representative sample data. Sample data, because the full population is too big to handle. Representative, because ideally it represents all the problems you're likely to run into with the full population. If "animal name" to you doesn't mean "Jack" or "Ginger", but "ocelot" and "Clymene dolphin", representative sample data will make that clear.
Address records are probably used in most database, but I've seen a number of slightly different sets of fields used to store them. The number of fields seems to vary from 3-7, and sometimes all fields are simple labelled address1..addressN, other times given specific meaning (town, city, etc).
This is UK specific, though I'm open to comments about the rest of the world too. Here you need the first line of the address (actually just the number) and the post code to identify the address - everything else is mostly an added bonus.
I'm currently favouring:
Address 1
Address 2
Address 3
Town
County
Post Code
We could add Country if we ever needed it (unlikely).
What do you think? Is this too little, too much?
The Post Office suggests (http://www.postoffice.co.uk/portal/po/content1?catId=19100182&mediaId=19100267) 7 lines:
Addressees Name
Company/Organisation
Building Name
Number of building and name of thoroughfare
Locality Name
Post Town
Post Code
They then say you do not need to include a County name provided the Post Town and Postcode are used.
The BSI have BS 7666 - that covers all addressing. I recommend you look there.
The 2000 version recommends
An address shall be based upon a logical data model comprising the following entities:
addressable object, with sub-types:
primary addressable object;
secondary addressable object;
street;
locality;
town;
administrative area, a.k.a. district;
county;
postcode.
See: http://landregistry.data.gov.uk/def/common/BS7666Address
I don't know whether this is minimal (I doubt it) but the heading on my cheque book says something pretty close to:
Lloyds TSB
Isle of Man Offshore Centre
Peveril Buildings
Peveril Square
Douglas
Isle of Man
IM99 0XX
United Kingdom
This causes fits when I try to enter it into the US banking system.
If I were you, I'd call Royal Mail and ask them... or look on their website for postcode lookup as a best practice.
There's different types of addresses, and each different type has a slightly different structure. Forward sorting offices have a different postal address structure than a residential home with a street number. What if the house has a name instead of a number? There are so many factors to consider.
Since I moved to Canada I had to do something similar and it's far more complicated than a straightforward residential address which generally has:
Street Number if applicable
Street Number Suffix if applicable
House Name
Street Name
Street Type
Street Direction if applicable
Unit Number for flats, townhouses or other types of building/location
Minor Municipality (Village)
Major Municipality (Major Town/City)
County
PostCode
Country if you include Scotland, Wales, Northern Ireland (and now I noticed Eire)
Then you get businesses that have their own Delivery Route, PO Boxes, Forward Sortation Offices...
It gets complicated in a real hurry.
Best bet - give Royal Mail a call and they should be able to give you information on their standard address templates.
EDIT: Your 3 field method isn't a bad one...particularly. However, data sanitization may be a significant issue using the field setup you have and you may need a fairly complex strategy for making sure that the address entered is valid. It's far easier to sanitize single dedicated fields to make sure input is correct than it is to parse various address tokens out of combined fields.
Another simpler way to gain this info is to go on the Royal Mail website and check their postcode lookup page.
On their main postcode lookup, they use 4 fields and I guess they have some form of validation on the street name/type field. They separate the house number and name and I guess they only allow major municipality. I'm assuming the county/country are assumed. If you break out their advanced search, they give you two extra fields for flat number and business name.
Given that some fields are combined on their site, you have to assume that there's some amount of validation to make sure that data entered can be gainfully used.
Premises elements
Sub Building Name
Building Name
Building Number
Organisation Name
Department Name
PO Box Number
Thoroughfare elements
Dependent Thoroughfare Name
Dependent Thoroughfare Descriptor
Thoroughfare Name
Thoroughfare Descriptor
Locality elements
Double Dependent Locality
Dependent Locality
Post Town
Postcode element
Postcode
This answer may be a few years late, but it's aimed at those like myself looking for guidance on how to correctly format postal addresses for both storing in a database (or the likes of it) and for printing purposes.
Taken from Royal Mail Doc, link below - conveniently titled the 'Programmers Guide'
Technical specififcation for users of PAF
Page 27 - 42 was most helpful for me.
It's very likely that a "UK" will be opened to Eire as well, and in some lines of business there will be legal differences, generally between Scotland / NI / the channel islands and England and Wales.
In short, I would add country to the list. Otherwise it's fine (no fewer certainly), though of course any address is traceable from a building reference, a post code and a country alone.
Where we live in France its just 3 lines:-
myname
village/location name
6 digit postcode followed by post town name in uppercase
Even from UK that's all that is required