I'm looking to get a city to country mapping without an IP address
I have access to these files on my box:
GeoIP2Country.mmdb
GeoIPCountry.dat
GeoIP2City.mmdb
GeoIPCity.dat
GeoIP2ISP.mmdb
GeoIP2Connections.mmdb
Normally the way I would use this is GeoIP2Country.country(cip).country.name and it would return a country name for the IP I feed it.
In my use case I want to provide it with a city name and have it return a country name. Since all the data is in there this would save me a lot of time. Is it possible to query mmdb (no idea how to do this) then convert that to a dataframe so I can just have a df of country to city mapping or vise versa?
based on this :Query by city name on geolite2 .mmdb file (JAVA) I cant do what I wnated to.
BUT there is also a country_code.csv I think thats offered by maxmind which does what I need in conjunction with some other non mmdb files.
Related
For country and state, there are ISO numbers. With City, there is not.
Method 1:
Store in one column:
[Country ISO]-[State ISO]-[City Name]
Method 2:
Store in 3 separate columns.
Also, how to handle city names if there is no unique identifier?
First and foremost, three separate columns to keep your data. If you want to create a unique identifier, the easiest way would be giving a random 3-10 digit code depending on the size of your data set. However, I would suggest concatenating [country-code]-[state-code]-[code] if you have a small data set and if you want human readability to a certain point. code can be several things. Here are some ideas:
of course a random id or even a database row id
licence plate number/code if there is for a city
phone area code of the city or the code of the center
same logic may apply to zip codes
combination of latitude and longitude of the city center up to certain degree
Here are also more references that can be used:
ISO 3166 is a country codes. In there you can find codes for states or cities depending on the country.
As mentioned IATA has both Airport and City codes list but they are hard to obtain.
UN Location list is a good mention but it can be difficult to gather the levels of differentiation, like the airport code or city code or a borough code can be on the same list, but eventually the UN/LOCODE must be unique. (Airport codes are used for ICAO, similar to IATA but not the same)
there are several data sets out there like OpenTravelData or GeoNames that can be used for start but may require digging and converting. They provide unique codes for locations. And many others can be found.
Bonus:
I would suggest checking Schema.org's City Schema and other Place Schemas for a conscious setup.
I have an task to store data about destinations of delivery, where companies can ship the postal parcel.
The trivial way is to create a table
CompanyShippmentPlaces
id | country | city
There are the some design issues:
What if need be delivered to towns or villages, not to cities? That means altering a table?
What if company needs to specify a part of city, townm or village?
What if the destinations have the same name?
How I plan to use this data:
When system gest a order, the order should be distributes across all companies. I must get all companies that can deliver this product.
It pushes me to use noSQL database, but I am not confident.
What do you think about that?
What if need be delivered to towns or villages, not to cities? That means altering a table?
This would be solved by the solution of jaimish11.
Peronsaly I would change the naming of "City" to "locality" (or something comparable - to generalize).
What if company needs to specify a part of city, townm or village?
I think this is solved by the address lines.
What if the destinations have the same name?
Normaly (as much that i know) each location in a country has it's own pin- or zipcode respectively if the naming doesn't match the post will use the code to identify the location. (to be sure you should ask the post in your at least in your country)
When system gest a order, the order should be distributes across all companies. I must get all companies that can deliver this product.
I would get all locations where the products are available and then get the location wich is next by the city out of the first selection. Maybe you could save the nearest location to a city in your "city table".
The issue you're describing isn't actually an issue. No matter what database you use (SQL or NoSQL) you can simply have all the address fields you need such as:
Address Line 1
Address Line 2
Landmark
City
Pincode/ Zipcode
State
Country
This way, it won't matter whether it's city, town or village.
i have a database having country, city, state and hotels in these table country name has multiple identical records for eg mexico is wrongly spelled as maxico and mxico and mexico,other records like usa and united states of america and america these type of records are having mutiple same wrongly spelled states and states has multiple wrong spelled cities but hotels are unique and i want them to set them to there right city and state and country for eg. some hotel is in chicago city Illinois state and country is usa. please help me how can i fix this
you could do an update if you know all the different scenarios that are incorrect
update tbl
set city = 'Mexico'
where city in ('maxico', 'mxico')
Well,you can list all values the country column has,and then check wether the values is right, if it is wrong, just use update clause to fix the wrong value, like below:
update my_table set country = 'Mexico' where country in ('maco', 'xico');
It depends on infrastructure you're running.
If you have access to some ETL tools, they often have DataQuality capabilities, often with databases used in correcting adresses. Those are often paid.
If you are a "private" developer, then you might not want to use paid data, so you can look for open data sources, like https://catalog.data.gov allegheny country addresses.
You can use multitude of algorithms and solutions, ranging from simple distances in word space to neural networks pre-trained to do just that.
This type of data problem is hard. There is no built-in simple way to determine the "right spelling". Many databases have one of two capabilities built in that can help -- either "soundex" algorithms or Levenshtein distance.
What should you do? If you really want to fix this problem, create a table with the misspelled name and the correct value that you want. This table will need to be maintained manually, such as in a spreadsheet. Then use this table when importing data and use only the rectified value.
Better yet, set up a reference table with only the correct names. Create a second table with alternative names, which is maintained as above.
As part of addresses I am storing in my SQL database country codes (e.g. US, DE,...). I then have another table (with two columns) in my database which translates the country codes to the English language names of the respective countries.
If I want to make the site multi-language, I could expand this translation table adding country names in other languages than English.
I was wondering if there is another method which does not involve modification of the database, e.g. using gettext to translate the English country names?
The typical way to handle this is to change the table structure to have three columns, instead of two:
Language
CounryCode
FullName
Whenever you query the database, you would provide the current language.
You then have to change your code to include the additional language key in any queries.
Depending on how you are going to keep track of the current language, you would also use a view or user defined function.
You don't want to use automated translation, since the name of a country like "China" could turn into the equivalent of "porcelain".
Is there a way to programmatically determine what School District a given physical street address in the US is tied to?
The US Census Bureau coordinates with local school districts from each state to understand boundaries along with any changes. This information is published every other year by the Census Bureau itself in their "Tiger" data:
http://www.census.gov/did/www/schooldistricts/data/boundaries.html
(A relatively easy way to read the data is using PostGIS under PostgreSQL)
But before all of that, you need to make sure you're working with a correct address. The reason is that the address may not even exist at all or may be formatted incorrectly such that you are unable to determine a match. Furthermore, if the ZIP Code is wrong or street information is misspelled, or the person accidentally reversed the "North" or "South" part of an address, e.g. 123 North Main Street, that could put the coordinate in the wrong school district. So as a precursor to running your addresses through PostGIS, you'll definitely want to look at using an address verification service to make sure you've got good data to start with. (Full disclosure: I'm the founder of SmartyStreets, we do address verification.)