Mitsubishi Electric Elevator Branch Offices
U.S. Location Dataset // 15

Every branch office listed on the contact page of Mitsubishi Electric's US elevator and escalator division. Each row has the branch name, the region it serves, street address and suite, city, state, ZIP and phone, with fax where published. The branches are in 10 states, led by California. Mitsubishi publishes no coordinates, so each address was matched with the US Census geocoder: 14 at address level and 1 at its ZIP's centre. County and county FIPS are added.

What we did to this data: Added coordinates to 15 listings, added the county to 15 listings, re-placed 0 misplaced map points, flagged 0 incomplete addresses and measured 15 rows. Rebuilt September 29, 2026 from mitsubishielevator.com.

How complete the key fields are: phone 100%, website 100%, street address 100%, city 100%, state 100%, ZIP code 100%, latitude 100%, longitude 100%. 20 of 22 columns are filled on at least half the rows.

15Locations
10States
22Data Fields
September 29, 2026File built

Need just some of them? Ask in your own words.

●Where the rows are

Map of where the Mitsubishi Electric Elevator Branch Offices are
One dot for every ZIP code with at least one location. Ask above for any part of it: a state, a city, a distance.

{}Data Fields

company100%name100%locationType100%address100%address253%city100%state100%zip100%country100%phone100%fax7%website100%sourceUrl100%branchName100%region100%latitude100%longitude100%geo_precision100%county100%county_fips100%county_note13%address_quality100%

The percentage is how much of the file carries that field, measured on the delivered CSV rather than estimated. 2 of 22 fields are populated on under half the rows (fax, county_note).

How complete each column is
ColumnRows filled
company100%
name100%
locationType100%
address100%
address253%
city100%
state100%
zip100%
country100%
phone100%
fax7%
website100%
sourceUrl100%
branchName100%
region100%
latitude100%
longitude100%
geo_precision100%
county100%
county_fips100%
county_note13%
address_quality100%

≡Sample Data Preview

mitsubishi-electric-elevator-branch-offices.csv — 5 of 15 rows, 22 of 22 columns · scroll →UTF-8
companysourceUrlnamelocationTypeaddressaddress2citystatezipcountryphonefaxwebsitebranchNameregionlatitudelongitudegeo_precisioncountycounty_fipscounty_noteaddress_quality
Mitsubishi Electric Elevatorhttps://mitsubishielevator.com/contact-usMitsubishi Electric Elevator – Los Angeles/Orange CountyBranch office5900-A Katella AvenueCypressCA90630US714-220-4700714-844-4564https://mitsubishielevator.com/contact-usLos Angeles/Orange CountySouthern California33.802832-118.031061addressOrange County06059ZIP 90630 spans 2 counties; assigned to the county holding 99% of its land areacomplete
Mitsubishi Electric Elevatorhttps://mitsubishielevator.com/contact-usMitsubishi Electric Elevator – HawaiiBranch office99-075 Koaha WaySuite AAieaHI96701US808-486-0433https://mitsubishielevator.com/contact-usHawaiiHawaii21.373188-157.902335addressHonolulu County15003complete
Mitsubishi Electric Elevatorhttps://mitsubishielevator.com/contact-usMitsubishi Electric Elevator – BostonBranch office6-K Gill StreetWoburnMA01801US781-799-4069https://mitsubishielevator.com/contact-usBostonMassachusetts42.508755-71.146537addressMiddlesex County25017complete
Mitsubishi Electric Elevatorhttps://mitsubishielevator.com/contact-usMitsubishi Electric Elevator – NevadaBranch office5850 Polaris Ave.Suite 1000Las VegasNV89118US858-880-0806https://mitsubishielevator.com/contact-usNevadaNevada36.083464-115.185508addressClark County32003complete
Mitsubishi Electric Elevatorhttps://mitsubishielevator.com/contact-usMitsubishi Electric Elevator – Dallas-Fort WorthBranch office196 Freeport ParkwaySuite 140CoppellTX75019US214-984-9479https://mitsubishielevator.com/contact-usDallas-Fort WorthTexas32.967490-97.014908addressDallas County48113ZIP 75019 spans 2 counties; assigned to the county holding 98% of its land areacomplete
Showing 5 real rows from the file, all 22 columns that carry data in them. The free sample file has up to 10 rows.

✓Where this data comes from

Each row names the public source it came from, so any record can be checked against where it was published.

September 29, 2026

File built

22 fields

Columns filled on at least 1% of rows

Fill measured

On every row of the delivered file

How we build and date every file: methodology.

Use this list from ChatGPT or Claude

No setup needed. Ask ChatGPT or Claude your question about the Mitsubishi Electric Elevator Branch Offices and give it this page: it can open https://locationlists.com/find?dataset=mitsubishi-electric-elevator-branch-offices with the filters you need and show you the count and price.

Using ChatGPT or Claude? Tell it to answer from locationlists.com/find — no account, no connector.

How assistants ask

No connector needed. Any AI assistant can answer from this site with a web link, no connector, no account: open https://locationlists.com/find with the question as query parameters.

If a question needs filtering, distance, drive time, combining lists or a price, open a /find link: either put the question itself in q=, or build the structured link. The answer does not need an API, a connector or an account.

Simplest, the question itself: https://locationlists.com/find?q=<the question in plain words>

Or set the parts yourself: https://locationlists.com/find?dataset=<slug>&state=<ST>&city=<city>&county=<county>&zip=<zip>&near=<place or zip>&radius=<miles>&drive=<minutes>&where=<column>:<op>:<value>&total=<rows>

Leave out what the question does not need. Use radius for straight-line miles or drive for minutes of driving (5 to 60), not both; near can name several places separated by | to reach from any of them. To ask about several lists at once, use datasets with two or more names, or category with a kind of business. To compare two lists, add relate=nearest and the other list with b. in front of its parameters. To count by area, use areas=county (or zip, state, metro). To keep only places whose county, ZIP code, metro area or state meets a Census figure, add area_where (for example county:population>1000000); with areas, per=100000 gives counts per 100,000 residents.

Links an assistant can open, each showing how many rows match, a few preview rows and the price for just that part:

Optional: connect for repeat use or wallet payments:

Read https://locationlists.com/skill.md and follow the instructions to connect LocationLists. Then show me the Mitsubishi Electric Elevator Branch Offices list.

Your assistant will walk you through setup and show you the price before you pay.

For developers

At 15 records this dataset is not sold by the row — buy the file. Without a connector, open https://locationlists.com/find?dataset=mitsubishi-electric-elevator-branch-offices. An agent connected to https://locationlists.com/mcp can still search it, read a free sample file of up to 10 rows and buy the whole file itself. How agent purchasing works

?Frequently Asked Questions

Is this the whole of Mitsubishi Electric in the US?

No. It is the elevator and escalator division's branch offices only, as listed on that division's contact page.

How is this data cleaned?

Every rebuild runs the same steps and counts what each one changed. For the current file, rebuilt September 29, 2026 from mitsubishielevator.com: Merged 0 duplicate listings that had the same business name, street address and ZIP code, keeping every filled-in detail from both (September 29, 2026). Unified 0 city names written more than one way within the same ZIP code (for example with and without a space or an abbreviation) to the US Census Bureau spelling (September 29, 2026). Corrected 0 misspelled city names to the US Census Bureau place name for their ZIP code (September 29, 2026). Added map coordinates to 15 listings that had none, from the US Census Bureau address geocoder or, where the street address could not be matched, the centre of the ZIP code (September 29, 2026). Set the county and its federal county code on 15 listings, matched to the US Census Bureau county list from the county the source records, the listing's map point, or its ZIP code area (September 29, 2026). Checked every map point against the state in its address and re-placed 0 points that fell outside that state (September 29, 2026). Flagged 0 addresses that are incomplete, a PO box, or missing a house number, in an address quality column (September 29, 2026). Checked that the row count, state count and field completeness published for this file were measured from the file itself (September 29, 2026).

Isn't this free on mitsubishielevator.com?

The underlying records are public on mitsubishielevator.com. What you pay for is the work between that public release and this file: added coordinates to 15 listings, added the county to 15 listings, re-placed 0 misplaced map points, flagged 0 incomplete addresses and measured 15 rows. The current file was rebuilt September 29, 2026 from mitsubishielevator.com. Doing it yourself means downloading the full release, repeating each of those steps, and repeating them again every time the source updates.

How complete is each field?

Measured on every row of the current file, the share of rows that carry each key field: phone 100%, website 100%, street address 100%, city 100%, state 100%, ZIP code 100%, latitude 100%, longitude 100%. 20 of 22 columns are filled on at least half the rows.

↔Other elevator & escalator companies lists

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15 locations
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15 locations
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