Skip to content

Instantly share code, notes, and snippets.

@rogerallen

rogerallen/us_state_abbrev.py

Last active November 5, 2024 05:21
Show Gist options
  • Save rogerallen/1583593 to your computer and use it in GitHub Desktop.
Save rogerallen/1583593 to your computer and use it in GitHub Desktop.
Download ZIP
A Python Dictionary to translate US States to Two letter codes
Raw
us_state_abbrev.py
# United States of America Python Dictionary to translate States,
# Districts & Territories to Two-Letter codes and vice versa.
#
# Canonical URL: https://gist.github.com/rogerallen/1583593
#
# Dedicated to the public domain. To the extent possible under law,
# Roger Allen has waived all copyright and related or neighboring
# rights to this code. Data originally from Wikipedia at the url:
# https://en.wikipedia.org/wiki/ISO_3166-2:US
#
# Automatically Generated 2024-10-08 07:45:06 via Jupyter Notebook from
# https://gist.github.com/rogerallen/d75440e8e5ea4762374dfd5c1ddf84e0
us_state_to_abbrev = {
"Alabama": "AL",
"Alaska": "AK",
"Arizona": "AZ",
"Arkansas": "AR",
"California": "CA",
"Colorado": "CO",
"Connecticut": "CT",
"Delaware": "DE",
"Florida": "FL",
"Georgia": "GA",
"Hawaii": "HI",
"Idaho": "ID",
"Illinois": "IL",
"Indiana": "IN",
"Iowa": "IA",
"Kansas": "KS",
"Kentucky": "KY",
"Louisiana": "LA",
"Maine": "ME",
"Maryland": "MD",
"Massachusetts": "MA",
"Michigan": "MI",
"Minnesota": "MN",
"Mississippi": "MS",
"Missouri": "MO",
"Montana": "MT",
"Nebraska": "NE",
"Nevada": "NV",
"New Hampshire": "NH",
"New Jersey": "NJ",
"New Mexico": "NM",
"New York": "NY",
"North Carolina": "NC",
"North Dakota": "ND",
"Ohio": "OH",
"Oklahoma": "OK",
"Oregon": "OR",
"Pennsylvania": "PA",
"Rhode Island": "RI",
"South Carolina": "SC",
"South Dakota": "SD",
"Tennessee": "TN",
"Texas": "TX",
"Utah": "UT",
"Vermont": "VT",
"Virginia": "VA",
"Washington": "WA",
"West Virginia": "WV",
"Wisconsin": "WI",
"Wyoming": "WY",
"District of Columbia": "DC",
"American Samoa": "AS",
"Guam": "GU",
"Northern Mariana Islands": "MP",
"Puerto Rico": "PR",
"United States Minor Outlying Islands": "UM",
"Virgin Islands, U.S.": "VI",
}
# invert the dictionary
abbrev_to_us_state = dict(map(reversed, us_state_to_abbrev.items()))
@SagiPolaczek
Copy link

Thanks 👍
Save me to write that manually!

@Miles-Murphy
Copy link

Thank you so much! Have a great day :)

@ChrisShuttle
Copy link

Thank you!

@baileywellen
Copy link

saved me some time, thank you!

@tikhonova
Copy link

aMAzing ;) Thank you!

@gerardovitale
Copy link

This's greeeeeat!!

@KellyWemmer
Copy link

Thank YOU!!

@pnojai
Copy link

pnojai commented Nov 27, 2020

What a nice service to other developers. Makes me think of building a package with lots of lookups needed for cartography, like a FIPS lookup for example. Now, I bet someone else already did that, too.

@JSMboli
Copy link

JSMboli commented Jan 22, 2021

Thank for this.

I am trying to do something similar but worldwide.

I have list of locations that is mixed with states, cities and countries, counties and regions in abbreviations and some in full. For instance, NY, CA, England, UK, USA, Minnesota, London, Bradford, etc. I want it all to be converted to countries such as NY=USA, England=UK, Scotland = UK, Minnesota = USA, etc.

Is it possible to do this in python?
Thanks in advance.

@rmfranciacastillo
Copy link

Sweet! You just save me a lot of time!

@kinghelix You are today's hero!

@fletcheaston
Copy link

fletcheaston commented Feb 21, 2021 •
edited
Loading

In case anyone needs these in the form of enums.

from enum import Enum
from functools import cache


class State(str, Enum):
    ALABAMA = "Alabama"
    ALASKA = "Alaska"
    AMERICAN_SAMOA = "American Samoa"
    ARIZONA = "Arizona"
    ARKANSAS = "Arkansas"
    CALIFORNIA = "California"
    COLORADO = "Colorado"
    CONNECTICUT = "Connecticut"
    DELAWARE = "Delaware"
    DISTRICT_OF_COLUMBIA = "District of Columbia"
    FLORIDA = "Florida"
    GEORGIA = "Georgia"
    GUAM = "Guam"
    HAWAII = "Hawaii"
    IDAHO = "Idaho"
    ILLINOIS = "Illinois"
    INDIANA = "Indiana"
    IOWA = "Iowa"
    KANSAS = "Kansas"
    KENTUCKY = "Kentucky"
    LOUISIANA = "Louisiana"
    MAINE = "Maine"
    MARYLAND = "Maryland"
    MASSACHUSETTS = "Massachusetts"
    MICHIGAN = "Michigan"
    MINNESOTA = "Minnesota"
    MISSISSIPPI = "Mississippi"
    MISSOURI = "Missouri"
    MONTANA = "Montana"
    NEBRASKA = "Nebraska"
    NEVADA = "Nevada"
    NEW_HAMPSHIRE = "New Hampshire"
    NEW_JERSEY = "New Jersey"
    NEW_MEXICO = "New Mexico"
    NEW_YORK = "New York"
    NORTH_CAROLINA = "North Carolina"
    NORTH_DAKOTA = "North Dakota"
    NORTHERN_MARIANA_ISLANDS = "Northern Mariana Islands"
    OHIO = "Ohio"
    OKLAHOMA = "Oklahoma"
    OREGON = "Oregon"
    PENNSYLVANIA = "Pennsylvania"
    PUERTO_RICO = "Puerto Rico"
    RHODE_ISLAND = "Rhode Island"
    SOUTH_CAROLINA = "South Carolina"
    SOUTH_DAKOTA = "South Dakota"
    TENNESSEE = "Tennessee"
    TEXAS = "Texas"
    UTAH = "Utah"
    VERMONT = "Vermont"
    VIRGIN_ISLANDS = "Virgin Islands"
    VIRGINIA = "Virginia"
    WASHINGTON = "Washington"
    WEST_VIRGINIA = "West Virginia"
    WISCONSIN = "Wisconsin"
    WYOMING = "Wyoming"


@cache
def get_state_enum(state: str) -> State:
    state_mappings = {
        "AL": State.ALABAMA,
        "AS": State.AMERICAN_SAMOA,
        "AK": State.ALASKA,
        "AZ": State.ARIZONA,
        "AR": State.ARKANSAS,
        "CA": State.CALIFORNIA,
        "CO": State.COLORADO,
        "CT": State.CONNECTICUT,
        "DC": State.DISTRICT_OF_COLUMBIA,
        "DE": State.DELAWARE,
        "FL": State.FLORIDA,
        "GA": State.GEORGIA,
        "GU": State.GUAM,
        "HI": State.HAWAII,
        "ID": State.IDAHO,
        "IL": State.ILLINOIS,
        "IN": State.INDIANA,
        "IA": State.IOWA,
        "KS": State.KANSAS,
        "KY": State.KENTUCKY,
        "LA": State.LOUISIANA,
        "ME": State.MAINE,
        "MD": State.MARYLAND,
        "MA": State.MASSACHUSETTS,
        "MI": State.MICHIGAN,
        "MN": State.MINNESOTA,
        "MP": State.NORTHERN_MARIANA_ISLANDS,
        "MS": State.MISSISSIPPI,
        "MO": State.MISSOURI,
        "MT": State.MONTANA,
        "NE": State.NEBRASKA,
        "NV": State.NEVADA,
        "NH": State.NEW_HAMPSHIRE,
        "NJ": State.NEW_JERSEY,
        "NM": State.NEW_MEXICO,
        "NY": State.NEW_YORK,
        "NC": State.NORTH_CAROLINA,
        "ND": State.NORTH_DAKOTA,
        "OH": State.OHIO,
        "OK": State.OKLAHOMA,
        "OR": State.OREGON,
        "PA": State.PENNSYLVANIA,
        "PR": State.PUERTO_RICO,
        "RI": State.RHODE_ISLAND,
        "SC": State.SOUTH_CAROLINA,
        "SD": State.SOUTH_DAKOTA,
        "TN": State.TENNESSEE,
        "TX": State.TEXAS,
        "UT": State.UTAH,
        "VT": State.VERMONT,
        "VA": State.VIRGINIA,
        "VI": State.VIRGIN_ISLANDS,
        "WA": State.WASHINGTON,
        "WV": State.WEST_VIRGINIA,
        "WI": State.WISCONSIN,
        "WY": State.WYOMING,
        **{enum.value: enum for enum in State},
    }

    return state_mappings[state]

Note: updated to include more readable enums (full state names instead of abbreviations), and added a mapper function to return enums from both full and abbreviated names. If you're using Python <3.9, you can replace the @cache decorator with @lru_cache.

@jrpope2014
Copy link

Bumped into this while working on a Coursera Data Science class and looking for something of this form for a quick script, just wanted to be sure to say thanks! :)

@aidanchandra
Copy link

Thank you!

@tnalbertson
Copy link

Awesome! Thanks for the time saver :)

@Eventhisone
Copy link

Eventhisone commented Apr 9, 2021 •
edited
Loading

Here it is reversed and including DC, Northern Mariana Islands, Palau, Puerto Rico, the Virgin Islands, and US military base abbreviations.

us_state_abbrev = {
            'AL': 'Alabama',
            'AK': 'Alaska',
            'AZ': 'Arizona',
            'AR': 'Arkansas',
            'CA': 'California',
            'CO': 'Colorado',
            'CT': 'Connecticut',
            'DE': 'Delaware',
            'FL': 'Florida',
            'GA': 'Georgia',
            'HI': 'Hawaii',
            'ID': 'Idaho',
            'IL': 'Illinois',
            'IN': 'Indiana',
            'IA': 'Iowa',
            'KS': 'Kansas',
            'KY': 'Kentucky',
            'LA': 'Louisiana',
            'ME': 'Maine',
            'MD': 'Maryland',
            'MA': 'Massachusetts',
            'MI': 'Michigan',
            'MN': 'Minnesota',
            'MS': 'Mississippi',
            'MO': 'Missouri',
            'MT': 'Montana',
            'NE': 'Nebraska',
            'NV': 'Nevada',
            'NH': 'New Hampshire',
            'NJ': 'New Jersey',
            'NM': 'New Mexico',
            'NY': 'New York',
            'NC': 'North Carolina',
            'ND': 'North Dakota',
            'OH': 'Ohio',
            'OK': 'Oklahoma',
            'OR': 'Oregon',
            'PA': 'Pennsylvania',
            'RI': 'Rhode Island',
            'SC': 'South Carolina',
            'SD': 'South Dakota',
            'TN': 'Tennessee',
            'TX': 'Texas',
            'UT': 'Utah',
            'VT': 'Vermont',
            'VA': 'Virginia',
            'WA': 'Washington',
            'WV': 'West Virginia',
            'WI': 'Wisconsin',
            'WY': 'Wyoming',
            'DC': 'District of Columbia',
            'MP': 'Northern Mariana Islands',
            'PW': 'Palau',
            'PR': 'Puerto Rico',
            'VI': 'Virgin Islands',
            'AA': 'Armed Forces Americas (Except Canada)',
            'AE': 'Armed Forces Africa/Canada/Europe/Middle East',
            'AP': 'Armed Forces Pacific'
        }

@squeakyboots
Copy link

Those east of the Mississippi River:
['AL', 'CT', 'DE', 'FL', 'GA', 'IL', 'IN', 'KY', 'ME', 'MD', 'MA', 'MI', 'MS', 'NH', 'NJ', 'NY', 'NC', 'OH', 'PA', 'RI', 'SC', 'TN', 'VT', 'VA', 'WV', 'WI']

@khurchla
Copy link

Just what I need, cheers for creating this and sharing it!

@semvijverberg
Copy link

Hereby an auto enumerator.

from enum import IntEnum, auto

class US_States(IntEnum):
    AL = auto() # Alabama
    AK = auto() # Alaska
    AS = auto() # American Samoa
    AZ = auto() # Arizona
    AR = auto() # Arkansas
    CA = auto() # California
    CO = auto() # Colorado
    CT = auto() # Connecticut
    DE = auto() # Delaware
    DC = auto() # District of Columbia
    FL = auto() # Florida
    GA = auto() # Georgia
    GU = auto() # Guam
    HI = auto() # Hawaii
    ID = auto() # Idaho
    IL = auto() # Illinois
    IN = auto() # Indiana
    IA = auto() # Iowa
    KS = auto() # Kansas
    KY = auto() # Kentucky
    LA = auto() # Louisiana
    ME = auto() # Maine
    MD = auto() # Maryland
    MA = auto() # Massachusetts
    MI = auto() # Michigan
    MN = auto() # Minnesota
    MS = auto() # Mississippi
    MO = auto() # Missouri
    MT = auto() # Montana
    NE = auto() # Nebraska
    NV = auto() # Nevada
    NH = auto() # New Hampshire
    NJ = auto() # New Jersey
    NM = auto() # New Mexico
    NY = auto() # New York
    NC = auto() # North Carolina
    ND = auto() # North Dakota
    MP = auto() # Northern Mariana Islands
    OH = auto() # Ohio
    OK = auto() # Oklahoma
    OR = auto() # Oregon
    PA = auto() # Pennsylvania
    PR = auto() # Puerto Rico
    RI = auto() # Rhode Island
    SC = auto() # South Carolina
    SD = auto() # South Dakota
    TN = auto() # Tennessee
    TX = auto() # Texas
    UT = auto() # Utah
    VT = auto() # Vermont
    VI = auto() # Virgin Islands
    VA = auto() # Virginia
    WA = auto() # Washington
    WV = auto() # West Virginia
    WI = auto() # Wisconsin
    WY = auto() # Wyoming

@leotraeg
Copy link

Here is one to encode US states based on their population ranking (might be usefull for some further correlation analysis):
us_state_to_population_ranking_encoding = {
"CA": 52, "TX": 51, "FL": 50, "NY": 49, "PA": 48, "IL": 47,
"OH": 46, "GA": 45, "NC": 44, "MI": 43, "NJ": 42, "VA": 41,
"WA": 40, "AZ": 39, "TN": 38, "MA": 37, "IN": 36, "MO": 35,
"MD": 34, "CO": 33, "WI": 32, "MN": 31, "SC": 30, "AL": 29,
"LA": 28, "KY": 27, "OR": 26, "OK": 25, "CT": 24, "UT": 23,
"PR": 22, "NV": 21, "IA": 20, "AR": 19, "MS": 18, "KS": 17,
"NM": 16, "NE": 15, "ID": 14, "WV": 13, "HI": 12, "NH": 11,
"ME": 10, "MT": 9, "RI": 8, "DE": 7, "SD": 6, "ND": 5,
"AK": 4, "DC": 3, "VT": 2, "WY": 1
}

@elishevab
Copy link

Thank you!

@AnnieW2014
Copy link

Thank you!! And Happy New Year!

@Tetfretguru
Copy link

I just came in today to parse legal data from all US states and this came very in handy! Thanks buddy!

@shikhagoenkahf
Copy link

us_state_to_abbrev = {
"Alabama": "AL",
"Alaska": "AK",
"Arizona": "AZ",
"Arkansas": "AR",
"California": "CA",
"Colorado": "CO",
"Connecticut": "CT",
"Delaware": "DE",
"Florida": "FL",
"Georgia": "GA",
"Hawaii": "HI",
"Idaho": "ID",
"Illinois": "IL",
"Indiana": "IN",
"Iowa": "IA",
"Kansas": "KS",
"Kentucky": "KY",
"Louisiana": "LA",
"Maine": "ME",
"Maryland": "MD",
"Massachusetts": "MA",
"Michigan": "MI",
"Minnesota": "MN",
"Mississippi": "MS",
"Missouri": "MO",
"Montana": "MT",
"Nebraska": "NE",
"Nevada": "NV",
"New Hampshire": "NH",
"New Jersey": "NJ",
"New Mexico": "NM",
"New York": "NY",
"North Carolina": "NC",
"North Dakota": "ND",
"Ohio": "OH",
"Oklahoma": "OK",
"Oregon": "OR",
"Pennsylvania": "PA",
"Rhode Island": "RI",
"South Carolina": "SC",
"South Dakota": "SD",
"Tennessee": "TN",
"Texas": "TX",
"Utah": "UT",
"Vermont": "VT",
"Virginia": "VA",
"Washington": "WA",
"West Virginia": "WV",
"Wisconsin": "WI",
"Wyoming": "WY",
"District of Columbia": "DC",
"American Samoa": "AS",
"Guam": "GU",
"Northern Mariana Islands": "MP",
"Puerto Rico": "PR",
"United States Minor Outlying Islands": "UM",
"U.S. Virgin Islands": "VI",
"AL": "AL",
"AK": "AK",
"AZ": "AZ",
"AR": "AR",
"CA": "CA",
"CO": "CO",
"CT": "CT",
"DE": "DE",
"FL": "FL",
"GA": "GA",
"HI": "HI",
"ID": "ID",
"IL": "IL",
"IN": "IN",
"IA": "IA",
"KS": "KS",
"KY": "KY",
"LA": "LA",
"ME": "ME",
"MD": "MD",
"MA": "MA",
"MI": "MI",
"MN": "MN",
"MS": "MS",
"MO": "MO",
"MT": "MT",
"NE": "NE",
"NV": "NV",
"NH": "NH",
"NJ": "NJ",
"NM": "NM",
"NY": "NY",
"NC": "NC",
"ND": "ND",
"OH": "OH",
"OK": "OK",
"OR": "OR",
"PA": "PA",
"RI": "RI",
"SC": "SC",
"SD": "SD",
"TN": "TN",
"TX": "TX",
"UT": "UT",
"VT": "VT",
"VA": "VA",
"WA": "WA",
"WV": "WV",
"WI": "WI",
"WY": "WY",
"DC": "DC",
"AS": "AS",
"GU": "GU",
"MP": "MP",
"PR": "PR",
"UM": "UM",
"VI": "VI",
}

needed this for standardizing the column where some values were full names and some were abbreviations

@shayeny
Copy link

shayeny commented Feb 17, 2022

@pnojai take a look at : https://pypi.org/project/us/

@florent-zahoui
Copy link

thanks a lot

@bayusuarsa
Copy link

Thank you for sharing this information
@sandlerj It's worked very well, and thank you

@IMXENON
Copy link

IMXENON commented Jun 19, 2022

Thank you!

@quicksilver0
Copy link

Commenting as well, so everyone gets spam on this gist! haha

@jasondo-da
Copy link

Everyone who contributed to this I hope nothing but the best for you! Thank you!

@rogerallen
Copy link
Author

Updated with latest results from Wikipedia-scraping script. Only change was to Virgin Islands.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment