
import time
start_time = time.time()
import geopandas
import pandas as pd
import folium
import branca
import numpy as np
import json
from selenium import webdriver
from selenium.webdriver.common.keys import Keys 
from selenium.webdriver.chrome.options import Options
# Source: https://selenium-python.readthedocs.io/getting-started.html
import PIL.Image
import IPython
import os

simplification_level = 0.005 # This value will be passed to the tolerance
# argument within various shape simplification commands. Higher values
# produce smaller map file sizes but less accurate boundaries.


# Identifying the current working directory: (This directory
# will be passed as an argument to a screenshot generation function.)
cwd = os.getcwd()
cwd

'c:\\Users\\kburc\\D1V1\\Documents\\!Dell64docs\\Programming\\py\\kjb3_programs\\us_diocese_mapper'


generate_county_list_and_boundaries = False # This cell determines whether
# or not to create a new table of county boundaries, along with province
# and diocesan boundaries based on those county boundaries. This should be 
# set to True when generating the first batch of these boundaries or when 
# updating them; otherwise, it can generally be set to False, 
# thus saving processing time.
extract_FIPS_codes_from_website = False # Useful if working offline (or if 
# the website's layout changes in the future)


if generate_county_list_and_boundaries == True:

    shapefile_path = \
        r'C:\Users\kburc\Downloads\tl_2021_us_county_download\tl_2021_us_county.shp'
    if extract_FIPS_codes_from_website == True:
        state_fips_codes = pd.read_html(
            'https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/technical/nra/nri/results/?cid=nrcs143_013696')[0]
        # This resource contains both FIPS codes and state names. These state
        # names will then be merged into the county_shapes DataFrame below.
        state_fips_codes = state_fips_codes.iloc[0:55].copy()
        state_fips_codes['FIPS'] = state_fips_codes['FIPS'].astype('int')
        state_fips_codes.rename(columns={'Name':'State_Name',
        'Postal Code':'State_Code'},inplace=True) 
        state_fips_codes.loc[55] = ['District of Columbia', 'DC', 11] 
        # DC wasn't present in the original webpage, so I added it in. 
        # I located its FIPS code within the county shapefile dataset.
        state_fips_codes.to_csv('state_fips_codes.csv', index = False)
    else:
        state_fips_codes = pd.read_csv('state_fips_codes.csv')

    county_shapes = geopandas.read_file(shapefile_path)

    county_shapes.drop(['CLASSFP', 'MTFCC', 'CSAFP', 'CBSAFP', 'METDIVFP', 
    'FUNCSTAT', 'ALAND', 'AWATER', 'INTPTLAT', 'INTPTLON'], 
    axis = 1, inplace = True)
    county_shapes['STATEFP'] = county_shapes['STATEFP'].astype('int')

    merged_county_shapes = county_shapes.merge(state_fips_codes, 
    left_on = 'STATEFP', right_on = 'FIPS', how = 'left')
    merged_county_shapes['county_state'] = merged_county_shapes[
        'NAMELSAD'] + ', ' + merged_county_shapes['State_Name']
        # The county_state column will be a valuable resource, as each entry
        # within this column is unique. (County names by themselves are not
        # unique as multiple counties can share the same name.)

    # The above line exports the GeoDataFrame created by prepare_zip_table 
    # so that it can be imported back into the program, which takes less time
    # than does recreating the GeoDataFrame.

    # merged_county_shapes.to_file('original_county_outlines.geojson')
    # This file is over 200 MB in size.

    df_dioceses = merged_county_shapes.copy()

else: # If generate_county_list_and_boundaries is set to false, the block
    # simply reads in a saved copy of df_dioceses, along with two other
    # DataFrames. (These DataFrames will get created later on if
    # generate_county_list_and_boundaries is set to True.)
    df_dioceses = geopandas.read_file('counties_by_diocese.geojson')
    diocese_boundaries = geopandas.read_file('diocese_boundaries.geojson')
    province_boundaries = geopandas.read_file('province_boundaries.geojson')


df_dioceses.head(5)


regions_not_in_us_episcopal_conference = ['Puerto Rico', 'Guam', 
'Northern Mariana Islands', 'American Samoa']
df_dioceses = df_dioceses.query(
    "State_Name not in @regions_not_in_us_episcopal_conference").copy()


df_dioceses['Diocese'] = 'Not_Set'


condlist = [
df_dioceses['State_Name'] == 'Alabama',
df_dioceses['State_Name'] == 'Alaska',
df_dioceses['State_Name'] == 'Arizona',
df_dioceses['State_Name'] == 'Arkansas',
df_dioceses['State_Name'] == 'California',
df_dioceses['State_Name'] == 'Colorado',
df_dioceses['State_Name'] == 'Connecticut',
df_dioceses['State_Name'] == 'Delaware',
df_dioceses['State_Name'] == 'Florida',
df_dioceses['State_Name'] == 'Georgia',
df_dioceses['State_Name'] == 'Hawaii',
df_dioceses['State_Name'] == 'Idaho',
df_dioceses['State_Name'] == 'Illinois',
df_dioceses['State_Name'] == 'Indiana',
df_dioceses['State_Name'] == 'Iowa',
df_dioceses['State_Name'] == 'Kansas',
df_dioceses['State_Name'] == 'Kentucky',
df_dioceses['State_Name'] == 'Louisiana',
df_dioceses['State_Name'] == 'Maine',
df_dioceses['State_Name'] == 'Maryland',
df_dioceses['State_Name'] == 'Massachusetts',
df_dioceses['State_Name'] == 'Michigan',
df_dioceses['State_Name'] == 'Minnesota',
df_dioceses['State_Name'] == 'Mississippi',
df_dioceses['State_Name'] == 'Missouri',
df_dioceses['State_Name'] == 'Montana',
df_dioceses['State_Name'] == 'Nebraska',
df_dioceses['State_Name'] == 'Nevada',
df_dioceses['State_Name'] == 'New Hampshire',
df_dioceses['State_Name'] == 'New Jersey',
df_dioceses['State_Name'] == 'New Mexico',
df_dioceses['State_Name'] == 'New York',
df_dioceses['State_Name'] == 'North Carolina',
df_dioceses['State_Name'] == 'North Dakota',
df_dioceses['State_Name'] == 'Ohio',
df_dioceses['State_Name'] == 'Oklahoma',
df_dioceses['State_Name'] == 'Oregon',
df_dioceses['State_Name'] == 'Pennsylvania',
df_dioceses['State_Name'] == 'Rhode Island',
df_dioceses['State_Name'] == 'South Carolina',
df_dioceses['State_Name'] == 'South Dakota',
df_dioceses['State_Name'] == 'Tennessee',
df_dioceses['State_Name'] == 'Texas',
df_dioceses['State_Name'] == 'Utah',
df_dioceses['State_Name'] == 'Vermont',
df_dioceses['State_Name'] == 'Virginia',
df_dioceses['State_Name'] == 'Washington',
df_dioceses['State_Name'] == 'West Virginia',
df_dioceses['State_Name'] == 'Wisconsin',
df_dioceses['State_Name'] == 'Wyoming',
df_dioceses['State_Name'] == 'District of Columbia',
df_dioceses['State_Name'] == 'Virgin Islands'
]


choicelist = [

# To make sure that I had the dioceses and states in the same order, I copied
# and pasted the state list into this code block, then commented it out so 
# that it could be used as a reference.

# df_dioceses['State_Name'] == 'Alabama',
'Mobile',

# df_dioceses['State_Name'] == 'Alaska',
'Fairbanks',

# df_dioceses['State_Name'] == 'Arizona',
'Phoenix',

# df_dioceses['State_Name'] == 'Arkansas',
'Little Rock', # Statewide diocese

# df_dioceses['State_Name'] == 'California',
'Los Angeles', 

# df_dioceses['State_Name'] == 'Colorado',
'Pueblo',

# df_dioceses['State_Name'] == 'Connecticut',
'Norwich', 

# df_dioceses['State_Name'] == 'Delaware',
'Wilmington', # Statewide diocese

# df_dioceses['State_Name'] == 'Florida',
'Orlando', 

# df_dioceses['State_Name'] == 'Georgia',
'Savannah',

# df_dioceses['State_Name'] == 'Hawaii',
'Honolulu', # Statewide diocese

# df_dioceses['State_Name'] == 'Idaho',
'Boise', #Statewide diocese

# df_dioceses['State_Name'] == 'Illinois',
'Peoria',

# df_dioceses['State_Name'] == 'Indiana',
'Indianapolis', 

# df_dioceses['State_Name'] == 'Iowa',
'Dubuque',

# df_dioceses['State_Name'] == 'Kansas',
'Salina',

# df_dioceses['State_Name'] == 'Kentucky',
'Lexington',

# df_dioceses['State_Name'] == 'Louisiana',
'Shreveport',

# df_dioceses['State_Name'] == 'Maine',
'Portland in Maine', # Statewide diocese

# df_dioceses['State_Name'] == 'Maryland',
'Wilmington', 

# df_dioceses['State_Name'] == 'Massachusetts',
'Boston',

# df_dioceses['State_Name'] == 'Michigan',
'Marquette',

# df_dioceses['State_Name'] == 'Minnesota',
'Duluth',

# df_dioceses['State_Name'] == 'Mississippi',
'Jackson',

# df_dioceses['State_Name'] == 'Missouri',
'Springfield-Cape Girardeau',

# df_dioceses['State_Name'] == 'Montana',
'Helena',

# df_dioceses['State_Name'] == 'Nebraska',
'Grand Island',

# df_dioceses['State_Name'] == 'Nevada',
'Reno',

# df_dioceses['State_Name'] == 'New Hampshire',
'Manchester', # Statewide diocese

# df_dioceses['State_Name'] == 'New Jersey',
'Camden',

# df_dioceses['State_Name'] == 'New Mexico',
'Santa Fe',

# df_dioceses['State_Name'] == 'New York',
'Albany',

# df_dioceses['State_Name'] == 'North Carolina',
'Raleigh',

# df_dioceses['State_Name'] == 'North Dakota',
'Fargo',

# df_dioceses['State_Name'] == 'Ohio',
'Columbus',

# df_dioceses['State_Name'] == 'Oklahoma',
'Oklahoma City',

# df_dioceses['State_Name'] == 'Oregon',
'Portland in Oregon',

# df_dioceses['State_Name'] == 'Pennsylvania',
'Erie',

# df_dioceses['State_Name'] == 'Rhode Island',
'Providence', #Statewide diocese

# df_dioceses['State_Name'] == 'South Carolina',
'Charleston', # Statewide diocese

# df_dioceses['State_Name'] == 'South Dakota',
'Sioux Falls',

# df_dioceses['State_Name'] == 'Tennessee',
'Nashville',

# df_dioceses['State_Name'] == 'Texas',
'Lubbock',

# df_dioceses['State_Name'] == 'Utah',
'Salt Lake City', # Statewide Diocese

# df_dioceses['State_Name'] == 'Vermont',
'Burlington', # Statewide diocese

# df_dioceses['State_Name'] == 'Virginia',
'Richmond',

# df_dioceses['State_Name'] == 'Washington',
'Seattle',

# df_dioceses['State_Name'] == 'West Virginia',
'Wheeling-Charleston', # Statewide diocese

# df_dioceses['State_Name'] == 'Wisconsin',
'La Crosse',

# df_dioceses['State_Name'] == 'Wyoming'],
'Cheyenne', # Statewide diocese

# df_dioceses['State_Name'] == 'District of Columbia',
'Washington',

# df_dioceses['State_Name'] == 'Virgin Islands'
'St. Thomas'
]


df_dioceses['Diocese'] = np.select(condlist, choicelist, df_dioceses['Diocese'])
# https://numpy.org/doc/stable/reference/generated/numpy.select.html


len(df_dioceses) # The number of counties within the DataFrame

3146


df_dioceses


initial_version_of_df_dioceses = \
df_dioceses.copy() # Will be compared to a later version of df_dioceses


def add_dioceses(df, county_list, state, diocese):
    # Updates the 'Diocese' value within df_dioceses for a list 
    # of counties in a given state. If a diocese spans
    # multiple states, this function will need to be called once for each
    # state.
    # If a given 'county' variable does not have any spaces, 
    # the loop below will add ' County' to that string before 
    # adding in the state. Otherwise, the code assumes that the 'county' is
    # either a non-county (e.g. a municipality, city, census area, parish,
    # or borough), and will only add the state to this string.
    # Therefore, in order to run this function successfully, enter the 
    # area designation (county, city, etc.) after all non-counties and
    # counties with more than one word when building the county list.
    # However, you don't need to add in 'County' for counties with only
    # one word.
    for county in county_list:
        if ' ' not in county:
            county_string = county + ' County, ' + state
        else:
            county_string = county + ', ' + state
        if county_string not in df.index:
            raise ValueError(county_string, "not found in index")
        df.at[county_string, 'Diocese'] = diocese
        # https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.at.html
        # df.at updates the 'Diocese' value for a given county_string. For 
        # this function to work, the DataFrame's index must be set to 
        # county_string.
    return df


df_dioceses.set_index('county_state', drop = False, inplace = True) # This 
# temporary change is made to facilitate the use of df.at within the 
# add_dioceses function. The county_state column is retained for later use.

# Archdiocese of Anchorage-Juneau:
# Source: Wikipedia province map

anchorage_juneau_county_list = [
'Aleutians West Census Area',
'Aleutians East Borough', 'Lake and Peninsula Borough',
'Bristol Bay Borough', 'Dillingham Census Area', 'Kodiak Island Borough',
'Kenai Peninsula Borough', 'Chugach Census Area', 'Yakutat City and Borough',
'Aleutians West Census Area', 'Hoonah-Angoon Census Area',
'Petersburg Borough', 'Wrangell City and Borough', 'Ketchikan Gateway Borough',
'Prince of Wales-Hyder Census Area', 'Sitka City and Borough',
'Copper River Census Area', 'Matanuska-Susitna Borough',
'Anchorage Municipality', 'Juneau City and Borough', 'Skagway Municipality',
'Haines Borough'
]
# In the following line of code, add_dioceses will go through each county
# (or, in this case, county equivalent) in anchorage_juneau_county list
# and set its 'Diocese' value within df_dioceses to Anchorage-Juneau. 
df_dioceses = add_dioceses(df_dioceses, 
anchorage_juneau_county_list, state = 'Alaska', diocese = 'Anchorage-Juneau')

# Archdiocese of Atlanta:
# (Source: Diocesan website: 
# https://archatl.com/about/about-the-archdiocese-of-atlanta/)
# This site noted the counties within the Archdiocese of Atlanta that border
# the Diocese of Savannah. I entered in those counties first, then added in
# all other counties to the north of those.

atlanta_county_list = [
'Gilmer', 'Carroll', 'Douglas', 'Clayton', 'Spalding', 'Henry', 'Rockdale',
'Oconee', 'Barrow', 'Jackson', 'Madison', 'Elbert', 'Rabun', 'Towns',
'Union', 'Fannin', 'Murray', 'Catoosa', 'Whitfield', 'Dade', 'Walker',
'Chattooga', 'Gordon', 'Pickens', 'Dawson', 'Lumpkin', 'White', 'Habersham',
'Stephens', 'Hart', 'Franklin', 'Banks', 'Hall', 'Forsyth', 'Fulton',
'Cherokee', 'Bartow', 'Floyd', 'Polk', 'Haralson', 'Paulding', 'Cobb',
'DeKalb', 'Gwinnett', 'Walton', 'Clarke', 'Oglethorpe', 'Coweta', 'Wilkes',
'Coweta', 'Taliaferro', 'Greene', 'Morgan', 'Coweta', 'Newton', 'Butts', 
'Lamar', 'Pike', 'Coweta', 'Fayette', 'Coweta', 'Heard', 'Troup', 'Meriwether',
'Upson', 'Monroe', 'Jasper', 'Putnam', 'Baldwin', 'Hancock', 'Warren',
'McDuffie', 'Lincoln'
]
df_dioceses = add_dioceses(df_dioceses, 
atlanta_county_list, state = 'Georgia', diocese = 'Atlanta')

# # Diocese of Charlotte:
# Source: https://web.archive.org/web/20110504140939/http://www.charlottediocese.org/atlasofthediocese.html 
# See also:
# https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Charlotte#/media/File:Diocese_of_Charlotte.jpg

charlotte_county_list = [
'Richmond', 'Montgomery', 'Randolph', 'Guilford', 'Rockingham', 'Mecklenburg', 
'Davie', 'Yadkin', 'Surry', 'Alleghany', 'Wilkes', 'Iredell', 'Catawba', 
'Lincoln', 'Gaston', 'Cleveland', 'Stokes', 'Forsyth', 'Davidson', 'Rowan', 
'Stanly', 'Anson', 'Union', 'Cabarrus', 'Cherokee', 'Graham', 'Swain', 
'Haywood', 'Madison', 'Ashe', 'Watauga', 'Caldwell', 'Alexander', 'Burke', 
'McDowell', 'Rutherford', 'Polk', 'Henderson', 'Buncombe', 'Yancey', 'Mitchell', 
'Clay', 'Macon', 'Jackson', 'Transylvania', 'Avery'
]
df_dioceses = add_dioceses(df_dioceses, 
charlotte_county_list, state = 'North Carolina', diocese = 'Charlotte')

# Archdiocese of Baltimore:
# https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Baltimore

baltimore_county_list = [
'Anne Arundel County', 'Baltimore', 'Carroll', 'Frederick', 'Garrett', 
'Harford', 'Howard', 'Washington', 'Baltimore city','Allegany'
] 
df_dioceses = add_dioceses(df_dioceses, 
baltimore_county_list, state = 'Maryland', diocese = 'Baltimore')

# Diocese of Arlington:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Arlington

arlington_county_list = [
'Arlington', 'Clarke', 'Culpeper', 'Fairfax', 'Fauquier', 'Frederick', 
'King George County', 'Lancaster', 'Loudoun', 'Madison', 'Northumberland', 
'Orange', 'Page', 'Prince William County', 'Rappahannock', 'Richmond',
'Shenandoah', 'Spotsylvania', 'Stafford', 'Warren', 'Westmoreland', 
'Alexandria city', 'Falls Church city', 'Fairfax city', 'Fredericksburg city',
'Manassas city', 'Manassas Park city', 'Winchester city'
]
df_dioceses = add_dioceses(df_dioceses, 
arlington_county_list, state = 'Virginia', diocese = 'Arlington')

# Archdiocese of Washington:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Washington
# Note that the Archdiocese of Washington includes a number of counties
# in Maryland, which will be added here. The District of Columbia is already
# listed as belonging to the Diocese of Washington.
washington_county_list = [
'Calvert', 'Charles', 'Montgomery', 
"Prince George's County", "St. Mary's County"
]
df_dioceses = add_dioceses(df_dioceses, 
washington_county_list, state = 'Maryland', diocese = 'Washington')


# Diocese of Fall River:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Fall_River

fall_river_county_list = [
'Barnstable', 'Bristol', 'Dukes', 'Nantucket'
]
df_dioceses = add_dioceses(df_dioceses, 
fall_river_county_list, state = 'Massachusetts', diocese = 'Fall River')

# Diocese of Springfield in Massachusetts:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Springfield_in_Massachusetts

springfield_in_massachusetts_county_list = [
'Berkshire', 'Franklin', 'Hampshire', 'Hampden'
]
df_dioceses = add_dioceses(df_dioceses, 
springfield_in_massachusetts_county_list, state = 'Massachusetts', diocese = 
'Springfield in Massachusetts')

# Diocese of Worcester: 
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Worcester

df_dioceses.at[
"Worcester County, Massachusetts", 'Diocese'] = 'Worcester' 
# The Diocese of Worcester includes only one county, so it can
# be added directly to the DataFrame.

# Archdiocese of Chicago: 
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Chicago

chicago_county_list = [
'Cook', 'Lake'
]
df_dioceses = add_dioceses(df_dioceses, 
chicago_county_list, state = 'Illinois', diocese = 
'Chicago')

# Diocese of Belleville:
# I couldn't find a list of counties on the diocese's website
# or on the Diocese's Wikipedia page, so I based the county
# list off this map:
# https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Belleville#/media/File:Diocese_of_Belleville_map_1.png

belleville_county_list = [
"St. Clair County", "Clinton", "Marion", "Clay", "Richland", "Lawrence", 
"Wabash", "Edwards", "Wayne", "Monroe", "Washington", "Jefferson", "Hamilton", 
"White", "Gallatin", "Saline", "Williamson", "Jackson", "Union", "Johnson", 
"Pope", "Massac", "Pulaski", "Alexander", "Randolph", "Perry", "Franklin", 
"Hardin"
]
df_dioceses = add_dioceses(df_dioceses, 
belleville_county_list, state = 'Illinois', diocese = 
'Belleville')

# Diocese of Joliet:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Joliet_in_Illinois

joliet_county_list = [
"DuPage", "Ford", "Grundy", "Iroquois", "Kankakee", "Kendall", "Will"
]
df_dioceses = add_dioceses(df_dioceses, 
joliet_county_list, state = 'Illinois', diocese = 
'Joliet')

# Diocese of Rockford:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Rockford

rockford_county_list = [
"Boone", "Carroll", "DeKalb", "Jo Daviess County", "Kane", "Lee", "McHenry",
"Ogle", "Stephenson", "Whiteside", "Winnebago"
]
df_dioceses = add_dioceses(df_dioceses, 
rockford_county_list, state = 'Illinois', diocese = 
'Rockford')

springfield_in_illinois_county_list = [
"Adams", "Bond", "Brown", "Calhoun", "Cass", "Christian", "Clark", "Coles", 
"Crawford", "Cumberland", "Douglas", "Edgar", "Effingham", "Fayette", "Greene", 
"Jasper", "Jersey", "Macon", "Macoupin", "Madison", "Menard", "Moultrie", 
"Montgomery", "Morgan", "Pike", "Sangamon", "Scott", "Shelby"
]
df_dioceses = add_dioceses(df_dioceses, 
springfield_in_illinois_county_list, state = 'Illinois', diocese = 
'Springfield in Illinois')

# Archdiocese of Cincinnati:
# Source: https://catholicaoc.org/about/geography

cincinnati_county_list = [
'Mercer', 'Auglaize', 'Logan', 'Darke', 'Shelby', 'Miami', 'Clark', 'Preble', 
'Montgomery', 'Greene', 'Butler', 'Warren', 'Clinton', 'Hamilton', 'Clermont', 
'Brown', 'Highland', 'Adams', 'Champaign'
]
df_dioceses = add_dioceses(df_dioceses, 
cincinnati_county_list, state = 'Ohio', diocese = 
'Cincinnati')

# Diocese of Cleveland: 
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Cleveland
cleveland_county_list = [
'Ashland', 'Cuyahoga', 'Geauga', 'Lake', 'Lorain',
'Medina', 'Summit', 'Wayne'
]
df_dioceses = add_dioceses(df_dioceses, 
cleveland_county_list, state = 'Ohio', diocese = 
'Cleveland')

# Diocese of Steubenville:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Steubenville
steubenville_county_list = [
'Athens', 'Belmont', 'Carroll', 'Gallia', 'Guernsey', 'Harrison', 'Jefferson', 
'Lawrence', 'Meigs', 'Morgan', 'Monroe', 'Noble', 'Washington'
]
df_dioceses = add_dioceses(df_dioceses, 
steubenville_county_list, state = 'Ohio', diocese = 
'Steubenville')

# Diocese of Toledo:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Toledo

toledo_county_list = [
'Allen', 'Crawford', 'Defiance', 'Erie', 'Fulton',
'Hancock', 'Henry', 'Huron', 'Lucas', 'Ottawa', 'Paulding', 'Putnam', 
'Richland', 'Sandusky', 'Seneca', 'Van Wert County', 'Williams', 'Wood',
'Wyandot'
]
df_dioceses = add_dioceses(df_dioceses, 
toledo_county_list, state = 'Ohio', diocese = 
'Toledo')

# Diocese of Youngstown:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Youngstown

youngstown_county_list = [
'Mahoning', 'Trumbull', 'Columbiana', 'Stark', 'Portage', 'Ashtabula'
]
df_dioceses = add_dioceses(df_dioceses, 
youngstown_county_list, state = 'Ohio', diocese = 
'Youngstown')

# Archdiocese of Denver:
# Source: https://archden.org/wp-content/uploads/2021/11/2021_media_kit_updated_11-3-21.pdf
# This source incorrectly spells Broomfield County as 
# 'Bromfield.' 

denver_county_list = [
'Adams', 'Arapahoe', 'Boulder', 'Broomfield', 
'Clear Creek County', 'Denver', 'Eagle', 'Garfield',
'Gilpin', 'Grand', 'Jackson', 'Jefferson', 'Larimer',
'Logan', 'Moffat', 'Morgan', 'Phillips', 'Pitkin',
'Rio Blanco County', 'Routt', 'Sedgwick', 'Summit',
'Washington', 'Weld', 'Yuma'
]
df_dioceses = add_dioceses(df_dioceses, 
denver_county_list, state = 'Colorado', diocese = 
'Denver')


# Diocese of Colorado Springs:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Colorado_Springs

colorado_springs_county_list = [
'Chaffee', 'Lake', 'Park', 'Teller', 'Douglas',
'El Paso County', 'Elbert', 'Lincoln', 
'Kit Carson County', 'Cheyenne'
]
df_dioceses = add_dioceses(df_dioceses, 
colorado_springs_county_list, state = 'Colorado', diocese = 
'Colorado Springs')

# Archdiocese of Detroit:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Detroit

detroit_county_list = [
'Lapeer', 'Macomb', 'Monroe', 'Oakland', 'St. Clair County', 'Wayne'
]
df_dioceses = add_dioceses(df_dioceses, 
detroit_county_list, state = 'Michigan', diocese = 
'Detroit')


# Diocese of Gaylord:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Gaylord

gaylord_county_list = [
'Charlevoix', 'Emmet', 'Cheboygan', 'Presque Isle County', 
'Leelanau', 'Antrim', 'Otsego', 'Montmorency', 'Alpena', 'Benzie', 
'Grand Traverse County', 'Kalkaska', 'Crawford', 'Oscoda', 'Alcona',
'Manistee', 'Wexford', 'Missaukee', 'Roscommon', 'Ogemaw', 'Iosco'
]
df_dioceses = add_dioceses(df_dioceses, 
gaylord_county_list, state = 'Michigan', diocese = 
'Gaylord')

# Diocese of Grand Rapids:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Grand_Rapids

grand_rapids_county_list = [
'Ottawa', 'Kent', 'Ionia', 'Muskegon', 'Newaygo', 'Oceana', 
'Montcalm', 'Mecosta', 'Lake', 'Mason', 'Osceola'
]
df_dioceses = add_dioceses(df_dioceses, 
grand_rapids_county_list, state = 'Michigan', diocese = 
'Grand Rapids')


# Diocese of Kalamazoo:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Kalamazoo
kalamazoo_county_list = [
'Allegan', 'Barry', 'Van Buren County', 'Kalamazoo', 'Calhoun', 
'Berrien', 'Cass', 'St. Joseph County', 'Branch'
]
df_dioceses = add_dioceses(df_dioceses, 
kalamazoo_county_list, state = 'Michigan', diocese = 
'Kalamazoo')

# Diocese of Lansing:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Lansing

lansing_county_list = [
'Clinton', 'Eaton', 'Genesee', 'Hillsdale', 'Ingham', 'Jackson', 
'Lenawee', 'Livingston', 'Shiawassee', 'Washtenaw'
]
df_dioceses = add_dioceses(df_dioceses, 
lansing_county_list, state = 'Michigan', diocese = 
'Lansing')


# Diocese of Saginaw:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Saginaw
saginaw_county_list = [
'Arenac', 'Bay', 'Clare', 'Gladwin', 'Gratiot', 'Huron', 'Isabella',
'Midland', 'Saginaw', 'Sanilac', 'Tuscola']

df_dioceses = add_dioceses(df_dioceses, 
saginaw_county_list, state = 'Michigan', diocese = 
'Saginaw')

# Diocese of Davenport:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Davenport
# See also:
# https://d2y1pz2y630308.cloudfront.net/13543/documents/2020/8/Parishes%20Map%207-1-20.pdf
davenport_county_list = [
'Jasper', 'Poweshiek', 'Iowa', 'Johnson', 'Cedar', 'Clinton', 'Marion',
'Monroe', 'Appanoose', 'Mahaska', 'Wapello', 'Davis', 'Keokuk', 
'Washington', 'Muscatine', 'Scott', 'Louisa', 'Des Moines County', 
'Henry', 'Lee', 'Van Buren County', 'Jefferson']

df_dioceses = add_dioceses(df_dioceses, 
davenport_county_list, state = 'Iowa', diocese = 
'Davenport')

# Diocese of Sioux CIty:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Sioux_City#/media/File:Diocese_of_Sioux_City.jpg

sioux_city_county_list = [
'Boone', 'Greene', 'Carroll', 'Crawford', 'Monona', 'Webster', 'Humboldt', 
'Kossuth', 'Dickinson', 'Lyon', 'Sioux', 'Plymouth', 'Woodbury', 'Osceola',
'Emmet', "O'Brien", 'Clay', 'Palo Alto County', 'Cherokee', 
'Buena Vista County', 'Pocahontas', 'Ida', 'Sac', 'Calhoun'
]
df_dioceses = add_dioceses(df_dioceses, 
sioux_city_county_list, state = 'Iowa', diocese = 
'Sioux City')

# Diocese of Des Moines:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Des_Moines#/media/File:Diocese_of_Des_Moines.jpg

des_moines_county_list = [
'Harrison', 'Shelby', 'Audubon', 'Guthrie', 'Dallas', 'Polk',
'Pottawattamie', 'Cass', 'Adair', 'Madison', 'Warren', 'Mills',
'Montgomery', 'Adams', 'Union', 'Clarke', 'Lucas', 'Fremont',
'Page', 'Taylor', 'Ringgold', 'Decatur', 'Wayne'
]
df_dioceses = add_dioceses(df_dioceses, 
des_moines_county_list, state = 'Iowa', diocese = 
'Des Moines')

# Archdiocese of Galveston-Houston:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Galveston%E2%80%93Houston
galveston_houston_county_list = [
'Galveston', 'Harris', 'Austin', 'Brazoria', 'Fort Bend County', 'Grimes',
'Montgomery', 'San Jacinto County', 'Walker', 'Waller'] 

df_dioceses = add_dioceses(df_dioceses, 
galveston_houston_county_list, state = 'Texas', diocese = 
'Galveston-Houston')


# Diocese of Austin:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Austin
austin_county_list = [
'Bastrop', 'Bell', 'Blanco', 'Brazos', 'Burleson', 'Burnet', 'Caldwell',
'Coryell', 'Falls', 'Hamilton', 'Hays', 'Lampasas', 'Lee', 'Limestone',
'Llano', 'Mason', 'McLennan', 'Milam', 'Mills', 'Robertson', 'San Saba County',
'Travis', 'Washington', 'Williamson'
]

df_dioceses = add_dioceses(df_dioceses, 
austin_county_list, state = 'Texas', diocese = 
'Austin')

# Diocese of Beaumont:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Beaumont

beaumont_county_list = [
'Chambers', 'Hardin', 'Jasper', 'Jefferson', 'Liberty', 'Newton', 'Orange',
'Polk', 'Tyler'
]
df_dioceses = add_dioceses(df_dioceses, 
beaumont_county_list, state = 'Texas', diocese = 
'Beaumont')

# Diocese of Brownsville:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Brownsville
brownsville_county_list = [
'Starr', 'Willacy', 'Hidalgo', 'Cameron'
]
df_dioceses = add_dioceses(df_dioceses, 
brownsville_county_list, state = 'Texas', diocese = 
'Brownsville')

# Diocese of Corpus Christi:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Corpus_Christi

corpus_christi_county_list = [
'Aransas', 'Bee', 'Brooks', 'Duval', 'Jim Wells County', 'Kenedy', 'Kleberg', 
'Live Oak County', 'Nueces', 'Refugio', 'San Patricio County'
]
df_dioceses = add_dioceses(df_dioceses, 
corpus_christi_county_list, state = 'Texas', diocese = 
'Corpus Christi')

# Diocese of Tyler:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Tyler

tyler_county_list = ['Anderson', 'Angelina', 'Bowie', 'Camp', 'Cass',
'Cherokee', 'Delta', 'Franklin', 'Freestone', 'Gregg', 'Harrison',
'Henderson', 'Hopkins', 'Houston', 'Lamar', 'Leon', 'Madison', 'Marion', 
'Morris', 'Nacogdoches', 'Panola', 'Rains', 'Red River County', 'Rusk', 
'Sabine', 'San Augustine County', 'Shelby', 'Smith', 'Titus', 'Trinity', 
'Upshur', 'Van Zandt County', 'Wood']

df_dioceses = add_dioceses(df_dioceses, 
tyler_county_list, state = 'Texas', diocese = 
'Tyler')

# Diocese of Victoria:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Victoria_in_Texas

victoria_in_texas_county_list = [
'Calhoun', 'Colorado', 'DeWitt', 'Fayette', 'Goliad', 'Jackson', 'Lavaca', 
'Matagorda', 'Victoria', 'Wharton'
] 
df_dioceses = add_dioceses(df_dioceses, 
victoria_in_texas_county_list, state = 'Texas', diocese = 
'Victoria in Texas')

# Archddiocese of San Antonio:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_San_Antonio

san_antonio_county_list = [
'Val Verde County', 'Edwards', 'Kerr', 'Gillespie', 'Kendall', 'Comal',
'Guadalupe', 'Gonzales', 'Uvalde', 'Bandera', 'Real', 'Kinney', 'Medina', 
'Bexar', 'Wilson', 'Karnes', 'Frio', 'Atascosa', 'McMullen'
]
df_dioceses = add_dioceses(df_dioceses, 
san_antonio_county_list, state = 'Texas', diocese = 
'San Antonio')

# Diocese of Amarillo:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Amarillo

amarillo_county_list = [
'Armstrong', 'Briscoe', 'Carson', 'Castro', 'Childress', 'Collingsworth', 
'Dallam', 'Deaf Smith County', 'Donley', 'Gray', 'Hall', 'Hansford', 'Hartley',
'Hemphill', 'Hutchinson', 'Lipscomb', 'Moore', 'Ochiltree', 'Oldham', 'Parmer',
'Potter', 'Randall', 'Roberts', 'Sherman', 'Swisher', 'Wheeler'
]
df_dioceses = add_dioceses(df_dioceses, 
amarillo_county_list, state = 'Texas', diocese = 
'Amarillo')

# Diocese of Dallas:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Dallas

dallas_county_list = [
'Collin', 'Dallas', 'Ellis', 'Fannin', 'Grayson', 'Hunt', 'Kaufman', 'Navarro',
'Rockwall'
]
df_dioceses = add_dioceses(df_dioceses, 
dallas_county_list, state = 'Texas', diocese = 
'Dallas')

# Diocese of El Paso:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_El_Paso
el_paso_county_list = [
'El Paso County', 'Brewster', 'Culberson', 'Hudspeth', 'Jeff Davis County',
'Loving', 'Presidio', 'Reeves', 'Ward', 'Winkler'
] 
df_dioceses = add_dioceses(df_dioceses, 
el_paso_county_list, state = 'Texas', diocese = 
'El Paso')

# Diocese of Fort Worth:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Fort_Worth

fort_worth_county_list = [
'Archer', 'Baylor', 'Bosque', 'Clay', 'Comanche', 'Cooke', 'Denton', 'Eastland',
'Erath', 'Foard', 'Hardeman', 'Hill', 'Hood', 'Jack', 'Johnson', 'Knox', 
'Montague', 'Palo Pinto County', 'Parker', 'Shackelford', 'Somervell', 
'Stephens', 'Tarrant', 'Throckmorton', 'Wichita', 'Wilbarger', 'Wise', 'Young'
]
df_dioceses = add_dioceses(df_dioceses, 
fort_worth_county_list, state = 'Texas', diocese = 
'Fort Worth')

# Diocese of Laredo:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Laredo

laredo_county_list = [
'Dimmit', 'Jim Hogg County', 'La Salle County', 'Maverick', 'Webb', 'Zapata', 
'Zavala']
df_dioceses = add_dioceses(df_dioceses, 
laredo_county_list, state = 'Texas', diocese = 
'Laredo')

# Diocese of San Angelo:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_San_Angelo

san_angelo_county_list = [
'Andrews', 'Brown', 'Callahan', 'Coke', 'Coleman', 'Concho', 'Crane', 
'Crockett', 'Ector', 'Glasscock', 'Howard', 'Irion', 'Kimble', 'Martin', 
'McCulloch', 'Menard', 'Midland', 'Mitchell', 'Nolan', 'Pecos', 'Reagan',
'Runnels', 'Schleicher', 'Sterling', 'Sutton', 'Taylor', 'Terrell', 
'Tom Green County', 'Upton'
]
df_dioceses = add_dioceses(df_dioceses, 
san_angelo_county_list, state = 'Texas', diocese = 
'San Angelo')

# Archdiocese of Hartford:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Hartford

hartford_county_list = [
'Hartford', 'Litchfield', 'New Haven County'
]

df_dioceses = add_dioceses(df_dioceses, 
hartford_county_list, state = 'Connecticut', diocese = 
'Hartford')

# Diocese of Bridgeport:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Bridgeport

df_dioceses.at[
"Fairfield County, Connecticut", 'Diocese'] = 'Bridgeport' 
# The Diocese of Bridgeport includes only one county, so it can
# be added directly to the DataFrame.

# Diocese of Evansville:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Evansville
evansville_county_list = ['Warrick', 'Greene', 'Knox', 'Sullivan', 'Daviess', 
'Martin', 'Dubois', 'Spencer', 'Gibson', 'Pike', 'Posey', 'Vanderburgh']
df_dioceses = add_dioceses(df_dioceses, 
evansville_county_list, state = 'Indiana', diocese = 
'Evansville')


# Diocese of Fort Wayne-South Bend:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Fort_Wayne%E2%80%93South_Bend

fort_wayne_south_bend_county_list = [
'Adams', 'Allen', 'DeKalb', 'Elkhart', 'Huntington', 'Kosciusko', 'LaGrange',
'Marshall', 'Noble', 'Steuben', 'St. Joseph County', 'Wabash', 'Wells', 
'Whitley'
]
df_dioceses = add_dioceses(df_dioceses, 
fort_wayne_south_bend_county_list, state = 'Indiana', diocese = 
'Fort Wayne-South Bend')


# Diocese of Gary:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Gary

gary_county_list = [
'Lake', 'Porter', 'LaPorte', 'Starke'
]
df_dioceses = add_dioceses(df_dioceses, 
gary_county_list, state = 'Indiana', diocese = 
'Gary')

# Diocese of Lafayette in Indiana:
# Source: https://dol-in.org/uih-maps

lafayette_in_indiana_county_list = [
'Newton', 'Jasper', 'Pulaski', 'Fulton', 'Benton', 'White', 'Carroll', 'Cass',
'Miami', 'Warren', 'Tippecanoe', 'Clinton', 'Tipton', 'Grant', 'Blackford', 
'Jay', 'Fountain', 'Montgomery', 'Boone', 'Madison', 'Hamilton', 'Delaware',
'Randolph', 'Howard'
]
df_dioceses = add_dioceses(df_dioceses, 
lafayette_in_indiana_county_list, state = 'Indiana', diocese = 
'Lafayette in Indiana')


# Diocese of Kansas City in Kansas:
# Source: 

kansas_city_in_kansas_county_list = [
'Anderson', 'Atchison', 'Brown', 'Coffey', 'Doniphan', 'Douglas', 'Franklin',
'Jackson', 'Jefferson', 'Johnson', 'Leavenworth', 'Linn', 'Lyon', 'Marshall',
'Miami', 'Nemaha', 'Osage', 'Pottawatomie', 'Shawnee', 'Wabaunsee', 'Wyandotte'
]
df_dioceses = add_dioceses(df_dioceses, 
kansas_city_in_kansas_county_list, state = 'Kansas', diocese = 
'Kansas City in Kansas')

# Diocese of Dodge City:
# Source: https://www.dcdiocese.org/about/history
# Note: This website misspells Comanche as Commanche and Kearny as Kearney.
dodge_city_county_list = [
'Barber', 'Barton', 'Clark', 'Comanche', 'Edwards', 'Finney', 'Ford', 'Grant',
'Gray', 'Greeley', 'Hamilton', 'Haskell', 'Hodgeman', 'Kearny', 'Kiowa', 
'Lane', 'Meade', 'Morton', 'Ness', 'Pawnee', 'Pratt', 'Rush', 'Scott', 'Seward',
'Stafford', 'Stanton', 'Stevens', 'Wichita'
]

df_dioceses = add_dioceses(df_dioceses, 
dodge_city_county_list, state = 'Kansas', diocese = 
'Dodge City')

# Diocese of Wichita:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Wichita
# Note: The map on this page shows Ellsworth County as belonging to
# the Diocese of Wichita. However, Ellsworth County actually belongs
# to the Diocese of Salina: https://salinadiocese.org/wp-content/uploads/2021/08/2021-Salina-Diocese-Map-PARISH-1.pdf

wichita_county_list = [
'Allen', 'Bourbon', 'Butler', 'Chase', 'Chautauqua', 'Cherokee', 'Cowley',
'Crawford', 'Elk', 'Greenwood', 'Harper', 'Harvey', 'Kingman', 'Labette',
'Marion', 'McPherson', 'Montgomery', 'Morris', 'Neosho', 'Reno', 'Rice', 
'Sedgwick', 'Sumner', 'Wilson', 'Woodson'
]

df_dioceses = add_dioceses(df_dioceses, 
wichita_county_list, state = 'Kansas', diocese = 
'Wichita')


# Diocese of Fresno:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Fresno

fresno_county_list = [
'Fresno', 'Inyo', 'Kern', 'Kings', 'Madera', 'Mariposa', 'Merced', 'Tulare'
]
df_dioceses = add_dioceses(df_dioceses, 
fresno_county_list, state = 'California', diocese = 'Fresno')

# Diocese of Monterey
monterey_in_california_county_list = [
'Monterey', 'San Benito County', 'San Luis Obispo County', 'Santa Cruz County'
]

df_dioceses = add_dioceses(df_dioceses, 
monterey_in_california_county_list, state = 'California', 
diocese = 'Monterey')

# Diocese of Orange:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Orange
df_dioceses.at[
"Orange County, California", 'Diocese'] = 'Orange' 

# Diocese of San Bernardino:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_San_Bernardino
san_bernardino_county_list = ['San Bernardino County', 'Riverside']
df_dioceses = add_dioceses(df_dioceses, 
san_bernardino_county_list, state = 'California', 
diocese = 'San Bernardino')

# Diocese of San Diego:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_San_Diego

san_diego_county_list = [
'San Diego County', 'Imperial'
]
df_dioceses = add_dioceses(df_dioceses, 
san_diego_county_list, state = 'California', 
diocese = 'San Diego')


# Diocese of San Francisco:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_San_Francisco

san_francisco_county_list = [
'San Francisco County', 'Marin', 'San Mateo County'
]
df_dioceses = add_dioceses(df_dioceses, 
san_francisco_county_list, state = 'California', 
diocese = 'San Francisco')

# Diocese of Oakland:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Oakland

oakland_county_list = [
'Alameda', 'Contra Costa County'
]
df_dioceses = add_dioceses(df_dioceses, 
oakland_county_list, state = 'California', 
diocese = 'Oakland')

# Diocese of Sacramento:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Sacramento
sacramento_county_list = [
'Siskiyou', 'Modoc', 'Trinity', 'Shasta', 'Lassen', 'Tehama', 'Plumas', 'Glenn',
'Butte', 'Sierra', 'Colusa', 'Sutter', 'Yuba', 'Nevada', 'Yolo', 'Placer', 
'Solano', 'Sacramento', 'El Dorado County', 'Amador'
]
df_dioceses = add_dioceses(df_dioceses, 
sacramento_county_list, state = 'California', 
diocese = 'Sacramento')

# Diocese of San Jose:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_San_Jose_in_California

df_dioceses.at[
"Santa Clara County, California", 'Diocese'] = 'San Jose' 

# Diocese of Santa Rosa:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Santa_Rosa_in_California

santa_rosa_in_california_county_list = [
'Del Norte County', 'Humboldt', 'Lake', 'Mendocino', 'Napa', 'Sonoma'
]

df_dioceses = add_dioceses(df_dioceses, 
santa_rosa_in_california_county_list, state = 'California', 
diocese = 'Santa Rosa')


# Diocese of Stockton:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Stockton

stockton_county_list = [
'Alpine', 'Calaveras', 'Mono', 'San Joaquin County', 'Stanislaus', 'Tuolumne'
]
df_dioceses = add_dioceses(df_dioceses, 
stockton_county_list, state = 'California', 
diocese = 'Stockton')

# Diocese of Las Vegas:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Las_Vegas

las_vegas_county_list = [
'Clark', 'Esmeralda', 'Lincoln', 'Nye', 'White Pine County'
]
df_dioceses = add_dioceses(df_dioceses, 
las_vegas_county_list, state = 'Nevada', 
diocese = 'Las Vegas')



# Diocese of Gallup:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Gallup
gallup_county_list_nm = [
'San Juan County', 'McKinley', 'Cibola', 'Catron']
df_dioceses = add_dioceses(df_dioceses, 
gallup_county_list_nm, state = 'New Mexico', 
diocese = 'Gallup')

# Gallup also has territory in Arizona:
gallup_county_list_az = [
'Navajo', 'Apache'
]
df_dioceses = add_dioceses(df_dioceses, 
gallup_county_list_az, state = 'Arizona', 
diocese = 'Gallup')

# Diocese of Las Cruces:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Las_Cruces

las_cruces_county_list = [
'Hidalgo', 'Grant', 'Luna', 'Sierra', 'Doña Ana County', 'Otero', 'Lincoln', 
'Chaves', 'Eddy', 'Lea'
]
df_dioceses = add_dioceses(df_dioceses, 
las_cruces_county_list, state = 'New Mexico', 
diocese = 'Las Cruces')

# Diocese of Tucson:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Tucson
tucson_county_list = [
'Gila', 'Graham', 'Greenlee', 'Pinal', 'Cochise', 'Santa Cruz County', 
'Pima', 'Yuma', 'La Paz County' 
]
df_dioceses = add_dioceses(df_dioceses, 
tucson_county_list, state = 'Arizona', 
diocese = 'Tucson')

# Archdiocese of Louisville:
# Source: https://www.archlou.org/about-the-archdiocese/history/statistics/
# Note: This list misspells Metcalfe County as 'Metcalf' and Russell County
# as 'Russel.'  
louisville_county_list = [
'Meade', 'Trimble', 'Oldham', 'Henry', 'Jefferson',
'Shelby', 'Spencer', 'Bullitt', 'Hardin', 'Nelson', 'Washington', 'Larue', 
'Marion', 'Hart', 'Green', 'Taylor', 'Casey', 'Barren', 'Metcalfe', 'Adair', 
'Russell', 'Monroe', 'Cumberland', 'Clinton'
] 
df_dioceses = add_dioceses(df_dioceses, 
louisville_county_list, state = 'Kentucky', 
diocese = 'Louisville')

# The Diocese of Lexington counties were added in earlier, but here's a map of
# the diocese's counties anyway: 
# https://www.stjoanhershey.org/blog/special-collection-mission-cooperative-aug-5-6-2017

# Diocese of Covington:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Covington
covington_county_list = [
'Boone', 'Kenton', 'Campbell', 'Gallatin', 'Carroll', 'Grant', 'Owen', 
'Pendleton', 'Harrison', 'Bracken', 'Robertson', 'Mason', 'Fleming', 'Lewis']
df_dioceses = add_dioceses(df_dioceses, 
covington_county_list, state = 'Kentucky', 
diocese = 'Covington')

# Diocese of Owensboro:
# Source: https://owensborodiocese.org/our-diocese/
owensboro_county_list = [
'Fulton', 'Hickman', 'Carlisle', 'Ballard', 'McCracken', 'Graves', 'Marshall',
'Calloway', 'Trigg', 'Lyon', 'Caldwell', 'Crittenden', 'Union', 'Henderson', 
'Webster', 'Hancock', 'Ohio', 'Butler', 'Warren', 'Edmonson', 'Grayson',
'Breckinridge', 'Todd', 'Logan', 'Simpson', 'Allen', 'Livingston', 
'Christian', 'Hopkins', 'Muhlenberg', 'McLean', 'Daviess' 
]
df_dioceses = add_dioceses(df_dioceses, 
owensboro_county_list, state = 'Kentucky', 
diocese = 'Owensboro')

# Diocese of Knoxville:
# Source: https://dioknox.org/about (Doesn't include county names, so I looked
# on the map of US County shapefiles to identify them)

knoxville_county_list = [
'Polk', 'Bradley', 'Hamilton', 'Marion', 'Sequatchie',
'Bledsoe', 'Cumberland', 'Fentress', 'Pickett', 'Scott', 'Morgan', 'Roane',
'Rhea', 'Meigs', 'McMinn', 'Monroe', 'Blount', 'Knox', 'Anderson', 'Campbell',
'Claiborne', 'Union', 'Grainger', 'Jefferson', 'Sevier', 'Cocke', 'Greene',
'Hawkins', 'Sullivan', 'Washington', 'Unicoi', 'Carter', 'Johnson', 'Loudon',
'Hamblen', 'Hancock'
]
df_dioceses = add_dioceses(df_dioceses, 
knoxville_county_list, state = 'Tennessee', 
diocese = 'Knoxville')

# Diocese of Memphis:
# Source: https://cdom.org/wp-content/uploads/2021/08/Aug-2021-Parish-Directory-Public.pdf
# (Doesn't include county names, so I used the map of US County shapefiles
# to identify them)
memphis_county_list = [
'Shelby', 'Tipton', 'Lauderdale', 'Dyer', 'Lake', 'Obion', 'Crockett', 
'Hardin', 'Decatur', 'Benton', 'Henry', 'Carroll', 'Henderson', 'Chester', 
'McNairy', 'Hardeman', 'Fayette', 'Haywood', 'Gibson', 'Weakley', 'Madison'
]
df_dioceses = add_dioceses(df_dioceses, 
memphis_county_list, state = 'Tennessee', 
diocese = 'Memphis')

# Archdiocese of Miami:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Miami
miami_county_list = [
'Broward', 'Miami-Dade', 'Monroe'
]
df_dioceses = add_dioceses(df_dioceses, 
miami_county_list, state = 'Florida', 
diocese = 'Miami')

# Diocese of Palm Beach:
# Source: https://www.diocesepb.org/about-us/

palm_beach_county_list = [
'Palm Beach County', 'Martin', 'St. Lucie County', 'Indian River County', 
'Okeechobee'
]
df_dioceses = add_dioceses(df_dioceses, 
palm_beach_county_list, state = 'Florida', 
diocese = 'Palm Beach')

# Diocese of Venice:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Venice_in_Florida

venice_in_florida_county_list = [
'Charlotte', 'Collier', 'DeSoto', 'Glades', 'Hardee', 'Hendry', 'Highlands', 
'Lee', 'Manatee', 'Sarasota'
]
df_dioceses = add_dioceses(df_dioceses, 
venice_in_florida_county_list, state = 'Florida', 
diocese = 'Venice')

# Diocese of Pensacola-Tallahassee:
# Source: https://ptdiocese.org/pictures/2017/1/Standard%20Deanery%20Map%202017.png

pensacola_tallahassee_county_list = [
'Escambia', 'Santa Rosa County', 'Okaloosa', 'Walton', 'Holmes', 'Washington',
'Jackson', 'Bay', 'Calhoun', 'Gulf', 'Liberty', 'Franklin', 'Wakulla', 
'Leon', 'Gadsden', 'Jefferson', 'Madison', 'Taylor'
]
df_dioceses = add_dioceses(df_dioceses, 
pensacola_tallahassee_county_list, state = 'Florida', 
diocese = 'Pensacola-Tallahassee')


# Diocese of St. Petersburg:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Saint_Petersburg
saint_petersburg_county_list = [
'Pinellas', 'Hillsborough', 'Pasco', 'Hernando', 'Citrus'
]
df_dioceses = add_dioceses(df_dioceses, 
saint_petersburg_county_list, state = 'Florida', 
diocese = 'St. Petersburg')

# Diocese of St. Augustine:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_St._Augustine
st_augustine_county_list = [
'Alachua', 'Baker', 'Bradford', 'Clay', 'Columbia', 'Dixie', 'Duval', 'Flagler',
'Gilchrist', 'Hamilton', 'Lafayette', 'Levy', 'Nassau', 'Putnam', 
'St. Johns County', 'Suwannee', 'Union'
]
df_dioceses = add_dioceses(df_dioceses, 
st_augustine_county_list, state = 'Florida', 
diocese = 'St. Augustine')

# Archdiocese of Milwaukee:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Milwaukee

milwaukee_county_list = [
'Dodge', 'Fond du Lac County', 'Kenosha', 'Milwaukee', 'Ozaukee', 'Racine',
'Sheboygan', 'Walworth', 'Washington', 'Waukesha'
]
df_dioceses = add_dioceses(df_dioceses, 
milwaukee_county_list, state = 'Wisconsin', 
diocese = 'Milwaukee')

# Diocese of Green Bay:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Green_Bay

green_bay_county_list = [
'Brown', 'Calumet', 'Door', 'Florence', 'Forest', 'Kewaunee', 'Langlade', 
'Manitowoc', 'Marinette', 'Menominee', 'Oconto', 'Outagamie', 'Shawano',
'Waupaca', 'Waushara', 'Winnebago'
]
df_dioceses = add_dioceses(df_dioceses, 
green_bay_county_list, state = 'Wisconsin', 
diocese = 'Green Bay')

# Diocese of Madison:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Madison

madison_county_list = ['Columbia', 'Dane', 'Grant', 'Green', 
'Green Lake County', 'Iowa', 'Jefferson', 'Lafayette', 'Marquette', 
'Rock', 'Sauk'
]
df_dioceses = add_dioceses(df_dioceses, 
madison_county_list, state = 'Wisconsin', 
diocese = 'Madison')

# Diocese of Superior:
# https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Superior

superior_county_list = [
'Ashland', 'Barron', 'Bayfield', 'Burnett', 'Douglas', 'Iron', 'Lincoln', 
'Oneida', 'Price', 'Polk', 'Rusk', 'Sawyer', 'St. Croix County', 'Taylor',
'Vilas', 'Washburn'
]
df_dioceses = add_dioceses(df_dioceses, 
superior_county_list, state = 'Wisconsin', 
diocese = 'Superior')

# Diocese of Biloxi:
# Source: https://biloxidiocese.org/geographics

biloxi_county_list = [
'Covington', 'Forrest', 'George', 'Greene', 'Hancock', 'Harrison', 'Jackson', 
'Jefferson Davis County', 'Jones', 'Lamar', 'Lawrence', 'Marion', 
'Pearl River County', 'Perry', 'Stone', 'Walthall', 'Wayne'
]
df_dioceses = add_dioceses(df_dioceses, 
biloxi_county_list, state = 'Mississippi', 
diocese = 'Biloxi')


# Diocese of Birmingham:
# Source: https://bhmdiocese.org/documents/2021/12/Dio%20info%2012-13-21.pdf

birmingham_county_list = [
'Lauderdale', 'Limestone', 'Madison', 'Jackson', 'Colbert', 'Franklin', 
'Lawrence', 'Morgan', 'Marshall', 'DeKalb', 'Marion', 'Winston', 'Cullman', 
'Blount', 'Etowah', 'Cherokee', 'Lamar', 'Fayette', 'Walker', 'Jefferson',
'St. Clair County', 'Calhoun', 'Cleburne', 'Pickens', 'Tuscaloosa', 'Bibb', 
'Shelby', 'Talladega', 'Clay', 'Randolph', 'Sumter', 'Greene', 'Hale', 'Perry', 
'Chilton', 'Coosa', 'Tallapoosa', 'Chambers', 'Marengo'
]
df_dioceses = add_dioceses(df_dioceses, 
birmingham_county_list, state = 'Alabama', 
diocese = 'Birmingham')

# Archdiocese of New Orleans:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_New_Orleans
new_orleans_county_list = [
'Jefferson Parish', 'Orleans Parish', 'Plaquemines Parish', 
'St. Bernard Parish', 'St. Charles Parish', 'St. John the Baptist Parish',
'St. Tammany Parish', 'Washington Parish'
] 

df_dioceses = add_dioceses(df_dioceses, 
new_orleans_county_list, state = 'Louisiana', 
diocese = 'New Orleans')

# Diocese of Houma-Thibodaux:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Houma%E2%80%93Thibodaux

houma_thibodaux_county_list = ['Terrebonne Parish', 'Lafourche Parish']
df_dioceses = add_dioceses(df_dioceses, 
houma_thibodaux_county_list, state = 'Louisiana', 
diocese = 'Houma-Thibodaux')


# Diocese of Lafayette in Louisiana:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Lafayette_in_Louisiana
 
lafayette_in_louisiana_county_list = [
'St. Landry Parish', 'Evangeline Parish', 'Lafayette Parish', 
'St. Martin Parish', 'Iberia Parish', 'St. Mary Parish', 'Acadia Parish',
'Vermilion Parish'
]
df_dioceses = add_dioceses(df_dioceses, 
lafayette_in_louisiana_county_list, state = 'Louisiana', 
diocese = 'Lafayette in Louisiana')

# Diocese of Baton Rouge:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Baton_Rouge

baton_rouge_county_list = [
'Ascension Parish', 'Assumption Parish', 'East Baton Rouge Parish', 
'East Feliciana Parish', 'Iberville Parish', 'Livingston Parish', 
'Pointe Coupee Parish', 'Tangipahoa Parish', 'St. Helena Parish', 
'St. James Parish', 'West Baton Rouge Parish', 'West Feliciana Parish'
]
df_dioceses = add_dioceses(df_dioceses, 
baton_rouge_county_list, state = 'Louisiana', 
diocese = 'Baton Rouge')

# Diocese of Lake Charles:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Lake_Charles

lake_charles_county_list = [
'Allen Parish', 'Beauregard Parish', 'Calcasieu Parish', 'Cameron Parish',
'Jefferson Davis Parish'
]
df_dioceses = add_dioceses(df_dioceses, 
lake_charles_county_list, state = 'Louisiana', 
diocese = 'Lake Charles')

# Diocese of Alexandria:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Alexandria_in_Louisiana

alexandria_in_louisiana_county_list = [
'Avoyelles Parish', 'Rapides Parish', 'Vernon Parish', 'Natchitoches Parish',
'Winn Parish', 'Caldwell Parish', 'Madison Parish', 'Franklin Parish', 
'Tensas Parish', 'Concordia Parish', 'Catahoula Parish', 'LaSalle Parish',
'Grant Parish'
]
df_dioceses = add_dioceses(df_dioceses, 
alexandria_in_louisiana_county_list, state = 'Louisiana', 
diocese = 'Alexandria')

# Archdiocese of New York:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_New_York
new_york_county_list = ['New York County', 'Richmond', 'Bronx', 'Dutchess',
'Orange', 'Putnam', 'Rockland', 'Sullivan', 'Ulster', 'Westchester'
]
df_dioceses = add_dioceses(df_dioceses, 
new_york_county_list, state = 'New York', 
diocese = 'New York')

# Diocese of Brooklyn:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Brooklyn
brooklyn_county_list = [
'Kings', 'Queens'
]
df_dioceses = add_dioceses(df_dioceses, 
brooklyn_county_list, state = 'New York', 
diocese = 'Brooklyn')

# Diocese of Buffalo:
# https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Buffalo

buffalo_county_list = [
'Erie', 'Niagara', 'Genesee', 'Orleans', 'Chautauqua', 'Wyoming', 
'Cattaraugus', 'Allegany'
]
df_dioceses = add_dioceses(df_dioceses, 
buffalo_county_list, state = 'New York', 
diocese = 'Buffalo')

# Diocese of Rockville Centre:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Rockville_Centre

rockville_centre_county_list = [
'Nassau', 'Suffolk'
]
df_dioceses = add_dioceses(df_dioceses, 
rockville_centre_county_list, state = 'New York', 
diocese = 'Rockville Centre')

# Diocese of Ogdensburg:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Ogdensburg

ogdensburg_county_list = [
'Clinton', 'Essex', 'Franklin', 'Jefferson', 'Lewis', 'St. Lawrence County', 
'Hamilton'
] 

df_dioceses = add_dioceses(df_dioceses, 
ogdensburg_county_list, state = 'New York', 
diocese = 'Ogdensburg')

# Diocese of Rochester:
# Source: 

rochester_county_list = [
'Monroe', 'Cayuga', 'Livingston', 'Wayne', 'Tioga', 'Tompkins', 'Ontario', 
'Seneca', 'Schuyler', 'Yates', 'Steuben', 'Chemung'
]
df_dioceses = add_dioceses(df_dioceses, 
rochester_county_list, state = 'New York', 
diocese = 'Rochester')

# Diocese of Syracuse: 
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Syracuse

syracuse_county_list = [
'Broome', 'Chenango', 'Cortland', 'Madison', 'Oneida', 'Onondaga', 'Oswego']
df_dioceses = add_dioceses(df_dioceses, 
syracuse_county_list, state = 'New York', 
diocese = 'Syracuse')

# Archdiocese of Neawrk:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Newark

newark_county_list = ['Bergen', 'Union', 'Hudson', 'Essex']
df_dioceses = add_dioceses(df_dioceses, 
newark_county_list, state = 'New Jersey', 
diocese = 'Newark')

# Diocese of Metuchen:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Metuchen

metuchen_county_list = [
'Middlesex', 'Somerset', 'Hunterdon', 'Warren'
]
df_dioceses = add_dioceses(df_dioceses, 
metuchen_county_list, state = 'New Jersey', 
diocese = 'Metuchen')

# Diocese of Paterson:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Paterson

paterson_county_list = [
'Passaic', 'Morris', 'Sussex'
]
df_dioceses = add_dioceses(df_dioceses, 
paterson_county_list, state = 'New Jersey', 
diocese = 'Paterson')

# Diocese of Trenton:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Trenton

trenton_county_list = [
'Burlington', 'Mercer', 'Monmouth', 'Ocean'
]
df_dioceses = add_dioceses(df_dioceses, 
trenton_county_list, state = 'New Jersey', 
diocese = 'Trenton')


# Diocese of Tulsa:
# Source: https://d2y1pz2y630308.cloudfront.net/2682/documents/2022/3/revised%20vicariate%20full%20map.pdf
# (This map does not include county names, so I used the county shapefile 
# map to identify counties within the diocese.)

tulsa_county_list = [
'McCurtain', 'Choctaw', 'Bryan', 'Atoka', 'Pushmataha', 'Latimer', 'Coal', 
'Hughes', 'Okfuskee', 'Creek', 'Payne', 'Pawnee', 'Osage', 
'Washington', 'Nowata', 'Craig', 'Ottawa', 'Delaware', 'Adair', 'Sequoyah',
'Le Flore County', 'Pittsburg', 'McIntosh', 'Okmulgee',
'Tulsa', 'Rogers', 'Wagoner', 'Cherokee', 'Muskogee', 'Haskell', 'Mayes']
df_dioceses = add_dioceses(df_dioceses, 
tulsa_county_list, state = 'Oklahoma', 
diocese = 'Tulsa')

# Archdiocese of Ohama:
# Source: https://archomaha.org/about-us/
# Note: Parish data on the Grand Island and Lincoln diocesan webpages 
# indicate that Wheeler, Greeley, Howard, and Hall Counties do not belong
# to the Archdiocese of Omaha, so I've excluded them from the list below.
# See https://gidiocese.org/parishfinder (note that one of the parishes is
# in Wheeler County) and https://www.lincolndiocese.org/directory/parish-map .

omaha_county_list = [
'Boyd', 'Holt', 'Merrick', 'Nance', 'Boone', 'Antelope', 'Knox', 'Pierce', 
'Madison', 'Platte', 'Colfax', 'Stanton', 'Wayne', 'Cedar', 'Dixon', 'Dakota',
'Thurston', 'Cuming', 'Dodge', 'Burt', 'Washington',
'Douglas', 'Sarpy']

df_dioceses = add_dioceses(df_dioceses, 
omaha_county_list, state = 'Nebraska', 
diocese = 'Omaha')

# Archdiocese of Lincoln:
# Source: https://commons.wikimedia.org/wiki/File:Diocese_of_Lincoln_map_1.png
# See also: https://www.lincolndiocese.org/diocese/about-the-diocese/history-of-the-diocese

lincoln_county_list = [
'Richardson', 'Nemaha', 'Otoe', 'Cass', 'Pawnee', 'Johnson', 'Lancaster', 
'Saunders', 'Butler', 'Polk', 'Hamilton', 'Clay', 'Nuckolls', 'Thayer', 
'Jefferson', 'Gage', 'Webster', 'Adams', 'Kearney', 'Franklin', 'Harlan', 
'Furnas', 'Gosper', 'Lincoln', 'Frontier', 'Red Willow County', 'Hitchcock',
'Dundy', 'Hayes', 'Chase', 'Perkins', 'Phelps', 'York', 'Seward', 'Fillmore', 
'Saline'
]
df_dioceses = add_dioceses(df_dioceses, 
lincoln_county_list, state = 'Nebraska', 
diocese = 'Lincoln')

# Archdiocese of Philadelphia:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Philadelphia

philadelphia_county_list = [
'Bucks', 'Chester', 'Delaware', 'Montgomery', 'Philadelphia'
]
df_dioceses = add_dioceses(df_dioceses, 
philadelphia_county_list, state = 'Pennsylvania', 
diocese = 'Philadelphia')

# Diocese of Allentown:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Allentown

allentown_county_list = [
'Berks', 'Carbon', 'Lehigh', 'Northampton', 'Schuylkill'
]
df_dioceses = add_dioceses(df_dioceses, 
allentown_county_list, state = 'Pennsylvania', 
diocese = 'Allentown')

# Diocese of Altoona-Johnstown:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Altoona%E2%80%93Johnstown


altoona_johnstown_county_list = [
'Bedford', 'Blair', 'Cambria', 'Centre', 'Clinton', 'Fulton', 'Huntingdon',
'Somerset'
]
df_dioceses = add_dioceses(df_dioceses, 
altoona_johnstown_county_list, state = 'Pennsylvania', 
diocese = 'Altoona-Johnstown')

# Diocese of Harrisburg:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Harrisburg

harrisburg_county_list = [
'Adams', 'Columbia', 'Cumberland', 'Dauphin', 'Franklin', 'Juniata', 
'Lancaster', 'Lebanon', 'Mifflin', 'Montour', 'Northumberland', 'Perry', 
'Snyder', 'Union', 'York'
]
df_dioceses = add_dioceses(df_dioceses, 
harrisburg_county_list, state = 'Pennsylvania', 
diocese = 'Harrisburg')

# Diocese of Greensburg:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Greensburg

greensburg_county_list = [
'Armstrong', 'Fayette', 'Indiana', 'Westmoreland'
]
df_dioceses = add_dioceses(df_dioceses, 
greensburg_county_list, state = 'Pennsylvania', 
diocese = 'Greensburg')

# Diocese of Pittsburgh:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Pittsburgh

pittsburgh_county_list = [
'Allegheny', 'Beaver', 'Butler', 'Greene', 'Lawrence', 'Washington'
]
df_dioceses = add_dioceses(df_dioceses, 
pittsburgh_county_list, state = 'Pennsylvania', 
diocese = 'Pittsburgh')

# Diocese of Scranton:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Scranton
scranton_county_list = [
'Lackawanna', 'Luzerne', 'Bradford', 'Susquehanna', 'Wayne', 'Tioga', 
'Sullivan', 'Wyoming', 'Lycoming', 'Pike', 'Monroe'
]
df_dioceses = add_dioceses(df_dioceses, 
scranton_county_list, state = 'Pennsylvania', 
diocese = 'Scranton')

# Diocese of Baker:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Baker

baker_county_list = [
'Baker', 'Crook', 'Deschutes', 'Gilliam', 'Grant', 'Harney', 
'Hood River County', 'Jefferson', 'Klamath', 'Lake', 'Malheur', 'Morrow', 
'Sherman', 'Umatilla', 'Union', 'Wallowa', 'Wasco', 'Wheeler'
]
df_dioceses = add_dioceses(df_dioceses, 
baker_county_list, state = 'Oregon', 
diocese = 'Baker')

# Diocese of Great Falls-Billings:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Great_Falls%E2%80%93Billings
# Note: I updated the source to include McCone county, which is encompassed
# by other counties in the diocese.

great_falls_billings_county_list = [
'Big Horn County', 'Blaine', 'Carbon', 'Carter', 'Cascade', 'Chouteau', 
'Custer', 'Daniels', 'Dawson', 'Fallon', 'Fergus', 'Garfield', 
'Golden Valley County', 'Hill', 'Judith Basin County', 'Liberty', 'McCone',
'Musselshell', 'Park', 'Petroleum', 'Phillips', 'Powder River County', 
'Prairie', 'Richland', 'Roosevelt', 'Rosebud', 'Sheridan', 'Stillwater', 
'Sweet Grass County', 'Treasure', 'Valley', 'Wibaux', 'Yellowstone'
]

df_dioceses = add_dioceses(df_dioceses, 
great_falls_billings_county_list, state = 'Montana', 
diocese = 'Great Falls-Billings')

# Archdiocese of St. Louis:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_St._Louis

st_louis_county_list = [
'Franklin', 'Jefferson', 'Lincoln', 'Perry', 'St. Charles County', 
'St. Francois County', 'Ste. Genevieve County', 'St. Louis County', 'Warren', 
'Washington', 'St. Louis city']

df_dioceses = add_dioceses(df_dioceses, 
st_louis_county_list, state = 'Missouri', 
diocese = 'St. Louis')

# Diocese of Kansas City-St. Joseph:
# Source: https://www.lifeandjusticekcsj.org/diocese-map.html
# (Website is affiliated with two diocesan offices)

kansas_city_st_joseph_county_list = [
'Andrew', 'Atchison', 'Bates', 'Buchanan', 'Caldwell', 'Carroll', 'Cass', 
'Clay', 'Clinton', 'Daviess', 'DeKalb', 'Gentry', 'Grundy', 'Harrison', 'Henry',
'Holt', 'Jackson', 'Johnson', 'Lafayette', 'Livingston', 'Mercer', 'Nodaway',
'Platte', 'Ray', 'St. Clair County', 'Vernon', 'Worth']
df_dioceses = add_dioceses(df_dioceses, 
kansas_city_st_joseph_county_list, state = 'Missouri', 
diocese = 'Kansas City-St. Joseph')

# Diocese of Jefferson City:
# Source: https://diojeffcity.org/about-us/

jefferson_city_county_list = [
'Putnam', 'Schuyler', 'Scotland', 'Clark', 'Sullivan', 'Adair', 'Knox', 'Lewis',
'Linn', 'Macon', 'Shelby', 'Marion', 'Chariton', 'Randolph', 'Monroe', 'Ralls',
'Pike', 'Saline', 'Howard', 'Boone', 'Audrain', 'Pettis', 'Cooper', 'Moniteau',
'Cole', 'Callaway', 'Osage', 'Montgomery', 'Gasconade', 'Benton', 'Morgan', 
'Hickory', 'Camden', 'Miller', 'Maries', 'Pulaski', 'Phelps', 'Crawford'
]
df_dioceses = add_dioceses(df_dioceses, 
jefferson_city_county_list, state = 'Missouri', 
diocese = 'Jefferson City')

# Archdiocese of St. Paul and Minneapolis:
# Source: https://commons.wikimedia.org/wiki/File:Map_of_the_Catholic_archdiocese_of_Saint_Paul_%26_Minneapolis.svg
# See also: https://s3.amazonaws.com/archspmmainsite/Resources/ArchMap--Parishes-Deaneries-COLORRamped_061516.pdf

saint_paul_and_minneapolis_county_list = [
'Goodhue', 'Rice', 'Le Sueur County', 'Scott', 'Dakota', 'Washington', 'Ramsey',
'Hennepin', 'Wright', 'Anoka', 'Chisago', 'Carver'
]
df_dioceses = add_dioceses(df_dioceses, 
saint_paul_and_minneapolis_county_list, state = 'Minnesota', 
diocese = 'St. Paul and Minneapolis')

# Diocese of Crookston:
# https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Crookston

crookston_county_list = [
'Kittson', 'Roseau', 'Lake of the Woods County', 'Marshall', 'Polk', 
'Red Lake County', 'Pennington', 'Clearwater', 'Beltrami', 'Norman', 'Mahnomen', 
'Hubbard', 'Clay', 'Becker'
]
df_dioceses = add_dioceses(df_dioceses, 
crookston_county_list, state = 'Minnesota', 
diocese = 'Crookston')

# Diocese of New Ulm:
# Source: https://www.dnu.org/about

new_ulm_county_list = [
'Big Stone County', 'Brown', 'Chippewa', 'Kandiyohi', 'Lac qui Parle County',
'Lincoln', 'Lyon', 'McLeod', 'Meeker', 'Nicollet', 'Redwood', 'Renville',
'Sibley', 'Swift', 'Yellow Medicine County'
]
df_dioceses = add_dioceses(df_dioceses, 
new_ulm_county_list, state = 'Minnesota', 
diocese = 'New Ulm')

# Diocese of St. Cloud
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Saint_Cloud

saint_cloud_county_list = [
'Benton', 'Douglas', 'Grant', 'Isanti', 'Kanabec', 'Mille Lacs County', 
'Morrison', 'Otter Tail County', 'Pope', 'Sherburne', 'Stearns', 'Stevens',
'Todd', 'Traverse', 'Wadena', 'Wilkin'
]
df_dioceses = add_dioceses(df_dioceses, 
saint_cloud_county_list, state = 'Minnesota', 
diocese = 'St. Cloud')


# Diocese of Winona-Rochester:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Winona%E2%80%93Rochester

winona_rochester_county_list = [
'Blue Earth County', 'Cottonwood', 'Dodge', 'Faribault', 'Fillmore', 'Freeborn',
'Houston', 'Jackson', 'Martin', 'Mower', 'Murray', 'Nobles', 'Olmsted',
'Pipestone', 'Rock', 'Steele', 'Wabasha', 'Waseca', 'Watonwan', 'Winona'
]
df_dioceses = add_dioceses(df_dioceses, 
winona_rochester_county_list, state = 'Minnesota', 
diocese = 'Winona-Rochester')

# Diocese of Bismark:
# Source https://bismarckdiocese.com/about

bismark_county_list = [
'Adams', 'Billings', 'Bowman', 'Burke', 'Burleigh', 'Divide', 'Dunn', 'Emmons', 
'Golden Valley County', 'Grant', 'Hettinger', 'McKenzie', 'McLean', 'Mercer', 
'Morton', 'Mountrail', 'Oliver', 'Renville', 'Sioux', 'Slope', 'Stark', 'Ward', 
'Williams'
]
df_dioceses = add_dioceses(df_dioceses, 
bismark_county_list, state = 'North Dakota', 
diocese = 'Bismark')

# Diocese of Rapid City:
# Source: https://www.rapidcitydiocese.org/wp-content/uploads/2022/01/MapDeaneryDec21-1030x752-1.jpeg

rapid_city_county_list = [
'Corson', 'Dewey', 'Stanley', 'Lyman', 'Gregory', 'Tripp', 'Todd', 'Bennett',
'Oglala Lakota County', 'Fall River County', 'Custer', 'Pennington', 'Lawrence',
'Meade', 'Butte', 'Harding', 'Perkins', 'Ziebach', 'Haakon', 'Jackson',
'Jones', 'Mellette']
df_dioceses = add_dioceses(df_dioceses, 
rapid_city_county_list, state = 'South Dakota', 
diocese = 'Rapid City')

# Diocese of Spokane:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Spokane

spokane_county_list = [
'Okanogan', 'Ferry', 'Stevens', 'Pend Oreille County', 'Lincoln', 'Spokane',
'Adams', 'Whitman', 'Franklin', 'Walla Walla County', 'Columbia', 'Garfield',
'Asotin'
]
df_dioceses = add_dioceses(df_dioceses, 
spokane_county_list, state = 'Washington', 
diocese = 'Spokane')

# Diocese of Yakkima:
# Source: https://en.wikipedia.org/wiki/Roman_Catholic_Diocese_of_Yakima

yakima_county_list = [
'Benton', 'Chelan', 'Douglas', 'Grant', 'Kittitas', 'Klickitat', 'Yakima'
]
df_dioceses = add_dioceses(df_dioceses, 
yakima_county_list, state = 'Washington', 
diocese = 'Yakima')


# county_list = [
# '', '', '', '', '', '', '', '', '', '',
# '', '', '', '', '', '', '', '', '', '',
# '', '', '', '', '', '', '', '', '', '',
# '', '', '', '', '', '', '', '', '', '',
# '', '', '', '', '', '', '', '', '', '',
# ]

# List of Catholic Dioceses in the US:
# https://en.wikipedia.org/wiki/List_of_Catholic_dioceses_in_the_United_States


df_dioceses.reset_index(drop=True, inplace = True) # The county_state column
# was kept in place even when county_state also served as the index, so
# its data is preserved even after the index gets reset.


counties_changed = [1 for i in range(len(df_dioceses)) 
if df_dioceses.iloc[i, df_dioceses.columns.get_loc(
    'Diocese')] != initial_version_of_df_dioceses.iloc[
        i, initial_version_of_df_dioceses.columns.get_loc(
            'Diocese')]]
len(counties_changed) # The number of counties that were modified above

1765


df_dioceses.head(5)


if 'Province' in df_dioceses.columns:
    df_dioceses.drop('Province', axis = 1, inplace = True)
    # This prevents two 'Province' columns from existing within df_dioceses.

df_provinces = pd.read_csv('diocese_province_list.csv')
df_dioceses = df_dioceses.merge(df_provinces, on = 'Diocese', how = 'left')
df_dioceses.drop_duplicates('Diocese').sort_values('Province').tail(5)


df_dioceses.groupby('Diocese').count().sort_values(['STATEFP'], 
ascending = False).head(15)['COUNTYFP']

Diocese
Richmond                      105
Savannah                       90
Little Rock                    75
Atlanta                        69
Jackson                        65
Wheeling-Charleston            55
Raleigh                        54
Lexington                      50
Oklahoma City                  46
Charleston                     46
Charlotte                      46
Sioux Falls                    44
Boise                          44
Springfield-Cape Girardeau     39
Birmingham                     39
Name: COUNTYFP, dtype: int64


df_dioceses.groupby('Diocese').count().sort_values(
    ['STATEFP']).head(5)['COUNTYFP']

Diocese
Bridgeport          1
San Jose            1
Worcester           1
Orange              1
Rockville Centre    2
Name: COUNTYFP, dtype: int64


df_dioceses.set_index('county_state', drop = False, inplace = True) # Once 
# again, the index of df_dioceses will be temporarily set to a copy of 
# county_state in order to facilitate the use of .at[]. 
df_dioceses['Diocese_Detail'] = df_dioceses['Diocese']
df_dioceses['Province_Detail'] = df_dioceses['Province']

df_dioceses.at['Plymouth County, Massachusetts', 'Diocese_Detail'
] = 'Boston, Fall River'
df_dioceses.at['Fayette County, Texas', 'Diocese_Detail'
] = 'Austin, Victoria'

df_dioceses.at['McMullen County, Texas', 'Diocese_Detail'
] = 'Corpus Christi, San Antonio'
df_dioceses.at['McMullen County, Texas', 'Province_Detail'
] = 'Galveston-Houston, San Antonio'

df_dioceses.at['Spencer County, Indiana', 'Diocese_Detail'
] = 'Evansville, Indianapolis'
df_dioceses.at['Rio Arriba County, New Mexico', 'Diocese_Detail'
] = 'Gallup, Santa Fe'
df_dioceses.at['Sandoval County, New Mexico', 'Diocese_Detail'
] = 'Gallup, Santa Fe'
df_dioceses.at['Bernalillo County, New Mexico', 'Diocese_Detail'
] = 'Gallup, Santa Fe'
df_dioceses.at['Valencia County, New Mexico', 'Diocese_Detail'
] = 'Gallup, Santa Fe'
df_dioceses.at['Pinal County, Arizona', 'Diocese_Detail'
] = 'Phoenix, Tucson'
df_dioceses.at['Coconino County, Arizona', 'Diocese_Detail'
] = 'Gallup, Phoenix'
df_dioceses.at['Jefferson Parish, Louisiana', 'Diocese_Detail'
] = 'Houma-Thibodaux, New Orleans'
df_dioceses.at['St. Mary Parish, Louisiana', 'Diocese_Detail'
] = 'Houma-Thibodaux, Lafayette in Louisiana'

df_dioceses.at['Suffolk County, New York', 'Diocese_Detail'
] = 'Norwich, Rockville Centre'
df_dioceses.at['Suffolk County, New York', 'Diocese_Detail'
] = 'Hartford, New York'

df_dioceses.at['Herkimer County, New York', 'Diocese_Detail'
] = 'Albany, Ogdensburg'
df_dioceses.at['Hamilton County, New York', 'Diocese_Detail'
] = 'Albany, Ogdensburg'
df_dioceses.at['Deuel County, Nebraska', 'Diocese_Detail'
] = 'Grand Island, Lincoln'
df_dioceses.at['Keith County, Nebraska', 'Diocese_Detail'
] = 'Grand Island, Lincoln'
df_dioceses.at['Lincoln County, Nebraska', 'Diocese_Detail'
] = 'Grand Island, Lincoln'
df_dioceses.at['Dawson County, Nebraska', 'Diocese_Detail'
] = 'Grand Island, Lincoln'
df_dioceses.at['Hall County, Nebraska', 'Diocese_Detail'
] = 'Grand Island, Lincoln'
df_dioceses.at['Toole County, Montana', 'Diocese_Detail'
] = 'Great Falls-Billings, Helena'
df_dioceses.at['Teton County, Montana', 'Diocese_Detail'
] = 'Great Falls-Billings, Helena'

df_dioceses.at['Fremont County, Idaho', 'Diocese_Detail'
] = 'Boise, Cheyenne'
df_dioceses.at['Fremont County, Idaho', 'Province_Detail'
] = 'Portland in Oregon, Denver'
df_dioceses.at['Gallatin County, Montana', 'Diocese_Detail'
] = 'Cheyenne, Helena'
df_dioceses.at['Gallatin County, Montana', 'Province_Detail'
] = 'Denver, Portland in Oregon'
df_dioceses.at['Park County, Montana', 'Diocese_Detail'
] = 'Cheyenne, Great Falls-Billings'
df_dioceses.at['Park County, Montana', 'Province_Detail'
] = 'Denver, Portland in Oregon'


df_dioceses.at['Bottineau County, North Dakota', 'Diocese_Detail'
] = 'Bismark, Fargo'

df_dioceses.reset_index(drop=True, inplace = True)


if generate_county_list_and_boundaries == True:
    # See https://geopandas.org/en/stable/docs/user_guide/aggregation_with_dissolve.html
    diocese_boundaries = df_dioceses.dissolve(by = 'Diocese')
    diocese_boundaries['geometry'] = diocese_boundaries.simplify(
        tolerance = simplification_level)
    diocese_boundaries['Diocese'] = diocese_boundaries.index 
    diocese_boundaries.reset_index(drop=True,inplace=True)
    diocese_boundaries.to_file('diocese_boundaries.geojson', driver = 'GeoJSON')
    # Now that these borders have been generated, they can be loaded into the
    # script near the beginning in order to save processing time.
    diocese_boundaries.head(5)


if generate_county_list_and_boundaries == True:
    province_boundaries = df_dioceses.dissolve(by = 'Province')
    province_boundaries['geometry'] = province_boundaries.simplify(
        tolerance = simplification_level) 
    province_boundaries.to_file('province_boundaries.geojson', 
    driver = 'GeoJSON')
    province_boundaries.head(5)


df_dioceses['geometry'] = df_dioceses.simplify(tolerance = simplification_level)


df_dioceses


df_dioceses.to_file('counties_by_diocese.geojson', driver = 'GeoJSON')
# This raises a ValueError if the index is set to county_state, 
# though I'm not sure why.
# This .geojson file can also be loaded in at the start of the program to save
# processing time.


df_dioceses.sort_values('Diocese', inplace = True) 
# Sorts the dioceses alphabetically so that the colors are not determined by 
# the order in which the dioceses were added
df_diocese_numbers = pd.DataFrame(list(enumerate(pd.unique(
    df_dioceses['Diocese']))))
df_diocese_numbers.columns = ['Diocese_Color_Code', 'Diocese']
df_diocese_numbers


if 'Diocese_Color_Code' in df_dioceses:
    df_dioceses.drop('Diocese_Color_Code', axis = 1, inplace = True)
    # This prevents multiple copies of 'Diocese_Color_Code' from appearing
    # within the DataFrame.
df_dioceses = df_dioceses.merge(df_diocese_numbers, on = 'Diocese', 
how = 'left') 
df_dioceses.head(5)


colormap = branca.colormap.linear.Paired_12.to_step(
    12, data = df_dioceses['Diocese_Color_Code'])
colormap


color_list = list(np.arange(0, 176, 176/12))
[(int(color_list[i]), colormap(color_list[i])) for i in range(len(color_list))]

[(0, '#a6cee3ff'),
 (14, '#1f78b4ff'),
 (29, '#b2df8aff'),
 (44, '#33a02cff'),
 (58, '#fb9a99ff'),
 (73, '#e31a1cff'),
 (88, '#fdbf6fff'),
 (102, '#ff7f00ff'),
 (117, '#cab2d6ff'),
 (132, '#6a3d9aff'),
 (146, '#ffff99ff'),
 (161, '#b15928ff')]


# # This use of df.apply() with if/else statements is based on an example
# by Professor Hardeep Johar.

# Green:
# The following line changes the color code of certain dioceses to 0, which 
# corresponds to the light blue color within the colormap. 
# Light blue:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 0 if row['Diocese'] in [
    'Santa Rosa', 'Crookston', 'Kansas City-St. Joseph', 'St. Petersburg', 
    'Gaylord'] else row['Diocese_Color_Code'], axis = 1)


# Blue:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 14 if row['Diocese'] in [
    'Davenport', 'Tulsa', 'San Diego', 
    'Biloxi', 'St. Paul and Minneapolis'
    ] else row['Diocese_Color_Code'], axis = 1)

# Light green:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 29 if row['Diocese'] in [
    'Sacramento', 'Washington', 'Palm Beach', 'Birmingham', 'Paterson',
    'Rockville Centre'] else row['Diocese_Color_Code'], axis = 1)


df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 44 if row['Diocese'] in 
['Seattle', 'Dubuque', 'Charleston'] else row['Diocese_Color_Code'], axis = 1)


#Pink:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 58 if row['Diocese'] in [
    'Reno', 'San Antonio', 'Cleveland'] else row['Diocese_Color_Code'], axis = 1)

#Red:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 73 if row['Diocese'] in [
    'Cheyenne', 'Sioux Falls', 'Baltimore', 'San Francisco', 'Scranton']
    else row['Diocese_Color_Code'], axis = 1)

# Light orange:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 88 if row['Diocese'] in [
    'Youngstown', 'Denver'] else row['Diocese_Color_Code'], axis = 1)

# Orange:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 102 if row['Diocese'] in [
    'Alexandria', 'Covington', 'Helena', 'Raleigh'] 
    else row['Diocese_Color_Code'], axis = 1)


# Light purple:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 117 if row['Diocese'] in [
    'St. Cloud', 'Memphis'] else row['Diocese_Color_Code'], axis = 1)

# Purple:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 132 if row['Diocese'] in [
    'Lafayette in Louisiana', 'Lexington', 'Gary', 'New York', 
    'St. Louis'] else row['Diocese_Color_Code'], axis = 1)


# Yellow (changed to dark red within the mapping code to make white labels
# easier to read):
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 146 if row['Diocese'] in [
    'Lubbock'] else row['Diocese_Color_Code'], axis = 1)


# Brown:
df_dioceses['Diocese_Color_Code'] = df_dioceses.apply(
    lambda row: 161 if row['Diocese'] in [
    'Louisville', 'Bridgeport', 'Milwaukee', 
    'Colorado Springs'] else row['Diocese_Color_Code'], axis = 1)


df_dioceses.to_csv('counties_by_diocese.csv', index = False)


# Locating and storing geographic coordinates atop which diocese names can be plotted:
diocese_boundaries['center'] = diocese_boundaries[
    'geometry'].representative_point()
# The benefit of using representative_point() is that it ensures that the 
# resulting point falls within the boundary of the diocese (which is not always 
# the same as the centroid of the diocese, depending on the diocese's shape).
# See https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoSeries.representative_point.html


diocese_boundaries['name_for_plotting'] = diocese_boundaries['Diocese']


# Creating abbreviated versions of certain diocese names:
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Portland in Oregon', 'Portland OR')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('San Francisco', 'SF')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('San Jose', 'SJ')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Oakland', 'Oakl.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Orange', 'Or.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Galveston-Houston', 'Galv.-Hou.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Victoria in Texas', 'Victoria')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('St. Paul and Minneapolis', 'St. Paul-Minn.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Chicago', 'Chi.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Lafayette in Indiana', 'Lafayette IN')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Lafayette in Louisiana', 'Lafyt. LA')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Shreveport', 'Shrvpt.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('St. Petersburg', 'St. Ptrsbg.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Springfield in Illinois', 'Springfield IL')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Washington', 'Was.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Baltimore', 'Balt.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Pittsburgh', 'Pitt.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Greensburg', 'Grnsbg.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Altoona-Johnstown', 'Alt-Jnstn.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Harrisburg', 'Hrsbg.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Allentown', 'Allntn.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Springfield in Massachusetts', 'Springfield MA.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Worcester', 'Wrcstr.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Bridgeport', 'Brgpt.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Providence', 'Prv.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Norwich', 'Nwch.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Brooklyn', 'Brkln.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Rockville Centre', 'Rockvl_Ctr.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Metuchen', 'Mtchn.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Newark', 'Nwrk.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Steubenville', 'Steub.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Philadelphia', 'Phil.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Paterson', 'Ptrsn.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Hartford', 'Htfd.')
diocese_boundaries['name_for_plotting'] = diocese_boundaries[
    'name_for_plotting'].str.replace('Manchester', 'Mnchstr.')

diocese_boundaries.head()


def create_map_screenshot(absolute_path_to_map_folder, 
map_name, added_text = '', screenshot_save_path = None, 
webdriver_source = 'Firefox'):

    '''
    This function uses the Selenium library to create a screenshot 
    of a map so that it can be shared as a .png file.
    See https://www.selenium.dev/documentation/ for more information on 
    Selenium. 
    
    Note that some setup work may be required for the Selenium code
    to run correctly. If you don't have time right now to complete this 
    setup or don't need to automatically generate interactive versions
    of the maps, you can comment out any code that calls this function.
  
    absolute_path_to_map_folder designates the absolute path where
    the map is stored. (I should be able to update this code in the future
    so that it accommodates relative paths.)

    map_name specifies the name of the map, including its extension.

    screenshot_save_path designates the folder where you wish to save
    the map screenshot. This can be a relative path.

    webdriver_source refers to the driver that you wish to use. It can 
    be either 'Firefox' or 'Chrome'; however, the code is based on the
    behavior of the Firefox webdriver, so I recommend sticking with
    that option if possible.
    '''

    if webdriver_source == 'Firefox':
        selenium_driver = webdriver.Firefox()
    
    elif webdriver_source == 'Chrome':
        options = Options() 
        # The following line came from user 'undetected Selenium' at:
        # https://stackoverflow.com/a/55016352/13097194
        options.add_argument("--headless") # This ended up being necessary
        # in order to set the width and height (as verified by get_window_size() equal to window_width and window_height. 
        # Without headless mode, the window ended up being significantly smaller.)

        selenium_driver = webdriver.Chrome(options=options)

    else:
        raise ValueError(
"Unrecognized value passed to webdriver_source.")

    # See https://www.selenium.dev/documentation/webdriver/getting_started/open_browser/
    # For more information on using Selenium to get screenshots of .html 
    # files, see my get_screenshots.ipynb file within my route_maps_builder
    # program, available here:
    # https://github.com/kburchfiel/route_maps_builder/blob/master/get_screenshots.ipynb
    window_width = 3000 # This produces a large window that can better
    # capture small details (such as zip code shapefiles).
    selenium_driver.set_window_size(window_width,window_width*(9/16)) # Creates
    # a window with an HD/4K/8K aspect ratio
    selenium_driver.get(f'{absolute_path_to_map_folder}\\{map_name}') 
    # See https://www.selenium.dev/documentation/webdriver/browser/navigation/
    time.sleep(2) # This gives the page sufficient
    # time to load the map tiles before the screenshot is taken. 
    # You can also experiment with longer sleep times.

    if screenshot_save_path != None:
        # If specifying a screenshot save path, you must create this path
        # within your directory before the function is run; otherwise,
        # it won't return an image. 
        selenium_driver.get_screenshot_as_file(
            screenshot_save_path+'/'+map_name.replace(
                '.html','')+added_text+'.png') 
    else: # If no save path was specified for the screenshot, the image
        # will be saved within the project's root folder.
        selenium_driver.get_screenshot_as_file(
            map_name.replace('.html','')+added_text+'.png') 
    # Based on:
    # https://www.selenium.dev/selenium/docs/api/java/org/openqa/selenium/TakesScreenshot.html

    selenium_driver.quit()
    # Based on: https://www.selenium.dev/documentation/webdriver/browser/windows/

def convert_png_to_smaller_jpg(png_folder, png_image_name, jpg_folder, 
reduction_factor = 1, quality_factor = 50):
    ''' This function converts a .png image into a smaller .jpg image, which
    helps reduce file sizes and load times when displaying a series of images
    within a notebook or online.
    png_folder and png_image_name specify the location of the original .png
    image.
    jpg folder specifies the location where the .jpg screenshot should be
    saved.
    reduction_factor specifies the amount by which you would like to reduce
    the image's dimensions. For instance, to convert a 4K (3840*2160) image
    to a full HD (1920*1080) one, use a reduction factor of 2. If you do not
    wish to reduce the image's size, use the default reduction factor of 1.
    '''
    with PIL.Image.open(f'{png_folder}/{png_image_name}') as map_image:
        (width, height) = (map_image.width // reduction_factor, 
        map_image.height // reduction_factor)
        jpg_image = map_image.resize((width, height))
        # The above code is based on:
        # https://pillow.readthedocs.io/en/stable/reference/Image.html
        jpg_image = jpg_image.convert('RGB')
        # The above conversion is necessary in order to save .png files as 
        # .jpg files. It's based on Patrick Artner's answer at: 
        # https://stackoverflow.com/a/48248432/13097194
        jpg_image_name = png_image_name.replace('png', 'jpg') 
        jpg_image.save(f'{jpg_folder}/{jpg_image_name}',
        format = 'JPEG', quality = quality_factor, optimize = True)
        # See https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html#jpeg


diocese_map = folium.Map(location=[38.7, -95], zoom_start=6, 
tiles = 'OpenStreetMap')

# Although Folium has a choropleth library, I wasn't able to find a way
# to disable the default legend. Therefore, I am instead using a custom
# choropleth mapping function. Much of this function is based on 
# Amodiovalerio Verde's code at:
# https://vverde.github.io/blob/interactivechoropleth.html . 

colormap = branca.colormap.linear.Paired_12.to_step(
    12, data = df_dioceses['Diocese_Color_Code'])
colormap

tooltip = folium.features.GeoJsonTooltip(fields = 
['county_state', 'Diocese', 'Province'], aliases = 
['County', 'Diocese', 'Province'])
# Based on https://python-visualization.github.io/folium/modules.html#folium.features.GeoJsonTooltip


style_function = lambda x: {
        "weight": 0.5,
        'color': '#777777',
        "fillColor": '#770000' if
        colormap(x['properties']['Diocese_Color_Code']) == '#ffff99ff'
        else colormap(x['properties']['Diocese_Color_Code']),
        # Note that 'properties' has to be added before the column name.
        # This can be inferred from the GeoJson definition within Folium:
        # https://python-visualization.github.io/folium/modules.html#folium.features.GeoJson
        # The if/else statement checks whether the color corresponding to the
        # colormap is yellow. (I found this value by printing out each color
        # within the colormap, as shown later in the code.)
        # If so, it changes the fill color to a dark red 
        # so that white text labels can be read atop it.
        'fillOpacity': 0.8}

folium.features.GeoJson(df_dioceses, 
style_function=style_function).add_to(diocese_map)



diocese_style_function = lambda x: {
        "fillOpacity": 0,
        "weight": 2,
        'color': '#FFFFFF',
        'Fill': False}

folium.features.GeoJson(diocese_boundaries['geometry'], 
style_function=diocese_style_function).add_to(diocese_map)
# diocese_boundaries includes both geometry and point values. The point values
# confuse the interpreter, so in order to avoid an error message, I 
# entered 'geometry' here to specify that those were the points to be plotted.


province_style_function = lambda x: {
        'weight': '2', 
        'fillOpacity': 0,
        'color': 
        '#000000', 
        'Fill': False} 
# See https://python-visualization.github.io/folium/modules.html#folium.vector_layers.path_options
# for style_function arguments.

folium.GeoJson(province_boundaries, name = "geojson", 
style_function = province_style_function).add_to(diocese_map)

tooltip_style_function = lambda x: {
        "fillOpacity": 0,
        "weight": 0,
        'color': '#000000',
        'Fill': False}

folium.features.GeoJson(df_dioceses, tooltip = tooltip,
style_function=tooltip_style_function).add_to(diocese_map)

for i in range(len(diocese_boundaries)):
    center_point = [float(diocese_boundaries.iloc[
        i, diocese_boundaries.columns.get_loc('center')].y),
    float(diocese_boundaries.iloc[i, diocese_boundaries.columns.get_loc(
        'center')].x)] 
    # The use of .y and .x here is based on Francois M.'s response at:
    # https://gis.stackexchange.com/a/255867/195615
    diocese_name = diocese_boundaries.iloc[
        i, diocese_boundaries.columns.get_loc('Diocese')]
    diocese_name_for_plotting = diocese_boundaries.iloc[
        i, diocese_boundaries.columns.get_loc('name_for_plotting')]
    split_name = diocese_name_for_plotting.replace('-', ' ').split(' ')
    horizontal_offset = max([len(word) for word in split_name])*3
    vertical_offset = len(split_name)*10
#     print(split_name, horizontal_offset) # For debugging
    style_tag = '<style> p{color:white; line-height: 1} </style>'
#     style_tag = '<style> p{text-align:center} </style>'
#     align_string = 'style = "text-align:center"'
#     align_string = 'style = "color:green"'
#     folium.CircleMarker(center_point, radius = 1).add_to(diocese_map) 
# The above line is very useful for debugging what offsets to use when placing
# text on the map.
    if diocese_name == diocese_boundaries.iloc[
        i, diocese_boundaries.columns.get_loc('Province')]: 
        # E.g. if this is an archdiocese (as provinces are 
        # named after archdioceses)
        folium.Marker(center_point, icon = folium.DivIcon(
            icon_anchor=(horizontal_offset, vertical_offset), 
            html=f"{style_tag}<p><b><i>{diocese_name_for_plotting}</i><b></p>")
            ).add_to(diocese_map)
    else:
        folium.Marker(center_point, icon = folium.DivIcon(
            icon_anchor=(horizontal_offset, vertical_offset), 
            html=f"{style_tag}<p><b>{diocese_name_for_plotting}</b></p>")
            ).add_to(diocese_map)

# The strategy of using an invisible folium.Marker object to display text on 
# the map via DivIcon elements comes from from Bob Haffner's response at:
# https://stackoverflow.com/a/56878525/13097194 or:
# and https://stackoverflow.com/a/46408144/13097194


# folium.LatLngPopup().add_to(diocese_map) # Useful for debugging

diocese_map.save('diocese_map.html')

# colormap.add_to(m)


create_map_screenshot(
    absolute_path_to_map_folder = cwd, 
    map_name = 'diocese_map.html', screenshot_save_path = 'screenshots',
    webdriver_source='Firefox')

convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'diocese_map.png', jpg_folder = 'smaller_screenshots', 
quality_factor = 80)

IPython.display.Image(filename='smaller_screenshots/'+'diocese_map.jpg') 
# Based on https://ipython.readthedocs.io/en/stable/api/generated/IPython.display.html


revised_diocese_boundaries = geopandas.read_file(
    'diocese_boundaries_revised.geojson')
revised_diocese_boundaries.sort_values('Diocese', inplace = True) 
revised_diocese_boundaries = revised_diocese_boundaries.merge(
    df_dioceses[['Diocese', 'Diocese_Color_Code']].drop_duplicates(), 
    on = 'Diocese')
revised_diocese_boundaries = revised_diocese_boundaries.merge(
    diocese_boundaries[['Diocese', 'name_for_plotting']], on = 'Diocese')
revised_diocese_boundaries
revised_diocese_boundaries['center'] = revised_diocese_boundaries[
    'geometry'].representative_point()
revised_diocese_boundaries.head(2)


revised_province_boundaries = geopandas.read_file('province_boundaries_revised.geojson')


revised_province_boundaries


# cathedral_list = pd.read_html(
#     'https://en.wikipedia.org/wiki/List_of_Catholic_cathedrals_in_the_United_States')[
#         0][['Diocese', 'Cathedral']]
# cathedral_list['Diocese'] = cathedral_list['Diocese'].str.replace(
#     'Diocese of', '').str.replace('Archdiocese of', '').str.strip()
# # Adding str.strip() ended up being necessary for the merge to work
# cathedral_list['Cathedral_List'] = [
#     [cathedral_list['Cathedral'][i]] for i in range(len(cathedral_list))]
# cathedral_list.drop('Cathedral', axis = 1, inplace = True)
# cathedral_list['Cathedral_coord_list'] = [
#     [] for i in range(len(cathedral_list))]
# df_provinces_cathedrals = df_provinces.merge(
#     cathedral_list, on = 'Diocese', how = 'left')
# df_provinces_cathedrals.to_csv('diocese_province_cathedral_list.csv', 
# index = False)
# df_provinces_cathedrals


df_cathedral_locations = pd.read_csv(
    'diocese_province_cathedral_list_revised.csv')

df_cathedral_locations


generate_water_features = False
water_simplification_level = simplification_level # Setting these
# two equal to each other for now, but consider decreasing
# water_simplification_level in order to produce smaller map file sizes.


if generate_water_features == True:
    us_water_bodies = geopandas.read_file(r'C:\Users\kburc\Downloads\tlgdb_2021_a_us_areawater.gdb\tlgdb_2021_a_us_areawater.gdb')
    # File source: 
    # https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-geodatabase-file.2021.html
    # (Click on "Areal Hydrography National Geodatabase" to download the 
    # .zip file). Even though 'tlgdb_2021_a_us_areawater.gdb' is actually 
    # a folder, GeoPandas is still able to read it into a GeoDataFrame.
    print(pd.value_counts(us_water_bodies['MTFCC']))
    # Shows the different MTFCC codes present in the dataset, 
    # along with the number of features present for each code:
    mtfcc_code_list = ['H2030', 'H2040', 'H2051', 'H2053']
    # These are the codes for lakes/ponds, reservoirs, 
    # bays/estuaries/gulfs/sounds, and oceans/seas. 
    major_us_water_bodies = us_water_bodies.query(
        "MTFCC in @mtfcc_code_list").query("AWATER > 10000000").copy()
    major_us_water_bodies
    major_us_water_bodies['geometry'] = major_us_water_bodies[
        'geometry'].simplify(tolerance = water_simplification_level)
    # For some reason, major_us_water_bodies doesn't include the part
    # of Lake Erie north of Youngstown. Therefore, I added this part
    # in manually by selecting it using the .cx method within 
    # GeoPandas, then adding it to major_us_water_bodies.
    boundary = [41.7050, -81.1780, 42.7231, -80.4419]
    water_north_of_youngstown = us_water_bodies.cx[-81.1780:-80.4419, 
    41.7050:42.7231].copy()
    # See https://geopandas.org/en/stable/docs/user_guide/indexing.html
    # water_north_of_youngstown = water_north_of_youngstown.query(
    #     "MTFCC in @mtfcc_code_list")
    water_north_of_youngstown['geometry'] = water_north_of_youngstown[
        'geometry'].simplify(tolerance = water_simplification_level)
    major_us_water_bodies = pd.concat([major_us_water_bodies, 
    water_north_of_youngstown]).drop_duplicates().copy()

    print(pd.value_counts(major_us_water_bodies['MTFCC']))
    major_us_water_bodies.to_file('major_us_water_bodies.geojson')
    # Note: This file is 6.79 MB in size (at least on my computer)
    # when water_simplification_level is set to 0.005. When I
    # increased the tolerance to 0.1, the file size decreased to
    # around 4.3 MB, but the water boundaries
    # became noticeably jagged.

else:
    major_us_water_bodies = geopandas.read_file('major_us_water_bodies.geojson')

C:\Users\kburc\AppData\Local\Temp\ipykernel_12196\3073223851.py:8: FutureWarning: pandas.value_counts is deprecated and will be removed in a future version. Use pd.Series(obj).value_counts() instead.
  print(pd.value_counts(us_water_bodies['MTFCC']))

MTFCC
H2030    2182304
H3010      53349
H2040       9403
H2051       8642
H3020       2561
H2081       1610
H2053        627
H2041        241
H3013         53
Name: count, dtype: int64

C:\Users\kburc\AppData\Local\Temp\ipykernel_12196\3073223851.py:34: FutureWarning: pandas.value_counts is deprecated and will be removed in a future version. Use pd.Series(obj).value_counts() instead.
  print(pd.value_counts(major_us_water_bodies['MTFCC']))

MTFCC
H2030    1702
H2051    1548
H2053     320
H2040     228
H3010      15
Name: count, dtype: int64


def create_diocese_map(tile_option = 'OpenStreetMap', starting_zoom = 6, 
starting_location = [38.7, -95], save_path = 'revised_diocese_map', 
include_cathedrals = True, include_names = True, include_counties = True,
include_water_bodies = True):
    ''' include_cathedrals, include_names, and include_counties determine
    whether the final map will show cathedrals, diocese names, and
    county outlines and names, respectively. I uploaded
    screenshots of a name-free and cathedral-free map to Wikimedia Commons
    for use in Wikipedia pages. Excluding counties allows the final map size
    to be significantly smaller, thus allowing it to get uploaded
    to Google Sites (which currently has a 15MB limit in place for pages
    built on embedded HTML).
    '''    
    revised_diocese_map = folium.Map(location=starting_location, 
    zoom_start=starting_zoom, tiles = tile_option)
    # tiles can be set to 'None' in order to produce a map without any 
    # background details. This produces a cleaner static image.

    # Although Folium has a choropleth library, I wasn't able to find a way
    # to disable the default legend. Therefore, I am instead using a custom
    # choropleth mapping function. Much of this function is based on 
    # Amodiovalerio Verde's code at:
    # https://vverde.github.io/blob/interactivechoropleth.html . 

    colormap = branca.colormap.linear.Paired_12.to_step(
        12, data = revised_diocese_boundaries['Diocese_Color_Code'])
    colormap
    # As noted earlier, this colormap will be used to assign different
    # map colors to different dioceses.

    # Adding in county borders:

    if include_counties == True:
        print("Adding in counties:")

        county_style_function = lambda x: {
                "weight": 0.5,
                'color': '#000000',
                'fillOpacity': 0}
        # See https://python-visualization.github.io/folium/modules.html#folium.vector_layers.path_options
        # for a list of items that can be included within a style function.
        # The above parameters will plot county shapes as thin black lines without
        # any fill color.

        folium.features.GeoJson(df_dioceses, name = 'Counties',
        style_function=county_style_function).add_to(revised_diocese_map)
        # See https://python-visualization.github.io/folium/modules.html#folium.features.GeoJson
        # for more information on adding GeoJson elements to Folium maps.

    # Adding in bodies of water:
    if include_water_bodies == True:
        print("Adding in bodies of water:")

        water_style_function = lambda x: {
                    "weight": 0.5,
                    'color': '#0000FF',
                    'fillOpacity': 1}
                # This style function will plot the bodies of water in
                # major_us_water_bodies as opaque blue polygons.

        folium.features.GeoJson(major_us_water_bodies, name = 'Bodies of Water',
            style_function=water_style_function).add_to(revised_diocese_map)

    # Adding in diocese colors and borders:
    print("Adding in dioceses:")

    diocese_style_function = lambda x: {
            "fillOpacity": 0.8,
            "weight": 2,
            'color': '#FFFFFF',
            "fillColor": '#770000' if
            colormap(x['properties']['Diocese_Color_Code']) == '#ffff99ff'
            else colormap(x['properties']['Diocese_Color_Code'])}
            # Note that 'properties' has to be added before the column name.
            # This can be inferred from the GeoJson definition within Folium:
            # https://python-visualization.github.io/folium/modules.html#folium.features.GeoJson}
    # This style function adds diocese colors and 
    # thick white diocesan boundaries to the map.
    # Note that colormap is used to determine the color of each diocese. 
    # (#ffff99ff, the yellow color within the colormap, makes it harder to read
    # white diocese names, so the style function changes this color to a dark
    # red whenever it appears.

    folium.features.GeoJson(revised_diocese_boundaries[
        ['geometry', 'Diocese_Color_Code']], 
    name = 'Dioceses', style_function=diocese_style_function).add_to(
        revised_diocese_map)
    # revised_diocese_boundaries includes both geometry and point values. 
    # The point values confuse the interpreter, so in order to avoid
    # an error message, I entered 'geometry' here so that only 
    # those coordinate values would be used.

    # Adding in province borders:
    print("Adding in provinces:")
    province_style_function = lambda x: {
            'weight': '2', 
            'fillOpacity': 0,
            'color': 
            '#000000', 
            'Fill': False} 

    folium.GeoJson(revised_province_boundaries, name = "Provinces", 
    style_function = province_style_function).add_to(revised_diocese_map)


    # Adding in tooltips:
    # The following lines of code add in 'tooltips,' which are text values
    # that appear when the user hovers over a given county. These tooltips
    # will reveal county, diocese, and province information. They are added
    # after the counties, dioceses, and provinces so that those features won't
    # # block the tooltips from view. 
    print("Adding in tooltips:")
    if include_counties == True:
        tooltip = folium.features.GeoJsonTooltip(fields = 
        ['county_state', 'Diocese_Detail', 'Province_Detail'], aliases = 
        ['County', 'Diocese', 'Province'])
        # Based on https://python-visualization.github.io/folium/modules.html#folium.features.GeoJsonTooltip
    else: # This verison of the tooltip won't include county names.
        tooltip = folium.features.GeoJsonTooltip(fields = 
        ['Diocese_Detail', 'Province_Detail'], aliases = 
        ['Diocese', 'Province'])

    tooltip_style_function = lambda x: {
            "fillOpacity": 0,
            "weight": 0,
            'color': '#000000',
            'Fill': False}
            # This style function makes the other components of the tooltips
            # invisible so as not to alter the appearance of the map.

    folium.features.GeoJson(df_dioceses, tooltip = tooltip, name = 'Tooltips',
    style_function=tooltip_style_function).add_to(revised_diocese_map)


    # Adding in cathedrals:
    # This section of the code adds in cathedral markers. Diocesan and 
    # archdiocesan cathedrals are given separate markers.
    if include_cathedrals == True:
        print("Adding in cathedrals:")
        # First, I'll add in variables that govern the size of the icons that
        # I'll plot:
        icon_width = 10
        icon_height = icon_width/(120/200)
        # The original markers are 120 by 200 pixels, so dividing the icon's 
        # width by this same ratio preserves the original shape of the icons
        # during the plotting process.
        cathedral_counter = 0
        cathedral_feature_group = folium.FeatureGroup(name = 'Cathedrals')
        # cathedral_feature_group will store all of the cathedral markers
        # on the map. The benefit of this setup is that cathedrals can then 
        # be toggled on and off using Folium's LayerControl feature.
        # This method comes from Bob Haffner at
        # https://stackoverflow.com/a/61283334/13097194 .
        # See also: https://python-visualization.github.io/folium/modules.html#folium.map.FeatureGroup

        for i in range(len(df_cathedral_locations)):
            # print(i)
            # First, I'll retrieve the locations of each cathedral from
            # df_cathedral_locations. Since I saved the locations in 
            # JSON format, I can use json.loads to convert those locations
            # into a list of lists that Python can interpret.
            # If you need to double-check how to convert an item
            # (such as a list of lists) into JSON format, you can pass that
            # item to json.dumps(). 
            loc_list = json.loads(df_cathedral_locations.iloc[
                i, df_cathedral_locations.columns.get_loc(
                    'Cathedral_coord_list')])
            # Each row of the DataFrame has a list of cathedral locations, 
            # as a given diocese can have more than one cathedral. Dioceses
            # with only one cathedral have a list with only one entry.
            # I'll also use json.loads() to extract a list of cathedral 
            # names from each row.
            cathedral_list = json.loads(df_cathedral_locations.iloc[
                i, df_cathedral_locations.columns.get_loc('Cathedral_List')])

            diocese_name = df_cathedral_locations.iloc[
                i, df_cathedral_locations.columns.get_loc('Diocese')]
            if diocese_name == df_cathedral_locations.iloc[
                i, df_cathedral_locations.columns.get_loc('Province')]:
                # print("True")
                marker = 'globus_cruciger_archbishop.png'
            # For archdioceses, I use a double-barred globus cruciger (see
            # https://en.wikipedia.org/wiki/Globus_cruciger ). For 
            # dioceses, I use a single-barred globus cruciger. I created these
            # images within Inkscape and release them into the public domain.
            else:
                marker = 'globus_cruciger.png'
            for j in range(len(loc_list)):
                folium.Marker(loc_list[j], icon = folium.CustomIcon(
                    marker, icon_size = (icon_width, icon_height)), 
                    tooltip = cathedral_list[j]).add_to(cathedral_feature_group)
                # See https://python-visualization.github.io/folium/modules.html#folium.features.CustomIcon
                # and https://python-visualization.github.io/folium/modules.html
                cathedral_counter += 1
        print("Added",cathedral_counter,"cathedrals to the map.")
        # Each cathedral then gets added to the feature group so that
        # all cathedrals can be toggled on or off at once.
        cathedral_feature_group.add_to(revised_diocese_map)


    # Adding in diocese names:
    if include_names == True:
        print("Adding in diocese names:")
        name_feature_group = folium.FeatureGroup(name = 'Diocese Names')
        # I'll first retrieve the coordinate at which to plot the name:
        for i in range(len(revised_diocese_boundaries)):
            center_point = [float(revised_diocese_boundaries.iloc[
                i, revised_diocese_boundaries.columns.get_loc('center')].y),
            float(revised_diocese_boundaries.iloc[
                i, revised_diocese_boundaries.columns.get_loc('center')].x)] 
            # The use of .y and .x here is based on Francois M.'s response at:
            # https://gis.stackexchange.com/a/255867/195615
            diocese_name = revised_diocese_boundaries.iloc[
                i, revised_diocese_boundaries.columns.get_loc('Diocese')]
            diocese_name_for_plotting = revised_diocese_boundaries.iloc[
                i, revised_diocese_boundaries.columns.get_loc(
                    'name_for_plotting')]
            # Folium will plot each word (whether separated by a space or a 
            # hyphen) on a separate line. Therefore, in order to place each
            # diocese name close to its corresponding center_point location,
            # I created horizontal_offset and vertical_offset values that 
            # could be passed to the icon_anchor parameter or 
            # folium.DivIcon (see below).
            split_name = diocese_name_for_plotting.replace('-', ' ').split(' ')
            # split_name determines on how many lines a given diocese name
            # will appear. By replacing all hyphens with spaces, I can split
            # on all parts of the string that originally contained a hyphen
            # or a space. This clever trick comes from Louis LC at
            # https://stackoverflow.com/a/7215696/13097194 .

            # I want to shift the text back so that it remains centered.
            # To do so, I'll find the longest word within split_name and then
            # set the horizontal offset based on 3 * that word's length. (I 
            # determined this number via trial and error.)
            horizontal_offset = max([len(word) for word in split_name])*3

            # Similarly, in order to keep the text vertically centered, 
            # I'll create a vertical offset value based on the total number
            # of lines within split_name.
            vertical_offset = len(split_name)*10

            # This style tag will allow me to control some basic style
            # properties of each diocese's name.
            style_tag = '<style> p{color:white; line-height: 1} </style>'
            # Based on https://developer.mozilla.org/en-US/docs/Web/HTML/Element/style
        
            if diocese_name == revised_diocese_boundaries.iloc[
                i, revised_diocese_boundaries.columns.get_loc(
                    'Province')]: # E.g. if this is an archdiocese 
            # (as provinces are named after archdioceses)
            # The following line plots archdioceses' names in bold and 
            # italic font using HTML tags.
            # The strategy of using an invisible folium.Marker object to display text on 
            # the map via DivIcon elements comes from from Bob Haffner's response at:
            # https://stackoverflow.com/a/56878525/13097194 or:
            # and https://stackoverflow.com/a/46408144/13097194
            # See https://python-visualization.github.io/folium/modules.html#folium.features.DivIcon
            # for more information on the use of DivIcon.
                folium.Marker(center_point, icon = folium.DivIcon(
                icon_anchor=(horizontal_offset, vertical_offset), 
            html=f"{style_tag}<p><b><i>{diocese_name_for_plotting}</i><b></p>")
            ).add_to(name_feature_group)
            else:
                # Dioceses' names are still in bold but are not italicized.
                folium.Marker(center_point, icon = folium.DivIcon(
                icon_anchor=(horizontal_offset, vertical_offset), 
                html=f"{style_tag}<p><b>{diocese_name_for_plotting}</b></p>")
                ).add_to(name_feature_group)
    
            # folium.CircleMarker(center_point, radius = 1).add_to(revised_diocese_map) 
            # The above line is very useful for debugging what offsets to use
            # when placing text on the map.
        # Finally, each diocese name gets added to name_feature_group.
        name_feature_group.add_to(revised_diocese_map)

    folium.LatLngPopup().add_to(revised_diocese_map) 
    # Useful for editing diocese boundaries

    folium.LayerControl().add_to(revised_diocese_map) # This allows the user
    # to select which layers of the map (provinces, cathedrals, diocese names,
    # etc. to display.)
    print("Saving map:")
    revised_diocese_map.save(save_path+'.html')

    # colormap.add_to(m) # This functions as the map's legend, but since the
    # colors have no real meaning, it will be excluded from this map.

    return revised_diocese_map


create_diocese_map()
print('Finished creating map.')


create_map_screenshot(
    absolute_path_to_map_folder = 
    cwd, 
    map_name = 'revised_diocese_map.html', screenshot_save_path = 'screenshots')
convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'revised_diocese_map.png', jpg_folder = 'smaller_screenshots', 
quality_factor = 80)


create_diocese_map(tile_option = None, save_path = 'revised_diocese_map_tileless')

create_map_screenshot(
    absolute_path_to_map_folder = 
    cwd, 
    map_name = 'revised_diocese_map_tileless.html', 
    screenshot_save_path = 'screenshots')
convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'revised_diocese_map_tileless.png', 
jpg_folder = 'smaller_screenshots', 
quality_factor = 80)

Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Adding in diocese names:
Saving map:


def add_alaska_and_hawaii(starting_map_name, tile_option = 'OpenStreetMap', 
include_cathedrals = True, include_names = True):
    '''This function creates a static version of the map stored at
    starting_map_name.html that includes Alaska and Hawaii at the bottom left.
    The value of starting_map_name should not include the .html at the end. 
    E.g. pass revised_diocese_map as an argument rather than 
    revised_diocese_map.html.
    This function assumes that starting_map_name.html was produced using 
    generate_diocese_map() with a starting zoom of 6 and a starting location
    of [38.7, -95] (the default parameters for generate_diocese_map().) It also
    assumes that a .png screenshot of that map was already created using
    create_map_screenshot().

    This function performs the following tasks:
    1. Creates .HTML maps of Alaska and Hawaii. (These are the same as the maps 
    created above except that they are centered near Alaska and Hawaii).
    2. Saves these maps as screenshots, then creates cropped versions
    of the screenshots that focus  on each state.
    3. Loads the screenshot of a map specified by 'starting_map_name'; 
    pastes the cropped Alaska and Hawaii images in at the bottom left corner;
    and saves this new screenshot.  

    Note that the names of the additional maps and screenshots 
    created within this function are based off starting_map_name.
    ''' 

    # Part 1: Creating Alaska map, screenshot, and cropped screenshot
    create_diocese_map(tile_option = tile_option, starting_zoom = 4, 
    starting_location = [65, -150], save_path = starting_map_name+'_alaska', 
    include_cathedrals = include_cathedrals, include_names = include_names)
    # This method of creating an Alaska-centric map is admittedly very
    # inefficient, as it also generates all other parts of the map.
    # Another option would be to use Selenium to navigate to Alaska and then
    # take the screenshot from there, but I had trouble finding a way to
    # get that to work. Therefore, I'll create extra .HTML maps instead.
    # You may choose to delete these extra .HTML maps, since they are only
    # used for screenshot generation.
    create_map_screenshot(absolute_path_to_map_folder = 
        cwd, 
        map_name = starting_map_name+'_alaska.html', 
        screenshot_save_path = 'screenshots')
    os.remove(starting_map_name+'_alaska.html') # This .HTML 
    # file is no longer needed, so it can be removed to save
    # file space.
    # https://docs.python.org/3/library/os.html
    with PIL.Image.open(
        'screenshots/'+starting_map_name+'_alaska.png') as map_image:
        # See https://pillow.readthedocs.io/en/stable/reference/Image.html
        print("Opened")
        cropped_image = map_image.crop((2200, 1100, 3500, 2300)) # Crops the
        # map based on the specified left, upper, right, and lower points. See
        # https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.crop
        # As with other parts of this program, these points were determined
        # using trial and error.
        # display(cropped_image) # https://stackoverflow.com/a/26649884/13097194
        # Useful for debugging
        cropped_image.save(
            'screenshots/'+starting_map_name+'_alaska_cropped.png')

    # Part 2: Creating Hawaii map, screenshot, and cropped screenshot
    create_diocese_map(tile_option = tile_option, starting_zoom = 6, 
    starting_location = [21, -156], save_path = starting_map_name+'_hawaii', 
    include_cathedrals = include_cathedrals, include_names = include_names)
    create_map_screenshot(absolute_path_to_map_folder = 
        cwd, 
        map_name = starting_map_name+'_hawaii.html', 
        screenshot_save_path = 'screenshots')
    os.remove(starting_map_name+'_hawaii.html')
    with PIL.Image.open(
        'screenshots/'+starting_map_name+'_hawaii.png') as map_image:
        print("Opened")
        cropped_image = map_image.crop((2500, 1400, 3300, 1900)) 
        cropped_image.save(
            'screenshots/'+starting_map_name+'_hawaii_cropped.png')
    
    # Part 3: Pasting these screenshots into the original map 
    with PIL.Image.open('screenshots/'+starting_map_name+'.png') as map_image:
        alaska = PIL.Image.open(
            'screenshots/'+starting_map_name+'_alaska_cropped.png')
        alaska = alaska.resize(
            (int(alaska.width/1.25), int(alaska.height/1.25)))
        hawaii = PIL.Image.open(
            'screenshots/'+starting_map_name+'_hawaii_cropped.png')
        # The following lines paste the cropped Alaska and Hawaii maps
        # onto starting_map_name.png.
        map_image.paste(im = alaska, box = (0, 2300))
        map_image.paste(im = hawaii, box = (1200, 2600))
        map_image.save('screenshots/'+starting_map_name+'_50_states.png')


convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'revised_diocese_map_tileless.png', 
jpg_folder = 'smaller_screenshots', 
quality_factor = 80)

IPython.display.Image(filename='smaller_screenshots/'+'revised_diocese_map_tileless.jpg') 
# Based on https://ipython.readthedocs.io/en/stable/api/generated/IPython.display.html

add_alaska_and_hawaii(tile_option = None, 
starting_map_name = 'revised_diocese_map_tileless')

convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'revised_diocese_map_tileless_50_states.png', 
jpg_folder = 'smaller_screenshots', 
quality_factor = 80)

IPython.display.Image(
    filename='smaller_screenshots/'+'revised_diocese_map_tileless_50_states.jpg') 
# Based on https://ipython.readthedocs.io/en/stable/api/generated/IPython.display.html

Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Adding in diocese names:
Saving map:
Opened
Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Adding in diocese names:
Saving map:
Opened


add_alaska_and_hawaii('revised_diocese_map')

Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Adding in diocese names:
Saving map:
Opened
Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Adding in diocese names:
Saving map:
Opened


# The above line produces a screenshot of the final map,
# so create_map_screenshot doesn't need to be called there.
convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'revised_diocese_map_50_states.png', 
jpg_folder = 'smaller_screenshots', 
quality_factor = 80)

IPython.display.Image(
    filename='smaller_screenshots/'+'revised_diocese_map_50_states.jpg') 
# Based on https://ipython.readthedocs.io/en/stable/api/generated/IPython.display.html


create_diocese_map(tile_option = None, include_cathedrals = False, 
save_path = 'revised_diocese_map_no_cathedrals_tileless')
create_map_screenshot(absolute_path_to_map_folder = 
    cwd, 
    map_name = 'revised_diocese_map_no_cathedrals_tileless.html', 
    screenshot_save_path = 'screenshots')

Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in diocese names:
Saving map:


add_alaska_and_hawaii(tile_option = None, 
starting_map_name = 'revised_diocese_map_no_cathedrals_tileless', 
include_cathedrals = False)

convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'revised_diocese_map_no_cathedrals_tileless_50_states.png', 
jpg_folder = 'smaller_screenshots', 
quality_factor = 80)

# IPython.display.Image(
# filename='smaller_screenshots/'+'revised_diocese_map_no_cathedrals_tileless_50_states.jpg') 
# # Based on https://ipython.readthedocs.io/en/stable/api/generated/IPython.display.html

Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in diocese names:
Saving map:
Opened
Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in diocese names:
Saving map:
Opened


create_diocese_map(tile_option = None, include_names = False, 
save_path = 'revised_diocese_map_no_names_tileless')
create_map_screenshot(absolute_path_to_map_folder = 
    cwd, 
    map_name = 'revised_diocese_map_no_names_tileless.html', 
    screenshot_save_path = 'screenshots')

Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Saving map:


add_alaska_and_hawaii(tile_option = None, 
starting_map_name = 'revised_diocese_map_no_names_tileless', 
include_names = False)

Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Saving map:
Opened
Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Saving map:
Opened


convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'revised_diocese_map_no_names_tileless_50_states.png', 
jpg_folder = 'smaller_screenshots', 
quality_factor = 80)

# IPython.display.Image(
# filename='smaller_screenshots/'+'revised_diocese_map_no_names_tileless_50_states.jpg') 
# Based on https://ipython.readthedocs.io/en/stable/api/generated/IPython.display.html


create_diocese_map(include_water_bodies = False, 
    save_path = 'revised_diocese_map_no_water_bodies')

create_map_screenshot(absolute_path_to_map_folder = 
    cwd, 
    map_name = 'revised_diocese_map_no_water_bodies.html', 
    screenshot_save_path = 'screenshots')

add_alaska_and_hawaii(tile_option = None, 
starting_map_name = 'revised_diocese_map_no_water_bodies', 
include_cathedrals = True)

convert_png_to_smaller_jpg(png_folder = 'screenshots', 
png_image_name = 'revised_diocese_map_no_water_bodies_50_states.png', 
jpg_folder = 'smaller_screenshots', 
quality_factor = 80)

# IPython.display.Image(
# filename='smaller_screenshots/'+'revised_diocese_map_no_cathedrals_tileless_50_states.jpg') 
# # Based on https://ipython.readthedocs.io/en/stable/api/generated/IPython.display.html

Adding in counties:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Adding in diocese names:
Saving map:
Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Adding in diocese names:
Saving map:
Opened
Adding in counties:
Adding in bodies of water:
Adding in dioceses:
Adding in provinces:
Adding in tooltips:
Adding in cathedrals:
Added 194 cathedrals to the map.
Adding in diocese names:
Saving map:
Opened


end_time = time.time()
run_time = end_time - start_time
run_minutes = run_time // 60
run_seconds = run_time % 60
print("Completed run at",time.ctime(end_time),"(local time)")
print("Total run time:",'{:.2f}'.format(run_time),
"second(s) ("+str(run_minutes),"minute(s) and",'{:.2f}'.format(run_seconds),
"second(s))") 
# Only meaningful when the program is run nonstop from start to finish

Completed run at Mon Apr  8 23:51:16 2024 (local time)
Total run time: 978.22 second(s) (16.0 minute(s) and 18.22 second(s))

	Diocese_Color_Code	Diocese
0	0	Albany
1	1	Alexandria
2	2	Allentown
3	3	Altoona-Johnstown
4	4	Amarillo
...	...	...
171	171	Wilmington
172	172	Winona-Rochester
173	173	Worcester
174	174	Yakima
175	175	Youngstown

	Diocese	Province	Cathedral_List	Cathedral_coord_list	Notes
0	Anchorage-Juneau	Anchorage-Juneau	["Our Lady of Guadalupe Cathedral (Anchorage)"...	[[61.18492777777778, -149.94404444444444], [58...	Our Lady of Guadalupe Cathedral's coordinates ...
1	Fairbanks	Anchorage-Juneau	["Cathedral of the Sacred Heart"]	[[64.83631, -147.78065]]	NaN
2	Atlanta	Atlanta	["Cathedral of Christ the King"]	[[33.8279, -84.38699]]	NaN
3	Charleston	Atlanta	["Cathedral of Saint John the Baptist"]	[[32.77656, -79.93447]]	NaN
4	Charlotte	Atlanta	["Cathedral of Saint Patrick"]	[[35.20529, -80.84475]]	NaN
...	...	...	...	...	...
171	St. Cloud	St. Paul and Minneapolis	["Cathedral of Saint Mary"]	[[45.5588, -94.1614]]	Obtained via GeoHack
172	St. Paul and Minneapolis	St. Paul and Minneapolis	["Cathedral of Saint Paul (Saint Paul)", "Basi...	[[44.946944, -93.108889], [44.973056, -93.2863...	Obtained via GeoHack
173	Winona-Rochester	St. Paul and Minneapolis	["Cathedral of the Sacred Heart (Winona)", "Co...	[[44.0484, -91.6395], [44.023, -92.4685]]	Obtained via GeoHack
174	St. Thomas	Washington	["Saints Peter and Paul Cathedral"]	[[18.341011, -64.936792]]	Obtained via GeoHack
175	Washington	Washington	["Cathedral of Saint Matthew the Apostle"]	[[38.906111, -77.04]]	Obtained via GeoHack

US Diocese Mapper¶

Introduction and Overview¶

Preliminary steps¶

Matching US Counties to Dioceses¶

Assigning Dioceses' Counties to Those Dioceses¶

Inaccurate parts of the map at this point:¶

Generating diocese colors¶

Updating Color Codes:¶

Plotting Diocese Names¶

Creating a draft of the diocese map (with some incorrect boundaries)¶

Generating a map with revised diocesan/provincial boundaries¶

Creating a cathedral list¶

Adding in water features¶

Creating simpler maps:¶

Creating a map without water boundaries:¶

	STATEFP	COUNTYFP	COUNTYNS	GEOID	NAME	NAMELSAD	LSAD	State_Name	State_Code	FIPS	county_state	Diocese	Diocese_Detail	Province_Detail	Province	geometry
0	31	039	00835841	31039	Cuming	Cuming County	06	Nebraska	NE	31	Cuming County, Nebraska	Omaha	Omaha	Omaha	Omaha	POLYGON ((-96.55551 42.08996, -96.55517 41.742...
1	53	069	01513275	53069	Wahkiakum	Wahkiakum County	06	Washington	WA	53	Wahkiakum County, Washington	Seattle	Seattle	Seattle	Seattle	POLYGON ((-123.72656 46.38487, -123.21795 46.3...
2	35	011	00933054	35011	De Baca	De Baca County	06	New Mexico	NM	35	De Baca County, New Mexico	Santa Fe	Santa Fe	Santa Fe	Santa Fe	POLYGON ((-104.44494 34.69165, -104.33973 34.6...
3	31	109	00835876	31109	Lancaster	Lancaster County	06	Nebraska	NE	31	Lancaster County, Nebraska	Lincoln	Lincoln	Omaha	Omaha	POLYGON ((-96.91094 41.04612, -96.46387 41.045...
4	31	129	00835886	31129	Nuckolls	Nuckolls County	06	Nebraska	NE	31	Nuckolls County, Nebraska	Lincoln	Lincoln	Omaha	Omaha	POLYGON ((-98.27357 40.35036, -97.82082 40.350...

	STATEFP	COUNTYFP	COUNTYNS	GEOID	NAME	NAMELSAD	LSAD	State_Name	State_Code	FIPS	county_state	Diocese	Diocese_Detail	Province_Detail	geometry	Province
114	27	095	00659493	27095	Mille Lacs	Mille Lacs County	06	Minnesota	MN	27	Mille Lacs County, Minnesota	St. Cloud	St. Cloud	St. Paul and Minneapolis	POLYGON ((-93.81091 46.24313, -93.43065 46.246...	St. Paul and Minneapolis
480	46	081	01266996	46081	Lawrence	Lawrence County	06	South Dakota	SD	46	Lawrence County, South Dakota	Rapid City	Rapid City	St. Paul and Minneapolis	POLYGON ((-104.05594 44.57102, -103.56765 44.6...	St. Paul and Minneapolis
283	27	001	00663198	27001	Aitkin	Aitkin County	06	Minnesota	MN	27	Aitkin County, Minnesota	Duluth	Duluth	St. Paul and Minneapolis	POLYGON ((-93.77526 47.03042, -93.05676 47.026...	St. Paul and Minneapolis
79	78	030	02378250	78030	St. Thomas	St. Thomas Island	10	Virgin Islands	VI	78	St. Thomas Island, Virgin Islands	St. Thomas	St. Thomas	Washington	POLYGON ((-65.15388 18.28114, -65.09179 18.447...	Washington
613	11	001	01702382	11001	District of Columbia	District of Columbia	00	District of Columbia	DC	11	District of Columbia, District of Columbia	Washington	Washington	Washington	POLYGON ((-77.11975 38.93435, -77.04088 38.995...	Washington

	STATEFP	COUNTYFP	COUNTYNS	GEOID	NAME	NAMELSAD	LSAD	State_Name	State_Code	FIPS	county_state	Diocese	Diocese_Detail	Province_Detail	geometry	Province
0	36	039	00974118	36039	Greene	Greene County	06	New York	NY	36	Greene County, New York	Albany	Albany	New York	POLYGON ((-74.04239 42.17039, -74.07480 42.096...	New York
1	36	025	00974111	36025	Delaware	Delaware County	06	New York	NY	36	Delaware County, New York	Albany	Albany	New York	POLYGON ((-74.45171 42.16922, -75.25796 41.862...	New York
2	36	091	00974143	36091	Saratoga	Saratoga County	06	New York	NY	36	Saratoga County, New York	Albany	Albany	New York	POLYGON ((-73.57788 43.05689, -73.67676 42.783...	New York
3	36	001	00974099	36001	Albany	Albany County	06	New York	NY	36	Albany County, New York	Albany	Albany	New York	POLYGON ((-73.78372 42.46423, -74.26347 42.407...	New York
4	36	043	00974120	36043	Herkimer	Herkimer County	06	New York	NY	36	Herkimer County, New York	Albany	Albany, Ogdensburg	New York	POLYGON ((-74.71261 43.28614, -74.76330 42.863...	New York

	Province	STATEFP	COUNTYFP	COUNTYNS	GEOID	NAME	NAMELSAD	LSAD	Unnamed: 0	State_Name	State_Code	FIPS	county_state	Diocese	Diocese_Detail	Province_Detail	geometry
0	Anchorage-Juneau	2	130	01419973	02130	Ketchikan Gateway	Ketchikan Gateway Borough	04	1.0	Alaska	AK	2	Ketchikan Gateway Borough, Alaska	Anchorage-Juneau	Anchorage-Juneau	Anchorage-Juneau	MULTIPOLYGON (((-179.17375 51.34303, -179.1076...
1	Atlanta	13	189	00348794	13189	McDuffie	McDuffie County	06	9.0	Georgia	GA	13	McDuffie County, Georgia	Atlanta	Atlanta	Atlanta	POLYGON ((-84.08447 30.67583, -84.86469 30.711...
2	Baltimore	51	775	01789074	51775	Salem	Salem city	25	45.0	Virginia	VA	51	Salem city, Virginia	Richmond	Richmond	Baltimore	POLYGON ((-82.14889 36.59472, -83.24893 36.593...
3	Boston	25	015	00606934	25015	Hampshire	Hampshire County	06	20.0	Massachusetts	MA	25	Hampshire County, Massachusetts	Springfield in Massachusetts	Springfield in Massachusetts	Boston	POLYGON ((-72.61690 42.03124, -72.75589 42.036...
4	Chicago	17	067	00424235	17067	Hancock	Hancock County	06	12.0	Illinois	IL	17	Hancock County, Illinois	Peoria	Peoria	Chicago	POLYGON ((-90.20713 38.08821, -90.24257 38.112...
5	Cincinnati	39	063	01074044	39063	Hancock	Hancock County	06	34.0	Ohio	OH	39	Hancock County, Ohio	Toledo	Toledo	Cincinnati	POLYGON ((-83.26796 38.61773, -83.28759 38.598...
6	Denver	8	109	00198170	08109	Saguache	Saguache County	06	5.0	Colorado	CO	8	Saguache County, Colorado	Pueblo	Pueblo	Denver	POLYGON ((-106.49067 36.99350, -103.10230 37.0...
7	Detroit	26	109	01622997	26109	Menominee	Menominee County	06	21.0	Michigan	MI	26	Menominee County, Michigan	Marquette	Marquette	Detroit	POLYGON ((-85.79198 41.75907, -87.20777 41.760...
8	Dubuque	19	053	00465215	19053	Decatur	Decatur County	06	14.0	Iowa	IA	19	Decatur County, Iowa	Des Moines	Des Moines	Dubuque	POLYGON ((-94.47329 40.57081, -95.76565 40.585...
9	Galveston-Houston	48	057	01383814	48057	Calhoun	Calhoun County	06	42.0	Texas	TX	48	Calhoun County, Texas	Victoria in Texas	Victoria in Texas	Galveston-Houston	POLYGON ((-97.34735 25.93118, -97.32600 25.917...
10	Hartford	9	007	00212797	09007	Middlesex	Middlesex County	06	NaN	Connecticut	CT	9	Middlesex County, Connecticut	Norwich	Norwich	Hartford	MULTIPOLYGON (((-73.49606 40.97549, -72.99955 ...
11	Indianapolis	18	073	00450494	18073	Jasper	Jasper County	06	13.0	Indiana	IN	18	Jasper County, Indiana	Lafayette in Indiana	Lafayette in Indiana	Indianapolis	POLYGON ((-86.91118 37.94157, -86.97618 37.931...
12	Kansas City in Kansas	20	073	00485003	20073	Greenwood	Greenwood County	06	15.0	Kansas	KS	20	Greenwood County, Kansas	Wichita	Wichita	Kansas City in Kansas	POLYGON ((-101.83357 36.99394, -102.04209 36.9...
13	Las Vegas	49	033	01448030	49033	Rich	Rich County	06	NaN	Utah	UT	49	Rich County, Utah	Salt Lake City	Salt Lake City	Las Vegas	POLYGON ((-115.85768 35.97280, -116.87425 36.7...
14	Los Angeles	6	083	00277306	06083	Santa Barbara	Santa Barbara County	06	4.0	California	CA	6	Santa Barbara County, California	Los Angeles	Los Angeles	Los Angeles	MULTIPOLYGON (((-119.62594 33.30504, -119.5881...
15	Louisville	21	053	00516873	21053	Clinton	Clinton County	06	16.0	Kentucky	KY	21	Clinton County, Kentucky	Louisville	Louisville	Louisville	POLYGON ((-88.51322 34.99585, -90.14836 34.994...
16	Miami	12	053	00295751	12053	Hernando	Hernando County	06	8.0	Florida	FL	12	Hernando County, Florida	St. Petersburg	St. Petersburg	Miami	MULTIPOLYGON (((-83.34679 29.24349, -83.35723 ...
17	Milwaukee	55	111	01581115	55111	Sauk	Sauk County	06	48.0	Wisconsin	WI	55	Sauk County, Wisconsin	Madison	Madison	Milwaukee	POLYGON ((-90.43714 42.50726, -90.64284 42.508...
18	Mobile	1	027	00161539	01027	Clay	Clay County	06	0.0	Alabama	AL	1	Clay County, Alabama	Birmingham	Birmingham	Mobile	POLYGON ((-90.86806 30.99931, -91.63694 30.999...
19	New Orleans	22	019	00558468	22019	Calcasieu	Calcasieu Parish	15	17.0	Louisiana	LA	22	Calcasieu Parish, Louisiana	Lake Charles	Lake Charles	New Orleans	POLYGON ((-92.63254 29.52972, -92.76760 29.570...
20	New York	36	101	00974148	36101	Steuben	Steuben County	06	31.0	New York	NY	36	Steuben County, New York	Rochester	Rochester	New York	MULTIPOLYGON (((-73.89406 40.99717, -73.92982 ...
21	Newark	34	037	00882236	34037	Sussex	Sussex County	06	29.0	New Jersey	NJ	34	Sussex County, New Jersey	Paterson	Paterson	Newark	POLYGON ((-74.48282 39.28413, -74.52396 39.240...
22	Oklahoma City	5	137	00069902	05137	Stone	Stone County	06	3.0	Arkansas	AR	5	Stone County, Arkansas	Little Rock	Little Rock	Oklahoma City	POLYGON ((-96.93625 33.95365, -96.97287 33.935...
23	Omaha	31	039	00835841	31039	Cuming	Cuming County	06	26.0	Nebraska	NE	31	Cuming County, Nebraska	Omaha	Omaha	Omaha	POLYGON ((-101.33559 40.00268, -102.05174 40.0...
24	Philadelphia	42	007	01214112	42007	Beaver	Beaver County	06	37.0	Pennsylvania	PA	42	Beaver County, Pennsylvania	Pittsburgh	Pittsburgh	Philadelphia	POLYGON ((-78.38503 39.72271, -80.51934 39.721...
25	Portland in Oregon	41	063	01155135	41063	Wallowa	Wallowa County	06	36.0	Oregon	OR	41	Wallowa County, Oregon	Baker	Baker	Portland in Oregon	POLYGON ((-123.23774 42.00368, -122.37805 42.0...
26	San Antonio	48	327	01383949	48327	Menard	Menard County	06	42.0	Texas	TX	48	Menard County, Texas	San Angelo	San Angelo	San Antonio	POLYGON ((-102.82939 29.44588, -102.81953 29.4...
27	San Francisco	6	091	00277310	06091	Sierra	Sierra County	06	NaN	California	CA	6	Sierra County, California	Sacramento	Sacramento	San Francisco	MULTIPOLYGON (((-155.01370 19.79093, -154.9778...
28	Santa Fe	35	011	00933054	35011	De Baca	De Baca County	06	30.0	New Mexico	NM	35	De Baca County, New Mexico	Santa Fe	Santa Fe	Santa Fe	POLYGON ((-110.64721 31.33312, -111.07498 31.3...
29	Seattle	53	069	01513275	53069	Wahkiakum	Wahkiakum County	06	46.0	Washington	WA	53	Wahkiakum County, Washington	Seattle	Seattle	Seattle	POLYGON ((-122.26262 45.54432, -122.33150 45.5...
30	St. Louis	29	083	00758496	29083	Henry	Henry County	06	24.0	Missouri	MO	29	Henry County, Missouri	Kansas City-St. Joseph	Kansas City-St. Joseph	St. Louis	POLYGON ((-94.09515 36.49868, -94.61786 36.499...
31	St. Paul and Minneapolis	46	099	01265772	46099	Minnehaha	Minnehaha County	06	40.0	South Dakota	SD	46	Minnehaha County, South Dakota	Sioux Falls	Sioux Falls	St. Paul and Minneapolis	POLYGON ((-100.22366 42.99873, -104.05303 43.0...
32	Washington	78	030	02378250	78030	St. Thomas	St. Thomas Island	10	54.0	Virgin Islands	VI	78	St. Thomas Island, Virgin Islands	St. Thomas	St. Thomas	Washington	MULTIPOLYGON (((-64.95180 17.69928, -64.93894 ...