usaddress | python library for parsing unstructured United States | Natural Language Processing library

import usaddress
from fuzzywuzzy import process

data1 = "3176 DETRIT ROAD"
choices = ["DETROIT RD"]

try:
    data1 = usaddress.tag(data1)
except usaddress.RepeatedLabelError:
    pass

parts = [
    data1[0].get("StreetNamePreDirectional

import os
import csv
import shutil
import usaddress
import pandas as pd
from fuzzywuzzy import process

with open(r"TEST_Cass_Howard.csv") as csv_file, \
        open(".\Scratch\Final_Test_Clean.csv", "w") as f, \
        open(r"TEST_Uniqu

from pyspark.sql.functions import *
from pyspark.sql.types import *

def cal(a: int, b: int) -> [int, int]:
    return [a+b, a*b]

cal = udf(cal, ArrayType(StringType()))

df.select('A', 'B', *[cal('A', 'B')[i] for i in range(0, 2)]) \

import usaddress

df2["short_address"] = df2["HouseNo"].astype(str) + " " + df2["StreetName"] + " " + df2["cityName"]

def f(x):
    norm_address = usaddress.tag(x)
     addressNum = norm_address[0]["AddressNumber"]
    streetName = norm_a

print(app.logger.name) # filename

print(app.logger.handlers) # [ (NOTSET)>]

app.logger.handlers.pop(0)

log_handler.setLevel(logging.DEBUG)

import usaddress
from address import AddressParser, Address
addr = usaddress.parse(address_line1)
ad = AddressParser()
addr2 = ad.parse_address(address_line1)
#perform some cleanup and functions on addr...
if addr2.street_suffix:
    post 

def copy(row):
    if 'Norfolk' in row[col_index_in_question]:
        return 'Norfolk'

def strip(row):
    return row[col_index_in_question].replace('Norfolk', '')


df['County'] = df.apply(copy, axis=1)
df[col_index_in_question] = df.ap

df = pd.DataFrame([[1, 2,], [3, 4]])
df

# This is a tuple (index value, Series object that represents row)
#   |
#   v    
for i in df.iterrows():
    print(df[i])
#            ^
#            |
# This is you trying to tell Pandas to use a

import usaddress
import pandas as pd

# your list of addresses dataframe
df = pd.read_csv('PATH_TO_ADDRESS_CSV')

# list of orderedDict
ordered_dicts = []

# loop through addresses and get respective information
for index, row in df.iterro