Complete Addresses
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You’re given two dataframes. One contains information about addresses and the other contains relationships between various cities and states:
Example:
df_addresses
address |
---|
4860 Sunset Boulevard, San Francisco, 94105 |
3055 Paradise Lane, Salt Lake City, 84103 |
682 Main Street, Detroit, 48204 |
9001 Cascade Road, Kansas City, 64102 |
5853 Leon Street, Tampa, 33605 |
df_cities
city | state |
---|---|
Salt Lake City | Utah |
Kansas City | Missouri |
Detroit | Michigan |
Tampa | Florida |
San Francisco | California |
Write a function complete_address
to create a single dataframe with complete addresses in the format of street, city, state, zip code.
Input:
import pandas as pd
addresses = {"address": ["4860 Sunset Boulevard, San Francisco, 94105", "3055 Paradise Lane, Salt Lake City, 84103", "682 Main Street, Detroit, 48204", "9001 Cascade Road, Kansas City, 64102", "5853 Leon Street, Tampa, 33605"]}
cities = {"city": ["Salt Lake City", "Kansas City", "Detroit", "Tampa", "San Francisco"], "state": ["Utah", "Missouri", "Michigan", "Florida", "California"]}
df_addresses = pd.DataFrame(addresses)
df_cities = pd.DataFrame(cities)
Output:
def complete_address(df_addresses,df_cities) ->
address |
---|
4860 Sunset Boulevard, San Francisco, California, 94105 |
3055 Paradise Lane, Salt Lake City, Utah, 84103 |
682 Main Street, Detroit, Michigan, 48204 |
9001 Cascade Road, Kansas City, Missouri, 64102 |
5853 Leon Street, Tampa, Florida, 33605 |
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