试图在 Python Pandas 中实现 join / vlookup（更新）

Question

Disclaimer: I am brand new to SO and Python.

I am trying to convert my SQL left join query to python.

Example:

df1 is a dataframe which contains the columns: City, Event, date

df2: City, Zip Code, State, Country, etc.

SQL:

SELECT Events.City, Events.Event, Events.Date, Masterlist.State, Masterlist.Country, Masterlist.[Zip Code]
FROM Events LEFT JOIN Masterlist ON Events.City = Masterlist.City

PYTHON:

df1 = pd.read_csv('Events.csv')

df2 = pd.read_csv('Masterlist.csv')

df3 = df1.join(df2, how='left')

df3 output:

City, Event, date, Zip Code, State, Country

Fremont, Charity, 6/11, 99999, CA, US

Oakland, Protest, 6/11, 99998, CA, US

Fremont, Concert, 6/12, null, null, null

Oakland, Concert, 6/12, null, null, null

Ideal output is that it references df2 and returns the value based on City.It is currently only returning it for the first found value with that City. How can I get it to populate with its respective State, Zip Code, and Country for each row item?

Answer 1

You didn't specify on, I believe the below works:

import pandas as pd


df1 = pd.DataFrame({'City':["Tucson","Tucson","Portland","San Diego"], 
                    "Event":[1,5,3,2], 
                     "date":[1,2,3,4]})
df2 = pd.DataFrame({"City":["San Diego", "Tucson", "Portland"], 
                    "zip":[1,2,3], "state":["CA", "AZ", "OR"], 
                    "country":["USA","USA","USA"]})
pd.merge(df1,df2, how="left", on="City")

It is also best to provide a minimal dataset (like I did above) to make it easy for people to work with and help you out.