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I have two pandas dataframes that look like:

provider_state                      provider_name provider_city  ... footnote  start_date    end_date
0                 AL            INFIRMARY LTAC HOSPITAL        MOBILE  ...      NaN  04/01/2019  09/30/2020
1                 AL            INFIRMARY LTAC HOSPITAL        MOBILE  ...      NaN  04/01/2019  09/30/2020
2                 AL            INFIRMARY LTAC HOSPITAL        MOBILE  ...      NaN  04/01/2019  09/30/2020
3                 AL            INFIRMARY LTAC HOSPITAL        MOBILE  ...      NaN  04/01/2019  09/30/2020
4                 AL            INFIRMARY LTAC HOSPITAL        MOBILE  ...      NaN  04/01/2019  09/30/2020
...              ...                                ...           ...  ...      ...        ...         ...
23800             WI  SELECT SPECIALTY HOSPITAL MADISON       MADISON  ...      NaN  07/01/2020  06/30/2021
23801             WI  SELECT SPECIALTY HOSPITAL MADISON       MADISON  ...        4  07/01/2020  06/30/2021
23802             WI  SELECT SPECIALTY HOSPITAL MADISON       MADISON  ...      NaN  07/01/2020  06/30/2021
23803             WI  SELECT SPECIALTY HOSPITAL MADISON       MADISON  ...      NaN  07/01/2020  06/30/2021
23804             WI  SELECT SPECIALTY HOSPITAL MADISON       MADISON  ...      NaN  07/01/2020  06/30/2021

[23805 rows x 11 columns]

provider_state                               provider_name provider_city  ...    phone_number  ownership_type total_number_of_beds
0               AL                     INFIRMARY LTAC HOSPITAL        MOBILE  ...  (251) 660-5611      Non-profit                 22.0
1               AL          NOLAND HOSPITAL MONTGOMERY II, LLC    MONTGOMERY  ...  (334) 240-0532      Government                 65.0
2               AL      SELECT SPECIALTY HOSPITAL - BIRMINGHAM    BIRMINGHAM  ...  (205) 599-4595      For profit                 38.0
3               AL          NOLAND HOSPITAL BIRMINGHAM II, LLC    BIRMINGHAM  ...  (205) 838-5100      Government                 45.0
4               AL              NOLAND HOSPITAL DOTHAN II, LLC        DOTHAN  ...  (334) 699-4300      Non-profit                 35.0
..             ...                                         ...           ...  ...             ...             ...                  ...
340             WV     ACUITY SPECIALTY HOSPITAL OF MORGANTOWN    MORGANTOWN  ...  (304) 598-1506      For profit                 25.0
341             WV       ACUITY SPECIALTY HOSPITAL OHIO VALLEY       WEIRTON  ...  (740) 283-7497      For profit                 49.0
342             WI  LAKEVIEW SPECIALTY HOSPITAL & REHAB CENTER     WATERFORD  ...  (262) 534-7297      For profit                 39.0
343             WI         SELECT SPECIALTY HOSPITAL MILWAUKEE    WEST ALLIS  ...  (414) 328-7700      For profit                 63.0
344             WI           SELECT SPECIALTY HOSPITAL MADISON       MADISON  ...  (608) 260-2700      For profit                 23.0

[345 rows x 8 columns]

I want to add the ownership_type and total_number_of_beds columns from the second data frame to the first one. Basically, I want it so that two new columns are created in data frame one where the value is based off of the provider_name column. For example, since INFIRMARY LTAC HOSPITAL has an ownership_type value of Non-Profit and a total_number_of_beds value of 22.0 in data frame 2, I would want every row in data frame 1 where the provider name is INFIRMARY LTAC HOSPITAL to have those values in the new ownership_type and total_number_of_beds column. I known there must be a quick way to do this, any suggestions?

1 Answers1

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Much thanks to G.Anderson for providing me with Pandas Merging 101, which led to:

left.merge(right[['provider_name', 'ownership_type', 'total_number_of_beds']], on='provider_name')