lose Ticker and Date columns after merging two Pandas Data frames together

I have two data frames, the first represent share prices and the second represent the company names. When I try to merge them on a unique key, which is SimFinId, everything is fine except that I lose the Ticker and the Date columns from the share prices table. I need to keep those two columns on every merge -I want later also to merge the output with a third table -so I can later filter after the date. I'm using Jupyter. Any help will be much appreciated!

pip install simfin
    # Import the main functionality from the SimFin Python API.
import simfin as sf

# Import names used for easy access to SimFin's data-columns.
from simfin.names import *
    import datetime

# Set your API-key for downloading data. This key gets the free data.
sf.set_api_key('free')

# Set the local directory where data-files are stored.
# The directory will be created if it does not already exist.
sf.set_data_dir('~/simfin_data/')

# Download the data from the SimFin server and load into a Pandas DataFrame.
df_prices = sf.load_shareprices(variant='daily', market='us', index=[TICKER, DATE])

Thats the share prices table

                   SimFinId   Open    Low   High  Close  Adj. Close  Dividend  \
Ticker Date                                                                     
A      2007-01-03     45846  34.99  34.05  35.48  34.30       22.66       NaN   
       2007-01-04     45846  34.30  33.46  34.60  34.41       22.73       NaN   
       2007-01-05     45846  34.30  34.00  34.40  34.09       22.52       NaN   
       2007-01-08     45846  33.98  33.68  34.08  33.97       22.44       NaN   
       2007-01-09     45846  34.08  33.63  34.32  34.01       22.47       NaN   

                    Volume  Shares Outstanding  
Ticker Date                                     
A      2007-01-03  2574600                 NaN  
       2007-01-04  2073700                 NaN  
       2007-01-05  2676600                 NaN  
       2007-01-08  1557200                 NaN  
       2007-01-09  1386200                 NaN  

# Download the companies data from the SimFin server and load into a Pandas DataFrame.
df_companies = sf.load_companies(market='us', index=[TICKER])

Thats the company name table

           SimFinId                      Company Name  IndustryId
Ticker                                                            
A              45846          AGILENT TECHNOLOGIES INC    106001.0
AA            367153                        Alcoa Corp    110004.0
AAC_delist    939324                AAC Holdings, Inc.    106011.0
AAL            68568      American Airlines Group Inc.    100006.0
AAMC          847094  Altisource Asset Management Corp    104001.0

# Merging the share prices Data with the companies Data on SimFinId.
pd.merge(df_companies, df_prices, on='SimFinId')

That image shows the output of the merge