Как добавить кадры данных с одинаковым идентификатором?

Просто сделай concat с groupbysum

pd.concat([gold,silver,bronze]).groupby('Country').sum()
Out[1306]: 
         Medals
Country        
France       53
Germany      20
Russia       25
UK           27
USA          72

Исправление вашего кода

silver.add(gold,fill_value = 0).add(bronze,fill_value=0)

если мы ожидаем с плавающей запятой:

pd.concat([gold,silver,bronze]).groupby('Country').sum().astype(float)

# For a video solution of the code, copy-paste the following link on your browser:
# https://thewikihow.com/video_p0cnApQDotA

import numpy as np 
import pandas as pd

# Defining the three dataframes indicating the gold, silver, and bronze medal counts
# of different countries
gold = pd.DataFrame({'Country': ['USA', 'France', 'Russia'],
                         'Medals': [15, 13, 9]}
                    )
silver = pd.DataFrame({'Country': ['USA', 'Germany', 'Russia'],
                        'Medals': [29, 20, 16]}
                    )
bronze = pd.DataFrame({'Country': ['France', 'USA', 'UK'],
                        'Medals': [40, 28, 27]}
                    )

# Set the index of the dataframes to 'Country' so that you can get the countrywise
# medal count
gold.set_index('Country', inplace = True)
silver.set_index('Country', inplace = True) 
bronze.set_index('Country', inplace = True) 

# Add the three dataframes and set the fill_value argument to zero to avoid getting
# NaN values
total = gold.add(silver, fill_value = 0).add(bronze, fill_value = 0)

# Sort the resultant dataframe in a descending order
total = total.sort_values(by = 'Medals', ascending = False)

# Print the sorted dataframe
print(total)