Python - Tkinter : Button activates function and prints dataframe in Tkinter

I am building a process in tkinter which allows the user to select two CSV Files - the files will then be fed into a function and the function's output will consist of a dataframe ( The output is a result of Merge , GroupBy and Count operations on the selected files). My GUI should consist of 3 Buttons ( 2 buttons for selecting files from the Desktop) and 1 Run button that would print the resulting dataframe as a table in tkinter. I have been able to create the buttons; however I am unable to print the dataframe once the Run button is selected.

The buttons:

root = tk.Tk()
ttk.Button(root, text="Load CCE file", command=open_CCE_file).place(x=50,y=60,width=120)
ttk.Button(root, text="Load SMS output file", command=open_SMS_file).place(x=50,y=20,width=120)
ttk.Button(root, text='Run', command= process_files).place(x=50,y=100,width=120)

The functions:

def open_SMS_file():
    file = filedialog.askopenfile(mode='r', filetypes=[('All Files', '*.*')])
    global path_SMS
    if file:
        filepath = os.path.abspath(file.name)
        Label(root, text=str(filepath), font=('Aerial 11')).place(x=180,y=20)
        path_SMS=str(filepath)

# Function determining the path for the CCE file        
def open_CCE_file():
    file = filedialog.askopenfile(mode='r', filetypes=[('All Files', '*.*')])
    global path_CCE
    if file:
        filepath = os.path.abspath(file.name)
        Label(root, text=str(filepath), font=('Aerial 11')).place(x=180,y=60)
        path_CCE=str(filepath)

def process_files():
    
    
    CCE_file = pd.read_csv(path_CCE, encoding='latin1') # read CCE file into dataframe 
    SMS_file = pd.read_csv(path_SMS) # read SMS file into dataframe 
    
    # filter cell code column from SMS file - new SMS dataframe that consists of the CellCode column
    SMS_file_selected = SMS_file[['CellCode']]
    
    # Select Source,content and rules columns from the CCE file
    # Rules column contains the cell codes corresponding to each segement
    CCE_file_selected = CCE_file[['Name','Source','Content EN','Content FR','Rule(s)']]
    CCE_file_selected.rename(columns={'Rule(s)':'Rules'}, inplace=True)
    
    # loop that retreives the cell codes for each segment and puts them in a list
    # each row in the Rules column will consist of a list of cell codes corresponding to a given segement 
    for i in range(len(CCE_file_selected)):
        CCE_file_selected['Rules'][i] = get_access_codes(CCE_file_selected['Rules'][i])
        
    
    # series that outputs the count per cellcode in the SMS file
    count_series = SMS_file_selected.groupby(['CellCode']).size()
    
    # Count series to dataframe
    SMS_count_df = pd.DataFrame({'CellCode':count_series.index, 'count':count_series.values})
    
    # adding segment name column to the SMS dataframe to match each cell code to its corresponidng segement
    SMS_count_df["Segment_name"] = ""
    
    # loop that matches segement name to cell code - ouput is (segement_name - cell_code - count)
    for i in range(len(SMS_count_df)): # loop through each row in the SMS file
        for j in range(len(CCE_file_selected)): # inner loop each row in the CCE file
            if SMS_count_df['CellCode'][i] in CCE_file_selected['Rules'][j]: 
                SMS_count_df['Segment_name'][i] = CCE_file_selected['Source'][j] 
                
    SMS_count_df = SMS_count_df[['Segment_name', 'CellCode', 'count']]
    # group by segement and cell code and return number of rows 
    Counts_table = SMS_count_df.groupby(['Segment_name','CellCode']).sum('count') 
    
   

    CCE_file_output = CCE_file_selected[['Source','Content EN','Content FR']]
    
    
    return Counts_table

Counts_table should be displayed when the Run button is clicked