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import pandas as pd import tkinter as tk from tkinter import filedialog, simpledialog def display_information(): # Display text prompt for required columns info_text.config(state=tk.NORMAL) info_text.delete('1.0', tk.END) info_text.insert(tk.END, "Please make sure the selected Excel sheet 1 has the following columns:\n" "1. Software Features\n" "2. Requirement(s)\n" "3. Specification(s)\n\n" "The second Excel sheet 2 should have columns:\n" "- Column1\n" "- Column2") info_text.config(state=tk.DISABLED) def process_files(): # Prompt to choose the first Excel sheet path_to_sheet1_excel = filedialog.askopenfilename( title="Step 1: Choose Excel Sheet with Columns", filetypes=[("Excel Files", "*.xlsx;*.xls")] ) # Load data from the first Excel sheet df_sheet1 = pd.read_excel(path_to_sheet1_excel) # Prompt to choose the second Excel sheet path_to_sheet2_excel = filedialog.askopenfilename( title="Step 2: Choose Second Excel Sheet with Columns Column1 and Column2", filetypes=[("Excel Files", "*.xlsx;*.xls")] ) # Load data from the second Excel sheet df_sheet2 = pd.read_excel(path_to_sheet2_excel) # If "Concated" column doesn't exist in the second sheet, create it if 'Concated' not in df_sheet2.columns: # Prompt to choose the columns for concatenation column1_name = simpledialog.askstring("Dora", "Enter the name of the first column:") column2_name = simpledialog.askstring("Dora", "Enter the name of the second column:") # Concatenate specified columns and create "Concated" column df_sheet2['Concated'] = df_sheet2[column1_name] + '|' + df_sheet2[column2_name] # Print the type of data in the 'Concated' column print("Data type of 'Concated' column:", type(df_sheet2['Concated'].iloc[0])) # Extract Concated filters from "Concated" column of Sheet2 concated_filters = df_sheet2['Concated'].tolist() # Create an empty dataframe to store the results result_df = pd.DataFrame(columns=['Column1', 'Column2', 'Concated', 'Features']) # Iterate through Concated filters for concated_filter in concated_filters: # Clean the Concated filter to remove non-printable characters cleaned_filter = ''.join(char for char in concated_filter if char.isprintable()) # Split the cleaned Concated filter column1, column2 = cleaned_filter.split('|') # Filter based on Column1 and Column2 in the first sheet filter_condition = (df_sheet1['Requirement(s)'].str.contains(column1)) & (df_sheet1['Specification(s)'].str.contains(column2)) filtered_df = df_sheet1[filter_condition].copy() # Get unique features for the Concated value features = ', '.join(filtered_df['Software Features'].unique()) # Append to the result dataframe result_df = pd.concat([result_df, pd.DataFrame({'Column1': [column1], 'Column2': [column2], 'Concated': [concated_filter], 'Features': [features]})], ignore_index=True) # Display the resulting dataframe result_text.config(state=tk.NORMAL) result_text.delete('1.0', tk.END) result_text.insert(tk.END, result_df.to_string(index=False)) result_text.config(state=tk.DISABLED) # Save result to Excel result_df.to_excel('output.xlsx', index=False) # Create the main application window app = tk.Tk() app.title("Dora by Team Medley") # Display information text info_text = tk.Text(app, height=10, width=80, state=tk.DISABLED) info_text.pack(padx=10, pady=10) display_information() # Create buttons and text widget process_button = tk.Button(app, text="Process Files", command=process_files) result_text = tk.Text(app, height=10, width=80, state=tk.DISABLED) # Pack buttons and text widget process_button.pack(pady=10) result_text.pack(padx=10, pady=10) # Start the main loop app.mainloop()
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