hdary85

# Function to find interdependent product groups
def find_interdependent_groups(transactions):
    product_groups = []
    remaining_products = set()

    # Get unique products
    for products in transactions:
        remaining_products |= products

    transactions_copy = transactions.copy()  # Create a copy of the list

hdary85

def populate_tree(tree, item, dictionary):
    if isinstance(dictionary, dict):
        for key, value in dictionary.items():
            if isinstance(value, dict):
                sub_item = tree.insert(item, "end", text=key)
                populate_tree(tree, sub_item, value)
            else:
                tree.insert(item, "end", text=key, values=(value,))
    else:
        tree.insert(item, "end", values=(dictionary,))

hdary85

import xlrd

# Open the workbook
workbook = xlrd.open_workbook('your_excel_file.xls')

# Select the first sheet
sheet = workbook.sheet_by_index(0)

# Iterate through rows and columns to read data
for row in range(sheet.nrows):

hdary85

%let folder_path = "your_folder_path"; /* Specify the path to your folder */
%let table_name = "xyz"; /* Specify the table name to search for */

/* Create a fileref for the directory */
filename dirlist "&folder_path" ;

/* Get a list of SAS program files in the folder */
data sas_files;
  length file_name $256.;
  infile dirlist truncover;

hdary85

import win32com.client
import pandas as pd
import io
from datetime import datetime

# Connect to Outlook
outlook = win32com.client.Dispatch("Outlook.Application")
namespace = outlook.GetNamespace("MAPI")

# Recherche du dossier principal par son nom

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import random

def jeu_de_devinette():
    nombre_a_deviner = random.randint(1, 20)
    essais = 0

    print("Bienvenue dans le jeu de devinette !")
    print("Je pense à un nombre entre 1 et 20.")

    while True:

hdary85

with open('your_file.txt', 'r') as file:
    paragraphs = file.read().split('$')

# Remove leading and trailing whitespace from each paragraph
paragraphs = [p.strip() for p in paragraphs]

# Remove duplicates while preserving order
unique_paragraphs = []
seen = set()