Match products with several descriptions (Python)

[francis-fm]

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Hi I am trying to do the following: from a data table that is called products_web (web products) I need to match with matches in their descriptions with the description of the company's products. For example so I have the products in the one table I have the ones coming from the web and the other table is the internal products of the company. The third table contains all the matches of the web products in the internal products table. That is an example to follow.
I was thinking to make that when I have more than 2 matches then that web product conindenica is attached. But it didn't give me anything.

Here's what I was doing:

# Now we are going to iterate each value that is inside the array created in product_name and we are going to search if it is in the product column of the SKUs segmentation.
# if it is then we add it to a list of matches
# if it is not there then we add it to a list of no matches
# if it is not in either list then we add it to a not found list
matches = []
no_matches = []
not_found = []

# Iterate over each value in product_name and search for matches in the "product" column of df_internal
for index, row in df_web_.iterrows():
    count = 0
    for word in row["product_name"]:
        print(f "Searching for word: {word}")
        if word.lower() in df_internal["product"].str.lower().values:
            count += 1
            print(f "Match found for: {word}")
        else:
            not_found.append(word).
    if count >= 2:
        matches.append(row).
    else:
        no_matches.append(row).

print("Words not found:")
print(set(no_matches_found))

I have thousands of products that I must make this transformation: and for example already with real data I have like this:
what has a list inside product_name corresponds to web products and the other picture corresponds to the internal description of the company.

Thanks

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