Iterating and updating a column using a list

 originallist = df['Customer'].tolist()

I have an list of customers. Within these customers, i have some translations to do which i have done. In other words, i iterate through the original list of about 4000 customers, find about 1500 entries that need to be translated and they can be anywhere in that original list/column. I now need to replace/map/update the entries with the updated translated customer.

 translated_customer = (translator.translate(customer).text)

How do I go about this? If it was one entry, all fine and good, but its because i have a list, its more complicated

Example Column 
these
are
all
good 
words
bien
bonjour
hello
word

I have the above list, iterate through, find those french words say, translate those words and now i need to update these words by slotting them back into the original list

  Example Column
these
are
all
good 
words
good
hello
hello
word

ignore duplicates

You can do this by mapping or updating the translated customers back to their original positions in the dataframe. To handle this for a list of customer entries, you can create a dictionary mapping the original customer names to their translated values, then use this dictionary to update the Dataframe.

Step 1: Create an empty dictionary to store translations. Step 2: Iterate through the original list of customers.

• Check if the customer needs translation.
• Translate the customer and store it in the dictionary. Step 3: Use the dictinoary to replace the original entries in the DataFrame by mapping the values back.

I will give you the full code for this.

# Step 1: Create a dictionary to store translations
translations = {}

# Step 2: Iterate over the original customer list and translate customers
for customer in df['customer']
  if customer_needs_translation(customer): # This is the condition to check if the customer needs translation
      translated_customer = trnaslator.trnaslate(customer).text
      translations[customer] = trnaslated_customer

# Step 3: Use the dictionary to map and replace the translated customers
df['Customer'] = df['Customer'].map(lambda x: translations.get(x,y))