Tips for clearing duplicate data

Tips for removing duplicates

1. Normalize data before deleting

Bring the text to a single format: lower case, without extra spaces. Otherwise, “test@mail.ru” and “Test@Mail.Ru” will be considered different.

2. Check the result

After removing duplicates, compare the number of lines before and after. Make sure you haven't deleted any necessary data.

3. Keep the original

Always work with a copy of the data. If the deletion was incorrect, you can return to the original data.

4. Consider partial duplicates

Sometimes the lines differ slightly (space, comma). Normalize the format before comparing.

5. Process large lists in blocks

If the list contains tens of thousands of rows, break it into parts for faster processing.

6. Combine with sorting

Sort the list first - this will make it easier to visually identify duplicates next to each other.

Example workflow

See also: Sorting Strings, Data Extraction