Courses / Build a Local SEO Audit Dashboard with Google Sheets & Python
Lesson 5 of 9

Introducing pandas for Data Cleaning

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Video by Keith Galli on YouTube · 60 min. We did not make this video and we do not host it — watching it here still counts as a view for the creator.

Load the CSV with pd.read_csv and clean duplicate URLs, trim whitespace, and extract domain names. A frequent beginner error is chaining operations without assigning back, which leaves the DataFrame unchanged. Use df.drop_duplicates(subset='url') and df['domain'] = df['url'].apply(lambda x: urlparse(x).netloc). Clean data ensures that KPI calculations like citation count are reliable, a step that agencies perform before presenting any audit to clients.

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