Streamlining web-scraped data for import into database
Budget: $15 – $25 USD
I'm looking for a data analyst who will take the text data in my CSV file and streamline it for import into a database. My project will involve the following tasks:
- Consolidating vast amounts of text data, approximately 23,000 rows, 140 columns (CSV).
- Cleaning up any discrepancies, repetitions, and inaccuracies,
- Organizing the cleaned data into fields provided by me.
- Deduplicate data.
- Simplify some data to reduce the total number of permutations. e.g. "Dark earth green" and "Pine forest green" would become "Green".
This data is from the scraping of an ecommerce store with physical products.
The ideal candidate for this project will have strong experience with text data management and data cleaning in spreadsheets. Being detail-oriented would be crucial for spotting any discrepancies and making sure no data is duplicated or incorrectly entered.
Ensure you have a strong command of Excel or analogous spreadsheet tools, along with experience in data cleanup, and data consolidation. Past examples of similar work would be useful during the selection process. More consideration for any candidate that has specific experience working with data that has been scraped from a website.
- Consolidating vast amounts of text data, approximately 23,000 rows, 140 columns (CSV).
- Cleaning up any discrepancies, repetitions, and inaccuracies,
- Organizing the cleaned data into fields provided by me.
- Deduplicate data.
- Simplify some data to reduce the total number of permutations. e.g. "Dark earth green" and "Pine forest green" would become "Green".
This data is from the scraping of an ecommerce store with physical products.
The ideal candidate for this project will have strong experience with text data management and data cleaning in spreadsheets. Being detail-oriented would be crucial for spotting any discrepancies and making sure no data is duplicated or incorrectly entered.
Ensure you have a strong command of Excel or analogous spreadsheet tools, along with experience in data cleanup, and data consolidation. Past examples of similar work would be useful during the selection process. More consideration for any candidate that has specific experience working with data that has been scraped from a website.