Free CSV guides

Practical, free how-to guides for cleaning up CSV files — no purchase required.

• Remove duplicate rows from a CSV

  A step-by-step way to find and remove duplicate rows in a CSV using Excel, Google Sheets, or a short Python script, plus what to watch out for with near-duplicates.

• Fix a broken/malformed CSV file

  Practical steps to diagnose and repair a CSV file that won't open cleanly: wrong delimiter detection, character-encoding issues, and rows with the wrong number of columns.

• CSV cleanup checklist

  A short pre-import checklist to catch the most common CSV problems before they cause failed imports or silent data corruption.

• Fix CSV encoding errors in Python

  Why pandas or the csv module raises UnicodeDecodeError on some CSV files, and the encodings to try instead of guessing.

• Merge multiple CSVs without duplicates

  A step-by-step way to combine several CSV exports (e.g. contact lists from different tools) into one clean file, and where duplicates usually sneak in.

• Export CRM contacts to CSV cleanly

  Practical tips for exporting contacts/leads from a CRM (HubSpot, Salesforce, Pipedrive, etc.) to CSV so the file opens cleanly and doesn't corrupt special characters.

• CSV file too large for Excel

  Why Excel truncates or slows to a crawl on big CSV exports, and practical ways to work with a large file without losing rows.

• Compare two CSV files for differences

  Ways to diff two versions of a CSV export (e.g. this month's list vs. last month's) to see which rows were added, removed, or changed.

• Stop Excel removing leading zeros

  Zip codes, account numbers, and product codes losing their leading zeros when a CSV is opened in Excel — why it happens and how to prevent or fix it.

• Stop Excel changing dates/values in a CSV

  Why dates, gene/product codes, and other text values sometimes silently change when a CSV is opened in Excel, and how to stop it from happening.

• Remove blank rows/columns from a CSV

  Why exports sometimes end up with trailing blank rows or unnamed empty columns, and how to clean them out before importing elsewhere.

• Handling commas/quotes in CSV values

  The quoting rules that let a CSV field safely contain a comma, a quote character, or a line break — and what goes wrong when they're missing.

• Convert CSV to Excel (.xlsx) properly

  The right way to turn a .csv file into a proper .xlsx workbook — and the data-corruption pitfalls (leading zeros, dates, encoding) to check for first.

• Handling missing/empty values in a CSV

  The difference between a truly empty field, a literal 'NULL'/'N/A' string, and a missing column — and how each one behaves differently when imported.

• Fix CSV line-ending issues (Windows vs. Unix)

  Why a CSV that opens fine on Windows sometimes shows every row squashed onto one line on Mac/Linux (or vice versa), and how to fix it.

• Trim extra whitespace from CSV values

  Why a leading or trailing space in a CSV field can make two records that look identical fail to match — and how to strip whitespace safely.

• Split one CSV column into multiple

  Splitting a combined field like 'full name' or 'city, state' into separate columns, and the edge cases that trip up a naive split.

• Combine multiple CSV columns into one

  Merging separate columns like first/last name or address parts into a single combined field, and handling blanks along the way.

• Normalize letter case before matching CSV rows

  How '[email protected]' and '[email protected]' silently fail to match as the same record, and the right way (and wrong way) to normalize case.

• Standardize phone number formats in a CSV

  Why '(555) 123-4567', '555-123-4567', and '5551234567' look like different values to a computer, and how to normalize them for matching without losing the original.

• Validate a CSV's schema before import

  A quick way to check column names, order, and row counts match what the destination system expects, before a bad import fails partway through.

• Fix ambiguous date formats (MM/DD vs DD/MM)

  Why a date like 03/04/2024 means different things in the US vs. most other countries, and how to standardize it without silently swapping month and day.

• Handle international number/currency formats

  Why '1.234,56' isn't a typo — it's the standard decimal format in much of Europe — and how to parse mixed-locale numeric CSV data safely.

• Back up and version a CSV before editing

  A simple habit that makes every other CSV cleanup guide reversible: never edit the only copy of the file.

• Remove duplicate header rows after merging CSVs

  A common bug from concatenating CSV exports: the header row from every file after the first ends up repeated as a fake data row.

• Detect a truncated/incomplete CSV file

  A CSV cut off mid-download can still open without an obvious error — here's how to check the file actually ended the way it should.

• Resolve conflicting data between duplicate rows

  Two rows share the same email but have different phone numbers or job titles — which one is right? A decision framework for conflicting duplicate data.

• Test a cleanup script on a sample before the full file

  Running an untested script on your entire dataset the first time is how small bugs turn into large data-loss incidents. Here's a safer workflow.

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