Append CSV files with matching headers safely
Append exports only when their column names and order match, keep one header, and stop if a source file changes its schema.
Example files included
All guidesWhat went wrong with your CSV import?
Get your data into the right columns, with its identifiers and characters intact.
Start with the original file. Import settings matter more than cell formatting.
Match the symptom
- Everything lands in one column
- Check the separator and quoted fields.
- Zeros disappear from the start of IDs
- Keep identifiers as text when importing.
- Long IDs change or lose digits
- Check whether values changed before trying a display fix.
- Accents turn into strange characters
- Check the original file and its encoding.
Keep an untouched copy of your export. First check the columns, then the text and identifiers. A tidy table can still contain changed values.
Check your CSV separator with a pasted sample, or download a small example file.
Convert CSV to JSON records without guessing types
Convert a CSV table into a JSON array in Python while preserving identifiers, checking headers, and leaving numeric conversion explicit.
Example files included
Convert flat JSON records to CSV with fixed columns
Choose a column order for flat JSON objects, reject unexpected fields, and write CSV with deliberate handling of null and nested values.
Example files included
Convert TSV to CSV without breaking commas in values
Use a tab-aware reader and a comma-aware writer to convert TSV into CSV while preserving punctuation inside the original fields.
Example files included
CSV opens in one column? Identify the delimiter first
Compare comma, semicolon, and tab examples, preserve quoted fields, and select the right import separator without editing the original data.
Example files included
Decode a UTF-16 CSV before checking its delimiter
Read a UTF-16 CSV with its byte-order mark, then parse the decoded text without deleting zero bytes or replacing unreadable characters.
Example files included
Detect duplicate CSV headers before values disappear
Find repeated CSV column names before using DictReader, and keep the original columns available for an explicit rename decision.
Example files included
Find CSV rows with too many or too few columns
Check each CSV record against its header width in Python and report short or long records before importing or converting the file.
Example files included
Fix garbled accents when importing a CSV into Excel
Use controlled UTF-8 and Windows-1252 examples to identify a decoding problem and reimport accented text without overwriting the original bytes.
Example files included
Flag formula-like CSV values before spreadsheet import
Inspect text fields for formula-like prefixes before opening a CSV in a spreadsheet, and understand why CSV quoting alone is not a safety check.
Example files included
Keep leading zeros when importing a CSV into Excel
Import product codes as text, check the original values, and avoid confusing display padding with preserved data. Includes a small CSV example.
Example files included
Long numbers in Excel: formatting or lost digits?
Tell scientific notation apart from changed identifier digits, then reimport long IDs as text. Includes a precision-check CSV and expected values.
Example files included
Read CSV fields containing commas, quotes, and newlines
Parse quoted CSV fields in Python without splitting a note into extra columns or counting its embedded newline as another record.
Example files included
Read headerless CSV without losing the first row
Supply explicit field names for a headerless CSV in Python, preserve the first record, and check column widths before assigning names.
Example files included
Remove a sep= directive before parsing a CSV
Handle a known sep= directive before the CSV header so another parser does not treat the separator hint as an ordinary data column.
Example files included
Split a CSV into chunks with a header in each part
Chunk parsed CSV records in Python, repeat the header in every part, and check that no record is lost or split across files.
Example files included
Tell an empty CSV from a header-only export
Distinguish zero-byte, header-only, and populated CSV exports before a cleanup job reports success or overwrites an earlier result.
Example files included