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Type-inference problem

Find Mixed Data Types in a CSV Column

Detect columns containing incompatible numbers, dates, booleans and text before importing them into typed systems.

Use the matching tool

Column Type Detector

Open Column Type Detector

What the error actually means

CSV does not store types. Importers infer them from text and may choose a type from an early sample. Later currency symbols, null markers or invalid dates can then fail the import or coerce the whole column to text.

Likely causes

  • Formatted and raw numbers are mixed.
  • Several date formats appear.
  • Identifiers resemble numbers.
  • Error labels are embedded in a numeric column.

Mixed amount column

Problem

12.50, $9.00, N/A, error

Correct pattern

12.50, 9.00, null, with error rows reported separately

A safe repair workflow

  1. 1Profile candidate types by column.
  2. 2Keep identifiers as text.
  3. 3Normalize valid values and isolate exceptions.
  4. 4Import a sample with explicit destination types.

How to verify the result

A file that downloads successfully is not automatically a correct file. Check the result at both the structural and business-data levels:

  • Exception counts are known.
  • Precision and leading zeros survive.
  • Invalid dates remain flagged.
  • The destination schema accepts the sample.

Read the deeper guides

How to Prepare CSV Files for Python PandasPrepare CSV files for reliable pandas imports by making encoding, delimiters, nulls, dates, identifiers, and column types explicit.How to Clean CSV Data Without Hiding the Original ProblemsLearn practical techniques to clean messy CSV files. Remove duplicates, fix formatting, and standardize data without Excel crashes or complex scripts.