CSV File Won’t Import
Check delimiter structure, quoted fields, row consistency, UTF-8 readability, and file-format clues before retrying the same CSV import.
ARADURU checks file-side evidence in your browser first, then separates file problems from app or website problems.
Analyzing your file...
Checking the file structure.
ARADURU is checking this file.
Waiting for the diagnosis.
Wait for the browser-side check to finish.
Building your troubleshooting path.
Waiting for the problem context.
Waiting for the file check.
Waiting for the next step.
WHY ARADURU SAYS THIS
Review file evidence and details
File facts, recovery guidance, and technical checks stay here until you need them.
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Your file at a glance
ARADURU will suggest the safest next action after the file check finishes.
File identity evidence
Technical details View file checks
A CSV import can fail even when the file looks simple
CSV has no single universal schema or signature. ARADURU checks practical file-side structure such as delimiter consistency and quoted-field boundaries, then separates those findings from destination import rules.
A quoted field is not closed
An opening quote that reaches the end of the file can shift later rows and prevent reliable parsing.
Rows use different field counts
Some inconsistent rows are intentional, but unexpected column-count changes can break strict importers.
The importer expects another delimiter
Comma, tab, semicolon, and pipe-delimited files can all look table-like while a destination expects only one convention.
How ARADURU checks this data problem
Decode the selected CSV target as UTF-8 text for the current browser-side check.
Check balanced quoted fields before analyzing rows.
Detect comma, tab, semicolon, or pipe-delimited multi-column structure.
Compare row field counts and report inconsistent rows without assuming every variation is an error.
How to interpret the match level
ARADURU found concrete structured-data evidence that can directly explain or strongly contribute to the selected problem.
ARADURU found relevant file-side evidence, but schema, importer, API, application, or business-rule conditions can also matter.
The current parser did not reveal an obvious match for this problem. Continue with schema, importer, application, or destination-specific troubleshooting.
What this check cannot prove
ARADURU checks practical delimited-text structure, not the destination importer’s complete rules. Header names, locale, date formats, decimal separators, required columns, maximum rows, and field-level business rules can still cause rejection.
Common questions about this data problem
Why can a CSV look normal but fail to import?
The destination may expect a different delimiter, header set, column count, text encoding, locale, field type, or business rule even when the table looks readable.
Does ARADURU automatically rename unknown table text to .csv?
No. CSV identification is heuristic because CSV has no unique binary signature. ARADURU avoids an automatic extension rename when the evidence is not strong enough.
Are inconsistent row lengths always wrong?
No. Some data formats intentionally vary by row. ARADURU reports the inconsistency as evidence so you can compare it with the importer’s expected layout.