Resolving CSV import errors

The guide below addresses the most common conflicts and errors when importing data from a CSV in the Social Card batching tool. Please reach out if the problem you are having cannot be resolved using one of the below methods. A member of our team will be more than happy to review your file and address any problems.

Email Field Warning

If you receive the following error/warning:

Your data does not contain a field titled email. Emails for each recipient are required for automated distribution.

This is the importer warning you that if you proceed with batching using this data set, our systems will be unable to distribute published cards automatically to your team.

If you do not wish to take advantage of automatic distribution, you can ignore this warning/error and proceed with batching. To resolve this error, add a column to your dataset titled email. If you already have a field in your dataset containing team member emails, you can fix this warning by renaming the column to email.

Missing Headers

Although not an error, if your data set does not contain a row of headers (or titles), it may cause unnecessary confusion when working with the imported data. We strongly recommend adding headers to your dataset(s) before importing them into the platform.

Missing Quotes

If you receive a missing quote error (as seen below), here is what to look for:

"Quoted field unterminated" This error means that one or more fields within your dataset contain quotation marks that are not closed. To resolve this error, ensure that all opened quotation marks have a closing or "terminated" quotation mark pairing. Invalid Quotes

If you receive an invalid quote error (as seen below), here is what to look for:

"Trailing quote on the quoted field is malformed"

This error means that one or more fields within your dataset contain quotation marks that are mismatches of one another. To resolve this error, ensure that all quotation marks match in a single quotation (' & `) or double quotation (") format.

Field Mismatch

If you receive an invalid quote error (as seen below), here is what to look for:

Too Few Fields

This error means that the data contained in one or more rows does not correlate to the provided headers. In the case of "Too Few Fields," your dataset contains one or more rows that have fewer fields than expected. For example, the message "Too few fields: Expected 3 fields but parsed 2" suggests that your data set has one or more rows with only two fields when the parser expects to receive three based on the file headers. To identify and resolve this error, open your dataset file and look for fields that do not contain the same number of fields as other rows.

Too Many Fields

This error means that the data contained in one or more rows does not correlate to the provided headers. In the case of "Too Many Fields," your dataset contains one or more rows that have more fields than expected. For example, the message "Too many fields: Expected 3 fields but parsed 5" suggests that your data set has one or more rows with five fields when the parser expects to receive three based on the file headers. To identify and resolve this error, open your dataset file and look for fields that do not contain the same number of fields as other rows.

Delimiter

Any errors referencing a delimiter mean that the dataset provided is not formatted correctly for parsing. Likely, this message will suggest that the parsing engine could not auto-detect the delimiter (or field operator) in the CSV file. The standard for delimiter is a comma (,). Look at the CSV Wiki to learn more about formatting CSV files.