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There are several steps that can be taken to resolve the issue of a PySpark 3.3.0 dataframe displaying data but generating an empty CSV file while writing:

1. Check for data type compatibility: The data types in the PySpark dataframe should be compatible with the data types specified in the CSV writer. If there is a mismatch between the data types, it can cause an empty CSV file to be generated. Ensure that the data types of the PySpark dataframe and the CSV writer are compatible.

2. Check for write permissions: Ensure that you have write permissions to the directory where the CSV file is being written. If you do not have write permissions, you will not be able to write data to the CSV file, resulting in an empty CSV file.

3. Check for missing records: Check for any missing records in the PySpark dataframe. If there are any records missing, it can cause an empty CSV file to be generated. Ensure that all records are present in the PySpark dataframe.

4. Check for encoding issues: Check for any encoding issues that may be causing the CSV file to be generated as empty. Ensure that the encoding used for the PySpark dataframe and the CSV writer are the same.

5. Try writing to a local file: Try writing the PySpark dataframe to a local file instead of a networked file system. This will help in identifying any issues related to the networked file system.

6. Check for Spark version compatibility: Ensure that the Spark version being used is compatible with the PySpark dataframe. If there is a compatibility issue, it can cause the CSV file to be generated as empty.

7. Check for missing data in partitions: Check for any missing data in partitions of the PySpark dataframe. If there are any missing data, it can cause an empty CSV file to be generated. Ensure that all partitions have data.

By following these steps, the issue of a PySpark 3.3.0 dataframe displaying data but generating an empty CSV file while writing can be resolved.