# ValueError: You are trying to merge on int64 and object columns. If you wish to proceed you should use pd.concat

- **ID:** `python/pandas-merge-type-mismatch`
- **Domain:** python
- **Category:** data_error
- **Verification:** ai_generated
- **Fix Rate:** 80%

## Root Cause

Join keys have mismatched dtypes (int vs string), preventing equality matches.

## Version Compatibility

| Version | Status | Introduced | Deprecated |
|---------|--------|------------|------------|
| 3.x | active | — | — |

## Workarounds

1. **** (95% success)
   ```
   df1['key'] = df1['key'].astype(str); df2['key'] = df2['key'].astype(str)
   ```
2. **** (85% success)
   ```
   pd.merge(df1, df2, left_on=df1.key.astype(int), right_on='key')
   ```

## Dead Ends

- **** — Produces cartesian/incorrect rows (80% fail)
- **** — Same dtype error (85% fail)