Wiki: frequent issues

Frequent issues in geocoding and geovisualisation with Python

### Adding Timestamps to Filenames

Use `datetime.now().strftime('%Y%m%d_%H%M%S')` to create timestamped filenames. This helps differentiate outputs and supports reproducible file handling.

### Handling Empty Rows

Empty DataFrame rows cause alignment errors. Check with `pd.isna()` and append `"n/a"` or similar placeholders to maintain consistent list length.

### Consistent List Management

To prevent mismatches, update all lists (`lat`, `lng`, `IDs`, etc.) in every loop iteration, including when values are missing or skipped.

### Geonames API Integration

Use `geocoder.geonames(address, key=...)` with fallback on feature class `P` or `S`. API failures can return incomplete or null results.

### Error Handling in Loops

Catch exceptions like `IndexError` using `try...except`. Append default values instead of stopping the loop to ensure continuity.

### Appending IDs

Some rows may lack a valid Geonames ID. Use `row['place_geonames_id'].values[0]` if available; else append `"n/a"` to maintain structure.

### Placeholder Management

If geocoding fails, append `"n/a"` to every list involved. This ensures that all list lengths match the DataFrame’s rows.

### String Splitting for Addresses

Use `address.split(", ")[0].strip()` to extract the first part of an address string safely, avoiding index or format errors.

### Assigning Lists to DataFrame

Always check `len(list) == len(addresses_df)` before assignment. Mismatched lengths will raise errors or result in dropped rows.

### Debugging Geocoding Logic

Add `print()` statements or use logging to inspect `address`, `lat`, `lng`, and `ID`. Helps identify silent failures in your geocoding workflow.

### Geocoding Fallback Options

Use fallback strategies like switching to `featureClass='S'` if `featureClass='P'` fails. Increases the chance of matching less-standard places.