Created the model and pickled it, however while predicting Y values for Test Data, getting this error.

Command - y_pred = regressor.predict(df_Test)
Output

XGBoostError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_26796/2506740906.py in
----> 1 y_pred = regressor.predict(df_Test)
2 sns.heatmap(df_Test.isnull(),yticklabels=False,cbar=False)

C:\ProgramData\Miniconda3\lib\site-packages\xgboost\sklearn.py in predict(self, X, output_margin, ntree_limit, validate_features, base_margin, iteration_range)
1047 if self._can_use_inplace_predict():
1048 try:
-> 1049 predts = self.get_booster().inplace_predict(
1050 data=X,
1051 iteration_range=iteration_range,

C:\ProgramData\Miniconda3\lib\site-packages\xgboost\core.py in inplace_predict(self, data, iteration_range, predict_type, missing, validate_features, base_margin, strict_shape)
2100 from .data import _ensure_np_dtype
2101 data, _ = _ensure_np_dtype(data, data.dtype)
-> 2102 _check_call(
2103 _LIB.XGBoosterPredictFromDense(
2104 self.handle,

C:\ProgramData\Miniconda3\lib\site-packages\xgboost\core.py in _check_call(ret)
201 """
202 if ret != 0:
--> 203 raise XGBoostError(py_str(_LIB.XGBGetLastError()))
204
205

XGBoostError: [00:23:51] c:\users\administrator\workspace\xgboost-win64_release_1.6.0\src\c_api\c_api_utils.h:159: Invalid missing value: null

Hi Krish,

Thanks a lottttttttt for sharing all good content every day.. I'm watching each and every video of yours., those are such an informative..

Also, big Thank you for sharing this code. Please share the data files as well (untouched .csv files), so that I can do some practice over them.