y contains previously unseen labels

[pokekarat]

After executing this command "sh run.sh randomforest", I got the following error messages.

Traceback (most recent call last):
File "/opt/anaconda3/envs/kaggle/lib/python3.8/runpy.py", line 193, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/opt/anaconda3/envs/kaggle/lib/python3.8/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/Users/ekaratrattagan/Program/Course/machine_learning/kaggle/e01/src/train.py", line 45, in
train_df.loc[:, c] = lbl.transform(train_df[c].values.tolist())
File "/opt/anaconda3/envs/kaggle/lib/python3.8/site-packages/sklearn/preprocessing/_label.py", line 273, in transform
_, y = encode(y, uniques=self.classes, encode=True)
File "/opt/anaconda3/envs/kaggle/lib/python3.8/site-packages/sklearn/preprocessing/_label.py", line 117, in _encode
return _encode_numpy(values, uniques, encode,
File "/opt/anaconda3/envs/kaggle/lib/python3.8/site-packages/sklearn/preprocessing/_label.py", line 49, in _encode_numpy
raise ValueError("y contains previously unseen labels: %s"
ValueError: y contains previously unseen labels: [nan, nan, nan, nan, nan, nan, nan, nan, ....

I then fixed it by adding the following two lines,
train_df[c].replace(np.nan, 'NAN', inplace=True)
valid_df[c].replace(np.nan, 'NAN', inplace=True)
,after for c in train_df.columns: and before lbl = preprocessing.LabelEncoder()
in train.py

label_encoders = {}
for c in train_df.columns:
train_df[c].replace(np.nan, 'NAN', inplace=True)
valid_df[c].replace(np.nan, 'NAN', inplace=True)
lbl = preprocessing.LabelEncoder()

After that, it worked perfectly.