Cant get it to work with custom dataset (Timeseries)

[Slayingripper]

I've been trying to implement my own dataset, but keep running into issues when using everwhereml. I've implemented a decision tree approach using normal SKLearn and works fine.

Example using Standard Sklearn

data=pd.read_csv(config.get('Datasets', 'Minime'), delimiter=',')

# use Decision tree to classify Minime  if it is good or bad
#drop first row
data = data[['Time', 'Flag']]
data['Time'] = data['Time'].str.replace(':', '')
data['Time'] = data['Time'].str.replace('.', '')

X = data.drop('Flag', axis=1)
y = data['Flag']

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20)
classifier = DecisionTreeClassifier()
classifier.fit(X_train, y_train)

Example using everywhereml SKlearn

data=pd.read_csv(config.get('Datasets', 'Minime'), delimiter=',')

data = data[['Time', 'Flag']]
data['Time'] = data['Time'].str.replace(':', '')
data['Time'] = data['Time'].str.replace('.', '')
X = data.drop('Flag', axis=1)
y = data['Flag']
#X, y = make_blobs(n_samples=100, centers=3, n_features=2, random_state=0)

clf = DecisionTreeClassifier()

clf.fit(X, y)

Gives out this error in python3.9

Traceback (most recent call last):
  File "/home/vasilisieropoulos/gitstuff/IoT-Ai/Machine Learning/thefinish.py", line 32, in <module>
    clf.fit(X, y)
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/sklearn/SklearnBaseClassifier.py", line 95, in fit
    self.dataset = Dataset.from_XY(X, y)
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/data/Dataset.py", line 39, in from_XY
    return Dataset(
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/data/Dataset.py", line 124, in __init__
    self.replace(X=X, y=y, feature_names=feature_names, target_names=target_names)
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/data/Dataset.py", line 195, in replace
    self._update_df()
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/everywhereml/data/Dataset.py", line 285, in _update_df
    data = np.hstack((self.X, self.y.reshape((-1, 1))))
  File "/home/vasilisieropoulos/anaconda3/lib/python3.9/site-packages/pandas/core/generic.py", line 5575, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'reshape'

Is this due to the python version or something else ? I can't get this to work in python3.10 since the Iterable abstract class was removed from collections in Python 3.10.