TypeError during resampling

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I am trying to apply resampling for my dataset which has unbalanced classes. What I have done is the following:

from sklearn.utils import resample

y = df.Label

vectorizer = CountVectorizer()
X = vectorizer.fit_transform(df['Text'].replace(np.NaN, ""))

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.30, stratify=y)

# concatenate our training data back together
X = pd.concat([X_train, y_train], axis=1)

# separate minority and majority classes
not_df = X[X.Label==0]
df = X[X.Label==1]

# upsample minority
df_upsampled = resample(df,

# combine majority and upsampled minority
upsampled = pd.concat([not_df, df_upsampled])

Unfortunately, I am having some problems at this step: X = pd.concat([X_train, y_train], axis=1), i.e.

/anaconda3/lib/python3.7/site-packages/pandas/core/reshape/concat.py in concat(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)
    279         verify_integrity=verify_integrity,
    280         copy=copy,
--> 281         sort=sort,
    282     )

/anaconda3/lib/python3.7/site-packages/pandas/core/reshape/concat.py in __init__(self, objs, axis, join, keys, levels, names, ignore_index, verify_integrity, copy, sort)
    355                     "only Series and DataFrame objs are valid".format(typ=type(obj))
    356                 )
--> 357                 raise TypeError(msg)
    359             # consolidate

TypeError: cannot concatenate object of type '<class 'scipy.sparse.csr.csr_matrix'>'; only Series and DataFrame objs are valid

You can think of Text column as

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I am trying to apply...

I hope you can help me to handle with it.


You have to convert X_train to a Dataframe before use concat

X = pd.concat([pd.DataFrame(X_train), y_train], axis=1)

Source: stackoverflow