I have a dataframe `d` and one of the columns is `price` (Numerical) having 109248 rows. I divided the data into two parts `d_train` and `d_test`. `d_train` has 73196 values and `d_test` has 36052 values. Now to normalize `d_train['price']` and `d_test['price']` i did something like this..

```
price_scalar = Normalizer()
X_train_price = price_scalar.fit_transform(d_train['price'].values.reshape(1, -1)
X_test_price = price_scalar.transform(d_test['price'].values.reshape(1, -1))

```

Now I'm having this issue

```
ValueError                                Traceback (most recent call last)
<ipython-input-20-ba623ca7bafa> in <module>()
3 X_train_price = price_scalar.fit_transform(X_train['price'].values.reshape(1, -1))
----> 4 X_test_price = price_scalar.transform(X_test['price'].values.reshape(1, -1))
/usr/local/lib/python3.7/dist-packages/sklearn/base.py in _check_n_features(self, X, reset)
394         if n_features != self.n_features_in_:
395             raise ValueError(
397                 f"is expecting {self.n_features_in_} features as input."
398             )
ValueError: X has 36052 features, but Normalizer is expecting 73196 features as input.

```

Doing change: `reshape(-1,1)` instead of `reshape(1,-1)` runs ok but makes all row values of `price` to 1.