Preprocessing in scikit learn - single sample - Depreciation warning
Solution 1:
Just listen to what the warning is telling you:
Reshape your data either X.reshape(-1, 1) if your data has a single feature/column and X.reshape(1, -1) if it contains a single sample.
For your example type(if you have more than one feature/column):
temp = temp.reshape(1,-1)
For one feature/column:
temp = temp.reshape(-1,1)
Solution 2:
Well, it actually looks like the warning is telling you what to do.
As part of sklearn.pipeline
stages' uniform interfaces, as a rule of thumb:
when you see
X
, it should be annp.array
with two dimensionswhen you see
y
, it should be annp.array
with a single dimension.
Here, therefore, you should consider the following:
temp = [1,2,3,4,5,5,6,....................,7]
# This makes it into a 2d array
temp = np.array(temp).reshape((len(temp), 1))
temp = scaler.transform(temp)
Solution 3:
This might help
temp = ([[1,2,3,4,5,6,.....,7]])
Solution 4:
.values.reshape(-1,1)
will be accepted without alerts/warnings
.reshape(-1,1)
will be accepted, but with deprecation war