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(data.py) fit_transform method able to transform datatime columns to float values. (#68)

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* fit_transform method able to transform datatime columns to float values.
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Gian Pio Domiziani 2021-04-20 17:32:58 +02:00 committed by GitHub
parent 06045703bf
commit 9ff4ae0cb2
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1 changed files with 6 additions and 0 deletions
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flaml/data.py
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@ -8,6 +8,8 @@ from scipy.sparse import vstack, issparse
import pandas as pd
from .training_log import training_log_reader
from datetime import datetime
def load_openml_dataset(dataset_id, data_dir=None, random_state=0):
'''Load dataset from open ML.
@ -193,6 +195,9 @@ class DataTransformer:
cat_columns, num_columns = [], []
drop = False
for column in X.columns:
# sklearn\utils\validation.py needs int/float values
if X[column].dtype.name == 'datetime64[ns]':
X[column] = X[column].map(datetime.toordinal)
if X[column].dtype.name in ('object', 'category'):
if X[column].nunique() == 1 or X[column].nunique(
dropna=True) == n - X[column].isnull().sum():
@ -263,3 +268,4 @@ class DataTransformer:
X_num.columns = range(X_num.shape[1])
X[num_columns] = self.transformer.transform(X_num)
return X