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from lightgbm import LGBMRegressor

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

df_train = pd.read_csv('../input/30-days-of-ml/train.csv')
df_test = pd.read_csv('../input/30-days-of-ml/test.csv')
submission = pd.read_csv('../input/30-days-of-ml/sample_submission.csv')

df_train

X_train = df_train.copy().drop('target', axis=1)
y_train = df_train['target'].copy()

df_cols = [col for col in X_train.columns if 'cat' in col]

lgbm_model = LGBMRegressor()
lgbm_model.fit(X_train, y_train)

y_pred = lgbm_model.predict(df_test)
y_pred