# -*- coding:utf-8 -*-
import os
basedir = os.path.dirname(__file__)
[docs]def load_boston():
import pandas as pd
from sklearn import datasets
# boston_dataset = datasets.load_boston()
# data = pd.DataFrame(boston_dataset.data)
# data.columns = boston_dataset.feature_names
# data.insert(0, 'target', boston_dataset.target)
data = pd.read_csv(f'{basedir}/boston.csv.gz', compression='gzip')
return data
[docs]def load_heart_disease_uci():
import pandas as pd
data = pd.read_csv(f'{basedir}/heart-disease-uci.csv')
return data
[docs]def load_bank():
import pandas as pd
data = pd.read_csv(f'{basedir}/bank-uci.csv.gz')
return data
[docs]def load_bank_by_dask():
from dask import dataframe as dd
data = dd.read_csv(f'{basedir}/bank-uci.csv.gz', compression='gzip', blocksize=None)
return data
[docs]def load_adult():
import pandas as pd
# print(f'Base dir:{basedir}')
data = pd.read_csv(f'{basedir}/adult-uci.csv.gz', compression='gzip', header=None)
return data
[docs]def load_glass_uci():
import pandas as pd
# print(f'Base dir:{basedir}')
data = pd.read_csv(f'{basedir}/glass_uci.csv', header=None)
return data
[docs]def load_blood():
import pandas as pd
data = pd.read_csv(f'{basedir}/blood.csv')
return data
[docs]def load_telescope():
import pandas as pd
data = pd.read_csv(f'{basedir}/telescope.csv')
return data
[docs]def load_Bike_Sharing():
import pandas as pd
data = pd.read_csv(f'{basedir}/Bike_Sharing.csv')
return data
[docs]def load_movielens():
import pandas as pd
data = pd.read_csv(f'{basedir}/movielens_sample.txt')
return data