-
Notifications
You must be signed in to change notification settings - Fork 4
/
Copy pathLoad_Save_Data.py
30 lines (24 loc) · 1.02 KB
/
Load_Save_Data.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
import pandas as pd
data_dir = './DC_Data/'
def Load_Data():
'''
读取训练数据和测试数据,并返回
'''
data_train1 = pd.read_csv( data_dir + 'train_1.csv' )
data_train2 = pd.read_csv( data_dir + 'train_2.csv' )
data_train3 = pd.read_csv( data_dir + 'train_3.csv' )
data_train4 = pd.read_csv( data_dir + 'train_4.csv' )
data_train = pd.concat( [data_train1, data_train2, data_train3, data_train4] )
data_test1 = pd.read_csv( data_dir + 'test_1.csv' )
data_test2 = pd.read_csv( data_dir + 'test_2.csv' )
data_test3 = pd.read_csv( data_dir + 'test_3.csv' )
data_test4 = pd.read_csv( data_dir + 'test_4.csv' )
data_test = pd.concat( [data_test1, data_test2, data_test3, data_test4] )
return data_train, data_test
def Save_Data( data_save ):
'''
按要求保存数据
'''
data_save = pd.DataFrame( data_save )
data_save.columns = ['prediction']
data_save.to_csv( data_dir + 'power_predict.csv', float_format='%.7f', index_label=['id'] )