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merge_samples.py
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# -*- coding:utf-8 *-*
# @Time : 2017/11/23 0023 21:29
# @Author : LQY
# @File : merge_samples.py
# @Software: PyCharm Community Edition
import os
import pandas as pd
import xgboost
import numpy as np
from pandas import DataFrame,Series
def merge_featue(path,labelpath,resultpath):
#path = 'E:\\JD\\data\\generate_feature_8'
paths=os.listdir(path)
print paths
a = pd.read_csv(labelpath, header=0)#lable文件
print a.index
for p in paths:
b=pd.read_csv(path+'\\'+p,header=0,delimiter=',',index_col=['shop_id'])
b.fillna(0)
#print b.index
a =pd.merge(a,b,left_on='shop_id',right_index=True,how='left')
a.to_csv(resultpath,encoding = "utf-8",index=None)
# merge_featue('E:\\JD\\data\\generate_feature_8','E:\\JD\\august.csv','E:\\JD\\data\\august_samples.csv')
# merge_featue('E:\\JD\\data\\generate_feature_9','E:\\JD\\september.csv','E:\\JD\\data\\september_samples.csv')
# merge_featue('E:\\JD\\data\\generate_feature_10','E:\\JD\\october.csv','E:\\JD\\data\\october_samples.csv')
# merge_featue('E:\\JD\\data\\generate_feature_11','E:\\JD\\november.csv','E:\\JD\\data\\november_samples.csv')
# merge_featue('E:\\JD\\data\\generate_feature_12','E:\\JD\\december.csv','E:\\JD\\data\\december_samples.csv')
# merge_featue('E:\\JD\\data\\generate_feature_1','E:\\JD\\january.csv','E:\\JD\\data\\january_samples.csv')
#merge_featue('E:\\JD\\data\\generate_feature_1','E:\\JD\\january.csv','E:\\JD\\data\\january_samples.csv')
#merge_featue('E:\\JD\\data\\generate_feature_4','E:\\JD\\Sales_Forecast.csv','E:\\JD\\data\\april_samples.csv')
#
#合并模型
def concact_feature():
# j = pd.read_csv('E:\wash_data\generate_feature_7\\for_7model_1107.csv', header=0, delimiter=',')
# i = pd.read_csv('E:\wash_data\generate_feature_7\\for_7model_1114.csv', header=0, delimiter=',')
# h=pd.read_csv('E:\wash_data\generate_feature_7\\for_7model_1121.csv',header=0, delimiter=',')
# a=pd.read_csv('E:\\JD\\data\\august_samples.csv',header=0, delimiter=',')
# b=pd.read_csv('E:\\JD\\data\\september_samples.csv',header=0, delimiter=',')
c=pd.read_csv('E:\\JD\\data\\october_samples.csv',header=0, delimiter=',')
d = pd.read_csv('E:\\JD\\data\\november_samples.csv', header=0, delimiter=',')
e = pd.read_csv('E:\\JD\\data\\december_samples.csv', header=0, delimiter=',')
f = pd.read_csv('E:\\JD\\data\\january_samples.csv', header=0, delimiter=',')
#g = pd.read_csv('E:\wash_data\generate_feature_28\\for_28model_0117_test.csv', header=0, delimiter=',')
# #d=pd.read_csv('E:\wash_data\\after_merge_feature\\7model\\for_7model_28.csv',header=0, delimiter=',')
list=[c,d,e,f,]
#list = [f, g]
# a = pd.read_csv('E:\wash_data\\after_merge_feature\\14model\\for_14model_14.csv', header=0, delimiter=',')
# b = pd.read_csv('E:\wash_data\\after_merge_feature\\14model\\for_14model_21.csv', header=0, delimiter=',')
# # c = pd.read_csv('E:\wash_data\\after_merge_feature\\14model\\for_14model_28.csv', header=0, delimiter=',')
# list=[a,b]
# a = pd.read_csv('E:\wash_data\\after_merge_feature\\21model\\for_21model_21.csv', header=0, delimiter=',')
# b = pd.read_csv('E:\wash_data\\after_merge_feature\\21model\\for_21model_28.csv', header=0, delimiter=',')
# list = [a, b]
result=pd.concat(list)
result.to_csv('E:\\JD\\data\\samples_all.csv',header=True,index=None)
#concact_feature()