def __init__(self, file_name=None): mexcel = Excel(file_name) self._raw_acode_data = mexcel.read() self.region_list = [re.sub('\s+','',item[1]) for item in self._raw_acode_data[1:]] self.admin_code_dict = OrderedDict([(re.sub('\s+','',item[1]),str(int(item[0]))) for item in self._raw_acode_data[1:]]) self.code_admin_dict = OrderedDict([(str(int(item[0])),re.sub('\s+','',item[1])) for item in self._raw_acode_data[1:]]) self._create_relationship()
# coding=UTF-8 import numpy as np import pandas as pd from libs.file.class_Excel import Excel # 0. 导入学生名单 STUDENT_FILE = 'E:\\temp\\lab\\student.xls' mexcel = Excel(STUDENT_FILE) student_list = mexcel.read() students = [item[1] for item in student_list] # 1. 生成学生数据和答案 out_path = 'E:\\temp\\lab\\' file_name = '_data.xls' rules1 = [1,2,4] rules3 = [3,7,9] result = [['student','model1','','','','model2','','','','model3','','','','model4','','','']] for student in students: mu, sigma = 0, np.random.randint(1,20)/10 miu = np.random.normal(mu, sigma, 1000) x1 = np.random.randint(1,100,1000) x2 = 5 + np.random.randint(1,5)*x1/10 + np.random.normal(mu, 0.1, 1000) x3 = np.random.randint(1,200,1000) pdata = pd.DataFrame({'x1':x1,'x2':x2,'x3':x3}) one_student_coefs = [student] for i in range(0,4): constant = np.random.randint(1,100,1) coefs = np.random.randint(0,10,3)
# coding=UTF-8 import pandas as pd import numpy as np from libs.database.class_cgssdatabase import CgssDatabase from libs.file.class_Excel import Excel filename = r"D:\data\student.xls" Path = r"D:\data\labdata" mexcel = Excel(filename) mdata = mexcel.read() mdata = [item[1] for item in mdata] cgdb = CgssDatabase(year=2013) pdata = cgdb.variables( variables=[ ["a2", False], ["a3a", False], ["a4", False], ["a7a", False], ["a8a", False], ["a8b", False], ["a10", False], ["a18", False], ["a59j", False], ["a69", False], ["a89b", False], ] ) pdata.columns = [ "A10政治面貌",
result = [] journals = json.load(open(r'E:\gitrobot\files\publication\ssci_geography_json.txt')) for journal in journals: if journal[1] not in impact_factor_journals: result.append([journal[0].upper(),journal[1],None]) else: result.append([journal[0].upper(),journal[1],impact_factor_journals[journal[1]]]) # 2. output for record in result: print(record) outfile = r'd:\down\tmp_journal.xlsx' moutexcel = Excel(outfile) moutexcel.new().append(result, 'sheet1') moutexcel.close()''' mongo = MongoDB() mongo.connect('publication','WesternJournal') filename = r'd:\down\journals.xlsx' mexcel = Excel(filename) mdata = mexcel.read(sheet=4) result = [] for item in mdata[1:]: if item[2] == '': result.append({'journal':item[0],'SSIN':item[1],'IF':None}) else: result.append({'journal':item[0],'SSIN':item[1],'IF':item[2]}) #for j in result: # mongo.collection.insert_one(j)