def read_from_dir(cls, path, outexcel=False, outpath=None): files = os.listdir(path) if outexcel: moutexcel = Excel(outpath) moutexcel.new().append([[item, item] for item in files], "sheet1") moutexcel.close() else: return files
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 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",
# 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)
if re.match('^(-)?\d+((\.|.)\d+)?$',new_item) is not None: new_item = re.sub('.','.',new_item) new_row.append(float(new_item)) else: all = False new_row.append(item) return new_row,all if __name__ == '__main__': filename = r'E:\data\procedure\Process\reduction\data\admincode\2003.xls' acodefile = AdminCodeFile(filename) filename = r'E:\data\procedure\Process\reduction\data\2003_prefecture\3_3_按三次业人员就业状况_地级市_2003.xls' mexcel = WinExcel(filename) mdata = mexcel.read() reduction = CitydataReduction(mdata,acodefile) reduction.reduction() ndata = reduction.second_data print(reduction.second_data) outfile = r'd:\data\demo.xlsx' moutexcel = Excel(outfile) moutexcel.new().append(ndata, 'mysheet') moutexcel.close()
source_file = os.path.join(current_import_dir, file) # 目标文件 file_name = re.split("\.", file)[0] new_file_name = "".join([file_name, "_first_step.xlsx"]) new_delete_name = "".join([file_name, "_deleted.xlsx"]) target_file = os.path.join(current_export_path, new_file_name) delete_file = os.path.join(current_export_path, new_delete_name) # 如果目标文件存在,那么跳过 if os.path.exists(target_file): print("Here it is! ", file) continue # 从excel文件读入数据,构建CitydataReduction对象 # mexcel = WinExcel(source_file) mexcel = Excel(source_file) sdata = mexcel.read() if abnormal: ndata = [] first_part = [] second_part = [] for row in sdata: if set(row) == {None}: if len(first_part) < 1: continue else: ndata.extend(first_part) ndata.extend(second_part) first_part = [] second_part = [] first_part.append(row[0:region_col])
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)