import pandas as pd
csv_data = pd.read_csv('C:/Users/hyq68/Desktop/DATAA.csv', encoding ='ANSI')'''
#以下是转换数据格式
UN_Code = []
for row in csv_data.UN_Code:
UN_Code.append(str(row))
for i in range(len(UN_Code)):
if len(UN_Code[i]) == 1:
UN_Code[i] = ('00'+UN_Code[i])
if len(UN_Code[i]) == 2:
UN_Code[i] = ('0'+UN_Code[i])
UN_Code = pd.DataFrame(UN_Code)
'''
UN_Code.to_csv('C:/Users/hyq68/Desktop/DATAA.csv',encoding='utf-8')###数据清洗模板import pandas as pd
import numpy as np
#读取文件
data = pd.read_csv('C:/Users/hyq68/Desktop/population.csv',encoding ='ANSI')
population =[]#增添数据for i inrange(len(data)):for m inrange(2000,2016):
population.append(data['Country Code'][i])for i inrange(len(data)):for m inrange(2000,2016):
population.append(str(m))for i inrange(len(data)):for m inrange(2000,2016):
population.append(data[str(m)][i])#数据变形
Country_Code = population[0:int(len(population)/3)]
Year = population[int((len(population)/3)):int((len(population)/3)*2)]
Population = population[int(((len(population)/3)*2)):len(population)]
Data =[Country_Code,Year,Population]
Data = np.transpose(Data)#写入数据
population = pd.DataFrame(columns =['Country_Code','Year','Population'], data = Data)
population.to_csv('C:/Users/hyq68/Desktop/population_new.csv',encoding ='utf-8')#-----------------------缺失值处理:平均值---------------------------#import numpy as np
import pandas as pd
data = pd.read_csv('C:/Users/hyq68/Desktop/data_raw.csv', encoding ='ANSI')
World_Average = pd.read_csv('C:/Users/hyq68/Desktop/World_Average.csv', encoding ='utf-8')
WA_ME = World_Average['Military_Expenditure (% of GDP)']#将数据按照国家分组
Military_Expenditure = data['Military_Expenditure (% of GDP)']
country_Military_Expenditure =[]for m inrange(int(len(data)/(16))):
country_Military_Expenditure.append([])for n inrange(16):
country_Military_Expenditure[m].append(Military_Expenditure[m*16+n])#计算平均值
avg =[]for m in country_Military_Expenditure:
sum_ =0
count_ =0
avg_ =0for n in m:if n !='..':
n =float(n)
sum_ += n
count_ +=1if count_ !=0:
avg_ = sum_/count_
avg.append(avg_)#用平均值替换..for m in country_Military_Expenditure:for n in m:if n =="..":
country_Military_Expenditure[country_Military_Expenditure.index(m)][m.index('..')]= avg[country_Military_Expenditure.index(m)]#解决0问题,解决类型问题for m in country_Military_Expenditure:for n in m:if n ==0:
country_Military_Expenditure[country_Military_Expenditure.index(m)][m.index(0)]= WA_ME[m.index(0)]#拉平向量
result =[]for m in country_Military_Expenditure:for n in m:
result.append(float(n))#写入数据
data_mature = pd.read_csv('C:/Users/hyq68/Desktop/data_mature.csv', encoding ='utf-8')
data_mature['Military Expenditure (% of GDP)']= result
data_mature.to_csv('C:/Users/hyq68/Desktop/data_mature.csv',encoding ='utf-8')