def GetNetProfitGrowth(stockcode):
file=os.getcwd()+'\\market_data\\'+'业绩预测.csv'
#print(file)
df=pd.read_csv(file,index_col=0)
df['growth']=df['range'].str.extract('(\d+|-\d+)',expand=True).astype('float')
#print(df)
if int(stockcode) in list(df.index.values):
growth=df.at[int(stockcode),'growth']
if type(growth)==np.float64:
#print(growth/100)
return growth/100
else:
#print(growth[0]/100)
return growth[0]/100
else:
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'incomestatements.csv'
df=pd.read_csv(file,index_col=0)
#print(df)
TermType={'1-3月':1,'1-6月':2,'1-9月':3,'度':4}
i=len(df.columns)-1
CurrentTerm=df.columns[i]
LastTerm=str(int(CurrentTerm[:4])-1)+CurrentTerm[4:]
if LastTerm not in df.columns:
LastTerm=str(int(CurrentTerm[:4])-1)+'年度'
if ssa.get_stock_type(stockcode)=='金融类': #金融类与非金融类股票的净利润项目名称不同，故要作区别对待。
NetProfitName='（一）归属于母公司所有者的净利润'#'五、净利润'
else:
NetProfitName='归属于母公司所有者的净利润'#'四、净利润'
CurrentProfit=float(df.at[NetProfitName,CurrentTerm].replace(',',''))/TermType[CurrentTerm[5:]]*4
#print(CurrentTerm,CurrentProfit)
LastProfit=float(df.at[NetProfitName,LastTerm].replace(',',''))/TermType[LastTerm[5:]]*4
#print(LastTerm,LastProfit)
#print(CurrentProfit/LastProfit-1)
return CurrentProfit/LastProfit-1
def GetInventoryRate(stockcode): #获取存货比率
stockname=ssa.get_stockname(stockcode)
file1=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'balancesheet.csv'
file2=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'incomestatements.csv'
df1=pd.read_csv(file1,index_col=0)
df2=pd.read_csv(file2,index_col=0)
if '现金及存放同业款项' in df1.index.values: #若是金融企业，没有存货，返回none
return None,None
s_ch=df1.loc['存货'].str.replace(',','').fillna('0').astype(float)/100000000
s_yysr=df2.loc['一、营业收入'].str.replace(',','').fillna('0').astype(float)/100000000 #获取营业收入
s_yysr_new_index=[]
for index in s_yysr.index.values: #将季度营业收入转变为年度营业收入
if '1-3月' in index:
s_yysr[index]=s_yysr[index]*4
s_yysr_new_index.append(index[0:4]+'-03-31')
if '1-6月' in index:
s_yysr[index]=s_yysr[index]/2*4
s_yysr_new_index.append(index[0:4]+'-06-30')
if '1-9月' in index:
s_yysr[index]=s_yysr[index]/3*4
s_yysr_new_index.append(index[0:4]+'-09-30')
if '年度' in index:
s_yysr_new_index.append(index[0:4]+'-12-31')
s_yysr=pd.Series(s_yysr.values,index=s_yysr_new_index)
InventoryRate=s_ch/s_yysr*100
labels=list(InventoryRate.index.values)
data=list(InventoryRate.values)
#print(labels,data)
return labels,data
def GET(self,stockcode):
labels,data1,data2=sn.GetAssets(stockcode)
title=ssa.get_stockname(stockcode)+'（%s）'%stockcode+'-资产负债情况'
legend1='总资产'
legend2='净资产'
yAxesLabel='（亿元）'
render=web.template.render('templates')
return render.showassets(title,labels,data1,data2,legend1,legend2,yAxesLabel)
def GET(self,stockcode):
labels,data1,data2=sn.GetROE(stockcode)
title=ssa.get_stockname(stockcode)+'（%s）'%stockcode+'-资产收益率'
legend1='总资产收益率'
legend2='净资产收益率'
yAxesLabel='（%）'
render=web.template.render('templates')
return render.ShowROE(title,labels,data1,data2,legend1,legend2,yAxesLabel)
def GET(self,stockcode):
labels,data1,data2=sn.GetIncomeProfit(stockcode)
title=ssa.get_stockname(stockcode)+'（%s）'%stockcode+'-营收情况'
legend1='营业收入'
legend2='净利润'
yAxesLabel='（亿元）'
render=web.template.render('templates')
return render.ShowIncomeProfit(title,labels,data1,data2,legend1,legend2,yAxesLabel)
def GET(self,stockcode):
labels,data=sn.GetReceivablesRate(stockcode)
title=ssa.get_stockname(stockcode)+'（%s）'%stockcode+'-应收账款比率'
#print(labels,data)
#legend=''
yAxesLabel='（%）'
render=web.template.render('templates')
return render.ShowReceivablesRate(title,labels,data,yAxesLabel)
def GET(self,stockcode):
labels,data1,data2=sn.GetPosition(stockcode)
title=ssa.get_stockname(stockcode)+'（%s）'%stockcode+'-供应链地位'
legend1='经营性资产'
legend2='经营性负债'
yAxesLabel='（亿元）'
render=web.template.render('templates')
return render.ShowPosition(title,labels,data1,data2,legend1,legend2,yAxesLabel)
def GET(self,stockcode):
labels,data=sn.GetAssetsSource(stockcode)
title=ssa.get_stockname(stockcode)+'（%s）'%stockcode+'-资产来源'
print(labels,data)
#legend=''
yAxesLabel='（亿元）'
render=web.template.render('templates')
return render.ShowAssetsSource(title,labels,data,yAxesLabel)
def GetAssetsSource(stockcode): #获取最近一期的资产来源
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'balancesheet.csv'
print (file)
df=pd.read_csv(file,index_col=0)
if '现金及存放同业款项' in df.index.values: #对金融类和非金融类要作区分
df2=df.loc[['向中央银行借款',
'同业及其他金融机构存放款项',
'短期借款',
'拆入资金',
'交易性金融负债',
'衍生金融负债',
'卖出回购金融资产款',
'吸收存款',
'代理买卖证券款',
'代理承销证券款',
'应付帐款',
'应付票据',
'预收款项',
'预收保费',
'应付手续费及佣金',
'应付分保帐款',
'应付职工薪酬',
'应交税费',
'应付利息',
'代理业务负债',
'预计负债',
'应付赔付款',
'应付保单红利',
'保户储金及投资款',
'未到期责任准备金',
'未决赔款准备金',
'寿险责任准备金',
'长期健康险责任准备金',
'长期借款',
'应付债券',
'独立帐户负债',
'递延所得税负债',
'其他负债',
'实收资本（或股本）',
'资本公积',
'减：库存股',
'盈余公积',
'一般风险准备',
'未分配利润',
'少数股东权益',
'外币报表折算差额',
'非正常经营项目收益调整'], df.columns[-1]].str.replace(',','').fillna('0').astype(float)/100000000
else:
df2=df.loc[['短期借款','交易性金融负债','应付票据','应付账款','预收款项',
'应付职工薪酬','应交税费','应付利息','应付股利','其他应付款',
'应付关联公司款','一年内到期的非流动负债','其他流动负债',
'长期借款','应付债券','长期应付款','专项应付款','预计负债',
'递延所得税负债','其他非流动负债','实收资本(或股本)','资本公积','盈余公积',
'未分配利润','少数股东权益','外币报表折算价差','非正常经营项目收益调整'],
df.columns[-1]].str.replace(',','').fillna('0').astype(float)/100000000
return list(df2.index.values),list(df2.values)
def GET(self,stockcode):
labels,data1,data2,data3=sn.GetNetCashFlowSum(stockcode)
title=ssa.get_stockname(stockcode)+'（%s）'%stockcode+'-资产收益率'
legend1='经营性现金净额'
legend2='筹资性现金净额'
legend3='投资性现金净额'
yAxesLabel='（亿元）'
render=web.template.render('templates')
return render.ShowNetCashFlowSum(title,labels,data1,data2,data3,legend1,legend2,legend3,yAxesLabel)
def GET(self,stockcode):
labels,data=sn.GetInventoryRate(stockcode)
title=ssa.get_stockname(stockcode)+'（%s）'%stockcode+'-存货比率'
#print(labels,data)
#legend=''
yAxesLabel='（%）'
render=web.template.render('templates')
if labels==None:
return '金融类企业，无法计算存货比率!'
else:
return render.ShowInventoryRate(title,labels,data,yAxesLabel)
def GetTradePosition(stockcode):
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'balancesheet.csv'
df0=pd.read_csv(file,index_col=0).fillna('0')
df1=df0.loc[['应收票据','应收账款','预付款项','应付票据','应付账款','预收款项']].applymap(ssa.str_to_float)
#print(df1)
s_jyxzc=sum(df1[df1.columns[-1]][['应收票据','应收账款','预付款项']])#经营性资产
#print(s_jyxzc)
s_jyxfz=sum(df1[df1.columns[-1]][['应付票据','应付账款','预收款项']])#经营性负债
#print (s_jyxfz)
return s_jyxfz/s_jyxzc
def GetNetInvestmentCashSum(stockcode):
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'cashflow.csv'
df=pd.read_csv(file,index_col=0).fillna('0')
sr=df.loc['投资活动产生的现金流量净额']
ls=[]
for i in range(len(sr.index)):
if i>0 and sr.index[i][5:]!='1-3月' and sr.index[i-1][5:]!='度':
ls.append(float(sr[sr.index[i]].replace(',',''))-float(sr[sr.index[i-1]].replace(',','')))
else:
ls.append(float(sr[sr.index[i]].replace(',','')))
return sum(ls)
def GetAssetsStructure(stockcode): #获取最近一期的资产结构
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'balancesheet.csv'
print (file)
df=pd.read_csv(file,index_col=0)
if '现金及存放同业款项' in df.index.values: #对金融类和非金融类要作区分
df2=df.loc[['现金及存放同业款项',
'货币资金',
'存放中央银行款项',
'结算备付金',
'贵金属',
'拆出资金',
'交易性金融资产',
'衍生金融资产',
'买入返售金融资产',
'应收利息',
'应收保费',
'应收代位追偿款',
'应收分保帐款',
'应收分保未到期责任准备金',
'应收分保未决赔款准备金',
'应收分保寿险责任准备金',
'应收分保长期健康险责任准备金',
'保户质押贷款',
'定期存款',
'发放贷款及垫款',
'存出保证金',
'代理业务资产',
'应收款项',
'预付款项',
'可供出售金融资产',
'持有至到期投资',
'长期股权投资',
'存出资本保证金',
'投资性房地产',
'存货',
'固定资产',
'在建工程',
'无形资产',
'长期待摊费用',
'固定资产清理',
'独立帐户资产',
'递延所得税资产',
'其他资产'], df.columns[-1]].str.replace(',','').fillna('0').astype(float)/100000000
else:
df2=df.loc[['货币资金','交易性金融资产','应收票据','应收账款','预付款项',
'其他应收款','应收关联公司款','应收利息','应收股利','存货',
'一年内到期的非流动资产','其他流动资产','可供出售金融资产',
'长期应收款','长期股权投资','投资性房地产','固定资产','在建工程',
'工程物资','固定资产清理','生产性生物资产','无形资产','开发支出',
'商誉','长期待摊费用','递延所得税资产','其他非流动资产'],
df.columns[-1]].str.replace(',','').fillna('0').astype(float)/100000000
return list(df2.index.values),list(df2.values)
def GetAssets(stockcode): #获取历年总资产与净资产
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'balancesheet.csv'
#print (file)
df=pd.read_csv(file,index_col=0)
if '现金及存放同业款项' in df.index.values: #略有文字不一致，导致对金融类和非金融类要作区分
s_zzc=df.loc['资产总计'].str.replace(',','').fillna('0').astype(float)/100000000#总资产
s_jzc=df.loc['所有者权益（或股东权益）合计'].str.replace(',','').fillna('0').astype(float)/100000000#净资产
else:
s_zzc=df.loc['资产总计'].str.replace(',','').fillna('0').astype(float)/100000000#总资产
s_jzc=df.loc['所有者权益(或股东权益)合计'].str.replace(',','').fillna('0').astype(float)/100000000#净资产
l_index=list(s_zzc.index.values) #报告期列表
l_zzc=list(s_zzc.values) #总资产列表
l_jzc=list(s_jzc.values) #净资产列表
return l_index,l_zzc,l_jzc
def GetIncomeGrowth(stockcode):
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'incomestatements.csv'
df=pd.read_csv(file,index_col=0)
#print(df)
TermType={'1-3月':1,'1-6月':2,'1-9月':3,'度':4}
i=len(df.columns)-1
CurrentTerm=df.columns[i]
LastTerm=str(int(CurrentTerm[:4])-1)+CurrentTerm[4:]
if LastTerm not in df.columns:
LastTerm=str(int(CurrentTerm[:4])-1)+'年度'
IncomeName='一、营业收入'
CurrentIncome=float(df.at[IncomeName,CurrentTerm].replace(',',''))/TermType[CurrentTerm[5:]]*4
#print(CurrentTerm,CurrentProfit)
LastIncome=float(df.at[IncomeName,LastTerm].replace(',',''))/TermType[LastTerm[5:]]*4
return CurrentIncome/LastIncome-1
def GetPosition(stockcode): #获取供应链地位
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'balancesheet.csv'
print (file)
df=pd.read_csv(file,index_col=0)
if '现金及存放同业款项' in df.index.values: #对金融类和非金融类要作区分
df2=df.loc[['吸收存款','发放贷款及垫款']].fillna('0').applymap(ssa.str_to_float)/100000000
s_jyxzc=df2.loc['发放贷款及垫款'] #经营性资产
s_jyxfz=df2.loc['吸收存款'] #经营性负债
else:
df2=df.loc[['应收票据','应收账款','预付款项',
'应付票据','应付账款','预收款项']].fillna('0').applymap(ssa.str_to_float)/100000000
s_jyxzc=df2.loc['应收票据']+df2.loc['应收账款']+df2.loc['预付款项']#经营性资产
s_jyxfz=df2.loc['应付票据']+df2.loc['应付账款']+df2.loc['预收款项']#经营性负债
labels=list(s_jyxzc.index.values) #报告期
data1=list(s_jyxzc.values) #经营性资产
data2=list(s_jyxfz.values) #经营性负债
return labels,data1,data2
def GetNetProfit(stockcode):
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'incomestatements.csv'
df=pd.read_csv(file,index_col=0)
#print(df)
i=len(df.columns)-1
while i>=0:
if '年度' in df.columns[i]:
LastYear=df.columns[i]
#print(LastYear)
break
i-=1
if ssa.get_stock_type(stockcode)=='金融类': #金融类与非金融类股票的净利润项目名称不同，故要作区别对待。
NetProfitName='（一）归属于母公司所有者的净利润'#'五、净利润'
else:
NetProfitName='归属于母公司所有者的净利润'#'四、净利润'
#print(df.loc[NetProfitName])
NetProfit=float(df.at[NetProfitName,LastYear].replace(',',''))
return NetProfit
def GetROE(stockcode): #获取资产收益率
stockname=ssa.get_stockname(stockcode)
file1=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'balancesheet.csv'
file2=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'incomestatements.csv'
df1=pd.read_csv(file1,index_col=0)
df2=pd.read_csv(file2,index_col=0)
if '现金及存放同业款项' in df1.index.values: #略有文字不一致，导致对金融类和非金融类要作区分
s_zzc=df1.loc['资产总计'].str.replace(',','').fillna('0').astype(float)/100000000#总资产
s_jzc=df1.loc['所有者权益（或股东权益）合计'].str.replace(',','').fillna('0').astype(float)/100000000#净资产
else:
s_zzc=df1.loc['资产总计'].str.replace(',','').fillna('0').astype(float)/100000000#总资产
s_jzc=df1.loc['所有者权益(或股东权益)合计'].str.replace(',','').fillna('0').astype(float)/100000000#净资产
if '五、净利润' in df2.index.values: #金融企业与非金融企业，净利润的项目序号不一样，应区别获取
s_jlr=df2.loc['五、净利润'].str.replace(',','').fillna('0').astype(float)/100000000
else:
s_jlr=df2.loc['四、净利润'].str.replace(',','').fillna('0').astype(float)/100000000
s_jlr_new_index=[]
for index in s_jlr.index.values: #将季度净利润转变为年度净利润
if '1-3月' in index:
s_jlr[index]=s_jlr[index]*4
s_jlr_new_index.append(index[0:4]+'-03-31')
if '1-6月' in index:
s_jlr[index]=s_jlr[index]/2*4
s_jlr_new_index.append(index[0:4]+'-06-30')
if '1-9月' in index:
s_jlr[index]=s_jlr[index]/3*4
s_jlr_new_index.append(index[0:4]+'-09-30')
if '年度' in index:
s_jlr_new_index.append(index[0:4]+'-12-31')
s_jlr=pd.Series(s_jlr.values,index=s_jlr_new_index)
ROA=s_jlr/s_zzc*100 #总资产收益率
ROE=s_jlr/s_jzc*100 #净资产收益率
labels=list(ROA.index.values)
data1=list(ROA.values)
data2=list(ROE.values)
return labels,data1,data2
def GetTotalLevel(stockcode):
try:
stockname=ssa.get_stockname(stockcode)
#print(stockcode,stockname)
StockPrice=GetStockPrice(stockcode)
#print('股价：',StockPrice)
shares=GetShares(stockcode)
#print('总股本：',shares)
NetProfit=GetNetProfit(stockcode)
EPS=NetProfit/shares
#print('每股收益：',EPS)
NetProfitGrowth=GetNetProfitGrowth(stockcode)
#print('净利润增长率：',NetProfitGrowth*100)
IncomeGrowth=GetIncomeGrowth(stockcode)
#print('营业收入增长率：',IncomeGrowth*100)
InterValue=iv(NetProfitGrowth,EPS,0.07,15)
#print('估值：',InterValue)
#计算安全边际
SecurityLevel=graduation(InterValue/StockPrice*100)
#print('股价安全度：',SecurityLevel)
#计算成长性
GrowthLevel=graduation(NetProfitGrowth*100)
#print('利润成长：',GrowthLevel)
#计算营业能力
IncomeLevel=graduation(IncomeGrowth*100)
#print('营收增长：',IncomeLevel)
#计算现金能力
NetIncomeCashSum=GetNetIncomeCashSum(stockcode)
#print('累计经营现金净额：',NetIncomeCashSum)
NetInvestmentCashSum=GetNetInvestmentCashSum(stockcode)
#print('累计投资现金净额：',NetInvestmentCashSum)
CashLevel=graduation(NetIncomeCashSum/abs(NetInvestmentCashSum)*100)
#print('运营现金：',CashLevel)
#计算供应链地位
TradePosition=GetTradePosition(stockcode)
TradePositionLevel=graduation(TradePosition*100)
#print('供应链地位：',TradePositionLevel)
return stockcode,stockname,SecurityLevel,GrowthLevel,IncomeLevel,CashLevel,TradePositionLevel
except:
return None,None,None,None,None,None,None
def GetIncomeProfit(stockcode): #获取营业状况
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'incomestatements.csv'
df=pd.read_csv(file,index_col=0)
s_yysr=df.loc['一、营业收入'].str.replace(',','').fillna('0').astype(float)/100000000 #获取营业收入
s_yysr_new_index=[]
for index in s_yysr.index.values: #将季度营业收入转变为年度营业收入
if '1-3月' in index:
s_yysr[index]=s_yysr[index]*4
s_yysr_new_index.append(index[0:4]+'-03-31')
if '1-6月' in index:
s_yysr[index]=s_yysr[index]/2*4
s_yysr_new_index.append(index[0:4]+'-06-30')
if '1-9月' in index:
s_yysr[index]=s_yysr[index]/3*4
s_yysr_new_index.append(index[0:4]+'-09-30')
if '年度' in index:
s_yysr_new_index.append(index[0:4]+'-12-31')
s_yysr=pd.Series(s_yysr.values,index=s_yysr_new_index)
if '五、净利润' in df.index.values: #金融企业与非金融企业，净利润的项目序号不一样，应区别获取
s_jlr=df.loc['五、净利润'].str.replace(',','').fillna('0').astype(float)/100000000
else:
s_jlr=df.loc['四、净利润'].str.replace(',','').fillna('0').astype(float)/100000000
for index in s_jlr.index.values: #将季度营业收入转变为年度营业收入
if '1-3月' in index:
s_jlr[index]=s_jlr[index]*4
if '1-6月' in index:
s_jlr[index]=s_jlr[index]/2*4
if '1-9月' in index:
s_jlr[index]=s_jlr[index]/3*4
labels=list(s_yysr.index.values)
data1=list(s_yysr.values)
data2=list(s_jlr.values)
return labels,data1,data2
def GetReceivablesRate(stockcode): #获取应收账款比率
stockname=ssa.get_stockname(stockcode)
file1=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'balancesheet.csv'
file2=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'incomestatements.csv'
df1=pd.read_csv(file1,index_col=0)
df2=pd.read_csv(file2,index_col=0)
if '现金及存放同业款项' in df1.index.values: #对金融类和非金融类要作区分,计算应收账款
df3=df1.loc[['应收利息','应收保费','应收代位追偿款','应收分保帐款','应收分保未到期责任准备金','应收分保未决赔款准备金',
'应收分保寿险责任准备金','应收分保长期健康险责任准备金','应收款项']].fillna('0').applymap(ssa.str_to_float)/100000000
s_yszk=df3.loc['应收利息']+df3.loc['应收保费']+df3.loc['应收代位追偿款']+df3.loc['应收分保帐款']+ \
df3.loc['应收分保未到期责任准备金']+df3.loc['应收分保未决赔款准备金']+df3.loc['应收分保寿险责任准备金']+ \
df3.loc['应收分保长期健康险责任准备金']+df3.loc['应收款项']
else:
s_yszk=df1.loc['应收账款'].str.replace(',','').fillna('0').astype(float)/100000000
s_yysr=df2.loc['一、营业收入'].str.replace(',','').fillna('0').astype(float)/100000000 #获取营业收入
s_yysr_new_index=[]
for index in s_yysr.index.values: #将季度营业收入转变为年度营业收入
if '1-3月' in index:
s_yysr[index]=s_yysr[index]*4
s_yysr_new_index.append(index[0:4]+'-03-31')
if '1-6月' in index:
s_yysr[index]=s_yysr[index]/2*4
s_yysr_new_index.append(index[0:4]+'-06-30')
if '1-9月' in index:
s_yysr[index]=s_yysr[index]/3*4
s_yysr_new_index.append(index[0:4]+'-09-30')
if '年度' in index:
s_yysr_new_index.append(index[0:4]+'-12-31')
s_yysr=pd.Series(s_yysr.values,index=s_yysr_new_index)
ReceivableRate=s_yszk/s_yysr*100
labels=list(ReceivableRate.index.values)
data=list(ReceivableRate.values)
#print(labels,data)
return labels,data
#print('累计投资现金净额：',NetInvestmentCashSum)
CashLevel=graduation(NetIncomeCashSum/abs(NetInvestmentCashSum)*100)
#print('运营现金：',CashLevel)
#计算供应链地位
TradePosition=GetTradePosition(stockcode)
TradePositionLevel=graduation(TradePosition*100)
#print('供应链地位：',TradePositionLevel)
return stockcode,stockname,SecurityLevel,GrowthLevel,IncomeLevel,CashLevel,TradePositionLevel
except:
return None,None,None,None,None,None,None
if __name__=='__main__':
stockcode=input('请输入股票代码：')#'000858'
stockname=ssa.get_stockname(stockcode)
print(stockcode,stockname)
StockPrice=GetStockPrice(stockcode)
label0='股价：'+str('{:.2f}'.format(StockPrice))+'元'
print(label0)
shares=GetShares(stockcode)
label1='总股本：'+str('{:.2f}'.format(shares/100000000))+'亿'
print(label1)
NetProfit=GetNetProfit(stockcode)
EPS=NetProfit/shares
label2='每股收益：'+str('{:.2f}'.format(EPS))+'元'
print(label2)
NetProfitGrowth=GetNetProfitGrowth(stockcode)
label3='净利润增长率：'+str('{:.2f}'.format(NetProfitGrowth*100))+'%'
print(label3)
IncomeGrowth=GetIncomeGrowth(stockcode)
def GetNetCashFlowSum(stockcode): #获取累计经营、投资和筹资累计现金流
stockname=ssa.get_stockname(stockcode)
file=os.getcwd()+'\\stock_financial\\'+stockcode+stockname+'cashflow.csv'
df6=pd.read_csv(file,index_col=0).fillna('0').applymap(ssa.str_to_float) #之所以是df6,是因为从ssa中复制的代码，为尽量偷懒，故延用
s_tzxjje=df6.loc['投资活动产生的现金流量净额']/100000000#投资现金净额
#以下换算成季度数据
s_tzxjje_value=[]
s_tzxjje_index=[]
s_tzxjje_lj_value=[]#计算累计额
s_tzxjje_lj_index=[]
for i in range(len(s_tzxjje)):
if i>0 and '年度' in s_tzxjje.index[i] and '1-9月' in s_tzxjje.index[i-1] and s_tzxjje.index[i][:5]==s_tzxjje.index[i-1][:5]:
s_tzxjje_value.append(s_tzxjje[i]-s_tzxjje[i-1])
s_tzxjje_index.append(s_tzxjje.index[i][:4]+'-12-31')
elif '1-9月' in s_tzxjje.index[i] and '1-6月' in s_tzxjje.index[i-1] and s_tzxjje.index[i][:5]==s_tzxjje.index[i-1][:5]:
s_tzxjje_value.append(s_tzxjje[i]-s_tzxjje[i-1])
s_tzxjje_index.append(s_tzxjje.index[i][:4]+'-09-30')
elif '1-6月' in s_tzxjje.index[i] and '1-3月' in s_tzxjje.index[i-1] and s_tzxjje.index[i][:5]==s_tzxjje.index[i-1][:5]:
s_tzxjje_value.append(s_tzxjje[i]-s_tzxjje[i-1])
s_tzxjje_index.append(s_tzxjje.index[i][:4]+'-06-30')
else:
s_tzxjje_value.append(s_tzxjje[i])
s_tzxjje_index.append(s_tzxjje.index[i][:4]+'-03-31')
s_tzxjje_lj_value.append(sum(s_tzxjje_value))#计算累计额
s_tzxjje_lj_index.append(s_tzxjje_index[i])
s_tzxjje_new=pd.Series(s_tzxjje_value,index=s_tzxjje_index)
s_tzxjje_new.name=s_tzxjje.name
s_tzxjje_lj_new=pd.Series(s_tzxjje_lj_value,index=s_tzxjje_lj_index)
s_tzxjje_lj_new.name=s_tzxjje.name
s_czxjje=df6.loc['筹资活动产生的现金流量净额']/100000000#筹资现金净额
#以下换算成季度数据
s_czxjje_value=[]
s_czxjje_index=[]
s_czxjje_lj_value=[]#计算累计额
s_czxjje_lj_index=[]
for i in range(len(s_czxjje)):
if i>0 and '年度' in s_czxjje.index[i] and '1-9月' in s_czxjje.index[i-1] and s_czxjje.index[i][:5]==s_czxjje.index[i-1][:5]:
s_czxjje_value.append(s_czxjje[i]-s_czxjje[i-1])
s_czxjje_index.append(s_czxjje.index[i][:4]+'-12-31')
elif '1-9月' in s_czxjje.index[i] and '1-6月' in s_czxjje.index[i-1] and s_czxjje.index[i][:5]==s_czxjje.index[i-1][:5]:
s_czxjje_value.append(s_czxjje[i]-s_czxjje[i-1])
s_czxjje_index.append(s_czxjje.index[i][:4]+'-09-30')
elif '1-6月' in s_czxjje.index[i] and '1-3月' in s_czxjje.index[i-1] and s_czxjje.index[i][:5]==s_czxjje.index[i-1][:5]:
s_czxjje_value.append(s_czxjje[i]-s_czxjje[i-1])
s_czxjje_index.append(s_czxjje.index[i][:4]+'-06-30')
else:
s_czxjje_value.append(s_czxjje[i])
s_czxjje_index.append(s_czxjje.index[i][:4]+'-03-31')
s_czxjje_lj_value.append(sum(s_czxjje_value))#计算累计额
s_czxjje_lj_index.append(s_czxjje_index[i])
s_czxjje_new=pd.Series(s_czxjje_value,index=s_czxjje_index)
s_czxjje_new.name=s_czxjje.name
s_czxjje_lj_new=pd.Series(s_czxjje_lj_value,index=s_czxjje_lj_index)
s_czxjje_lj_new.name=s_czxjje.name
s_jyxjje_0=df6.loc['经营活动产生的现金流量净额']/100000000#未经年度换算的经营现金净额,因尽量偷懒，复制的ssa中的代码
#以下换算成季度数据
s_jyxjje_0_value=[]
s_jyxjje_0_index=[]
s_jyxjje_0_lj_value=[]#计算累计额
s_jyxjje_0_lj_index=[]
for i in range(len(s_jyxjje_0)):
if i>0 and '年度' in s_jyxjje_0.index[i] and '1-9月' in s_jyxjje_0.index[i-1] and s_jyxjje_0.index[i][:5]==s_jyxjje_0.index[i-1][:5]:
s_jyxjje_0_value.append(s_jyxjje_0[i]-s_jyxjje_0[i-1])
s_jyxjje_0_index.append(s_jyxjje_0.index[i][:4]+'-12-31')
elif '1-9月' in s_jyxjje_0.index[i] and '1-6月' in s_jyxjje_0.index[i-1] and s_jyxjje_0.index[i][:5]==s_jyxjje_0.index[i-1][:5]:
s_jyxjje_0_value.append(s_jyxjje_0[i]-s_jyxjje_0[i-1])
s_jyxjje_0_index.append(s_jyxjje_0.index[i][:4]+'-09-30')
elif '1-6月' in s_jyxjje_0.index[i] and '1-3月' in s_jyxjje_0.index[i-1] and s_jyxjje_0.index[i][:5]==s_jyxjje_0.index[i-1][:5]:
s_jyxjje_0_value.append(s_jyxjje_0[i]-s_jyxjje_0[i-1])
s_jyxjje_0_index.append(s_jyxjje_0.index[i][:4]+'-06-30')
else:
s_jyxjje_0_value.append(s_jyxjje_0[i])
s_jyxjje_0_index.append(s_jyxjje_0.index[i][:4]+'-03-31')
s_jyxjje_0_lj_value.append(sum(s_jyxjje_0_value))#计算累计额
s_jyxjje_0_lj_index.append(s_jyxjje_0_index[i])
s_jyxjje_0_new=pd.Series(s_jyxjje_0_value,index=s_jyxjje_0_index)
s_jyxjje_0_new.name=s_jyxjje_0.name
s_jyxjje_0_lj_new=pd.Series(s_jyxjje_0_lj_value,index=s_jyxjje_0_lj_index)
s_jyxjje_0_lj_new.name=s_jyxjje_0.name
#整理数据以便输出
labels=list(s_jyxjje_0_lj_new.index.values) #x刻度
data1=list(s_jyxjje_0_lj_new.values) #经营性现金净额
data2=list(s_czxjje_lj_new.values) #筹资性现金净额
data3=list(s_tzxjje_lj_new.values) #投资性现金净额
return labels,data1,data2,data3
