profitreport = "./output/profit_%d_%d.csv"

outreport = "./output/profitcontinuous.csv"

year = 2015

quarter = 4

dflist = []

for i in range(3):

report = profitreport % (year, quarter)

if os.path.exists(report):

print("Get data from csv")

dfsingle = pd.read_csv(report, encoding="ANSI")

else:

print("Get data from internet")

try:

dfsingle = ts.get_report_data(year=year, quarter=quarter)

dfsingle["period"] = "%d_%d" % (year, quarter)

except Exception as e:

dfsingle = ts.get_report_data(year=year, quarter=quarter - 1)

dfsingle["period"] = "%d_%d" % (year, quarter - 1)

dfsingle.to_csv(report)

dflist.append(dfsingle)

year += 1

dfall = pd.concat(dflist)

dfposprofit = pd.DataFrame(dfall[(dfall["net_profits"] > 0)

& (dfall["profits_yoy"] > 0)])

result = dfposprofit.groupby(["code", "name"]).size().reset_index()

print(result.columns)

result.columns = ["code", "name", "poscontinue"]

print(result)

result = pd.DataFrame(result[(result["poscontinue"] >= 3)],

columns=["code", "name"]).drop_duplicates()

print(result)

wholestockfile = "./output/all_%s.csv" % (time.strftime('%Y-%m-%d', time.localtime(time.time())))

lowpricestockfile = "./output/lowprice_%s.csv" % (time.strftime('%Y-%m-%d', time.localtime(time.time())))

industryfile = "./output/industry_%s.csv" % (time.strftime('%Y-%m-%d', time.localtime(time.time())))

if os.path.exists(wholestockfile):

print("Get data from csv")

dfall = pd.read_csv(wholestockfile, encoding="ANSI")

dfindustry = pd.read_csv(industryfile, encoding="ANSI")

else:

print("Get data from internet")

dfall = ts.get_today_all()

dfall.to_csv(wholestockfile, index=False)

dfindustry = ts.get_industry_classified()

dfindustry.to_csv(industryfile, index=False)

# print(dfall)

# df2buy = pd.DataFrame(dfall[(dfall["trade"] < 7) & (dfall["trade"] > 0) & (dfall["pb"] < 1.5)])

print("Get data which 0< PB <= 1.5 and 0 < PE < 30")

df2buy = pd.DataFrame(dfall[(dfall["pb"] <= 1.5)

& (dfall["pb"] > 0)

& (dfall["per"] > 0)

& (dfall["per"] < 30)])

# print(dfindustry)

dfmerge = pd.merge(df2buy, dfindustry, on=['code', 'name'], how='left')

# print(dfmerge)

print("Output to csv")

dfmerge.to_csv(lowpricestockfile, index=False)

print(dfmerge)

dfgroup = dfmerge.groupby("c_name").size()

print(dfgroup)

dfgroup.plot(kind="bar")

chinese = mpl.font_manager.FontProperties(fname='C:\Windows\Fonts\simhei.ttf')

plt.rcParams['font.sans-serif'] = ['SimHei']

plt.rcParams['axes.unicode_minus'] = False

# plt.xlabel("c_name",fontproperties=chinese)

num_time = []

for date in dates:

date_time = datetime.datetime.strptime(date, '%Y-%m-%d')

num_date = date2num(date_time)

num_time.append(num_date)

# date = time.strftime('%Y-%m-%d',time.localtime(time.time()))

# realmarket = ts.get_k_data(code=code, start="2018-05-02")

# print(realmarket)

shyh = ts.get_k_data(code)

print(shyh)

mat_shyh = shyh.as_matrix()

num_time = date_to_num(mat_shyh[:, 0])

mat_shyh[:, 0] = num_time

# print(mat_shyh[:3])

fig, ax = plt.subplots(figsize=(10, 5))

fig.subplots_adjust(bottom=0.5)

mpf.candlestick_ochl(ax, mat_shyh, width=0.6, colorup="r", colordown="g", alpha=1.0)

chinese = mpl.font_manager.FontProperties(fname='C:\Windows\Fonts\simhei.ttf')

plt.grid(True)

plt.xticks(rotation=30)

# plt.title(getstockinfo(code))

plt.title(getstockinfo(code), fontproperties=chinese)

plt.xlabel("Date")

plt.ylabel("Price")

ax.xaxis_date()

marketdata = ts.get_k_data(code)

for index, row in marketdata.iterrows():

marketdata.loc[index, 'dayofweek'] = time.strftime('%A', time.strptime(row.date, "%Y-%m-%d"))

downdata = marketdata[((marketdata.close - marketdata.open) / marketdata.open) > 0.005]

print(downdata.head())

dayweekgroup = downdata['dayofweek'].groupby(

downdata['dayofweek'].map(lambda x: x[0:4])) \

.count()

print(dayweekgroup)

dayweekgroup.plot(kind="bar")

plt.rcParams['font.sans-serif'] = ['SimHei']

plt.rcParams['axes.unicode_minus'] = False

plt.title(u'Rise over 0.5%', fontsize=17)

industryfile = "./output/all_2018-03-30.csv"

dfindustry = pd.read_csv(industryfile, encoding="ANSI")

for stockinfo in dfindustry[dfindustry["code"] == int(code)].values:

filebasic = './output/stockbasic.csv'

filetoday = './output/stocktoday.csv'

if os.path.exists(filebasic) and not needreloadbasic:

print("Get basic data from csv")

dfstockbasic = pd.read_csv(filebasic, encoding="ANSI")

else:

print("Get basic data from internet")

try:

dfstockbasic = ts.get_stock_basics()

dfstockbasic.to_csv(filebasic, encoding='ANSI')

dfstockbasic = pd.read_csv(filebasic, encoding="ANSI")

except Exception as e:

print(e)

if os.path.exists(filetoday) and not needgettoday:

print("Get today data from csv")

dfstocktoday = pd.read_csv(filetoday, encoding="ANSI")

else:

print("Get today data from internet")

try:

dfstocktoday = ts.get_today_all()

dfstocktoday.to_csv(filetoday, encoding='ANSI')

except Exception as e:

print(e)

# dfstockbasic['tomarket'] = pd.to_numeric(dfstockbasic.timeToMarket)

# dfstockbasic = dfstockbasic[(dfstockbasic.tomarket <= 20180201)]

dfstockbasic['code'] = dfstockbasic['code'].apply(str)

for index, row in dfstockbasic.iterrows():

dfstockbasic.loc[index, 'code'] = '{:0>6}'.format(dfstockbasic.loc[index, 'code'])

# print(index, ' ', dfstockbasic.loc[index, 'code'])

dfstockbasic.rename(

columns={'code': '代码',

'name': '名称',

'industry': '所属行业',

'area': '地区',

'pe': '市盈率',

'outstanding': '流通股本(亿)',

'totals': '总股本(亿)',

'totalAssets': '总资产(万)',

'liquidAssets': '流动资产',

'fixedAssets': '固定资产',

'reserved': '公积金',

'reservedPerShare': '每股公积金',

'esp': '每股收益',

'bvps': '每股净资',

'pb': '市净率',

'timeToMarket': '上市日期',

'undp': '未分利润',

'perundp': '每股未分配',

'rev': '收入同比(%)',

'profit': '利润同比(%)',

'gpr': '毛利率(%)',

'npr': '净利润率(%)',

'holders': '股东人数'

}, inplace=True)

dfstockbasic.to_excel('./output/allstockbasicinformation.xlsx', encoding='ANSI')

return

dfmerge['totalnessets'] = (dfmerge.totals * dfmerge.trade)

dfbigstock = dfmerge[dfmerge.totalnessets > 400]

print(dfbigstock)

codes = {}

for index, row in dfbigstock.iterrows():

codes['{:0>6}'.format(row['code'])] = row['totalnessets']

chinese = mpl.font_manager.FontProperties(fname='C:\Windows\Fonts\simhei.ttf')

plt.figure(figsize=(10, 8), facecolor='w')

index = 1

for code in codes:

print(code)

shyh = ts.get_k_data(code)

mat_shyh = shyh.as_matrix()

num_time = date_to_num(mat_shyh[:, 0])

mat_shyh[:, 0] = num_time

ax = plt.subplot(4, 4, index)

mpf.candlestick_ochl(ax, mat_shyh, width=0.6, colorup="r", colordown="g", alpha=1.0)

plt.grid(True)

plt.xticks(rotation=30)

plt.title('%s: %.2f' % (getstockinfo(code), codes[code]), fontproperties=chinese)

plt.xlabel("Date")

plt.ylabel("Price")

ax.xaxis_date()

index = index + 1

if index == 16:

break

plt.suptitle('2015-10-01之后上市总市值超过400亿人民币的股票', fontproperties=chinese)

plt.tight_layout(1.5)

plt.subplots_adjust(top=0.92)

doc = {}

doc[1] = ['234']

doc[2] = ['22']

doc[3] = ['78776']