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calcu_3year_average_pe.py
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import os
import urllib.request
from datetime import datetime
from time import sleep
import pandas as pd
import tushare as ts
current_folder = os.path.dirname(os.path.abspath(__file__))
calcu_average_profit_end_year = 2016 # 计算平均利润的截止年,包括该年
caiwu_folder = os.path.join(current_folder, '财务数据%s' % calcu_average_profit_end_year)
DEBUG = True
today = str(datetime.now())[:10]
def create_folder_if_need(path):
if not os.path.exists(path): # 如果该文件夹不存在，创建文件夹
os.makedirs(path)
elif not os.path.isdir(path):
os.makedirs(path)
def download_if_need(code, url, name):
path = os.path.join(caiwu_folder, name + code + '.csv')
if not os.path.exists(path):
urllib.request.urlretrieve(url, path)
sleep(1.5) # 间隔一段时间，防止服务器关闭连接
def download_stock_data(code):
cwzb_url = 'http://quotes.money.163.com/service/zycwzb_%s.html?type=report' % code
# 财务指标
create_folder_if_need(caiwu_folder)
download_if_need(code, cwzb_url, '财务指标')
def calcu_3year_average_profit(code, year):
download_stock_data(code)
data = pd.read_csv(os.path.join(caiwu_folder, '财务指标' + code + '.csv'), encoding="gbk",
index_col=0)
data = data.T
average_profit = 0
for i in range(year - 2, year + 1):
average_profit += float(data['净利润(万元)'][str(i) + '-12-31']) # 之前2年的年净利润
# try:
# average_profit += float(data['净利润(万元)'][str(year) + '-09-30']) # 今年三季度的利润
# except Exception as e:
# average_profit += float(data['净利润(万元)'][str(year - 3) + '-12-31']) # 没有三季度的数据
# if DEBUG:
# print(code + '没有三季度的数据')
average_profit /= 3
# print(average_profit)
return average_profit
def calcu_all_stocks_3year_average_profit(year): # 生成3年平均利润列表
path = os.path.join(current_folder, '股票列表%s.csv' % today)
if not os.path.exists(path):
data = ts.get_stock_basics()
lie = ['名字', '行业', '地区', '市盈率', '流通股本', '总股本',
'总资产(万)', '流动资产', '固定资产', '公积金', '每股公积金', '每股收益', '每股净资',
'市净率', '上市日期', '未分利润', '每股未分配', '收入同比(%)', '利润同比(%)',
'毛利率(%)', '净利润率(%)', '股东人数']
data.columns = lie
data.index.names = ['代码']
data.to_csv(path, encoding='utf-8')
data = pd.read_csv(path, encoding='utf-8', index_col=0)
# print(data)
data['平均利润'] = 0
for index, row in data.iterrows():
try:
data.loc[index, '平均利润'] = calcu_3year_average_profit('%06d' % index, year)
except Exception as e:
print(e)
data.loc[index, '平均利润'] = 0
print('完成%s' % index)
data.to_csv(os.path.join(current_folder, '3年平均利润.csv'), encoding='utf-8')
def filter_stock_by_average_pe(min, max):
path = os.path.join(current_folder, '3年平均利润.csv')
if not os.path.exists(path): # 没有就生成3年平均利润列表
calcu_all_stocks_3year_average_profit(calcu_average_profit_end_year)
gplb = pd.read_csv(path, index_col=0, encoding='utf-8')
# current_sec=str(now)[:18].replace('-','_').replace(':','_')
price_path = os.path.join(current_folder, today + '股票价格.csv')
if not os.path.exists(price_path):
ts.get_today_all().set_index('code').to_csv(price_path)
current_price = pd.read_csv(price_path, encoding="utf-8", index_col=0)
current_price = current_price[['trade']]
current_price.columns = ['价格']
gplb = gplb[
['名字', '行业', '地区', '流通股本', '总股本', '总资产(万)', '流动资产', '固定资产', '每股净资', '市净率', '上市日期',
'平均利润']]
data = pd.merge(gplb, current_price, left_index=True, right_index=True)
# 因为这里的平均利润单位是万元，而总股本单位是亿，价格单位是元
data['平均市盈率'] = data['总股本'] * data['价格'] * 10000 / data['平均利润']
data = data[data['平均市盈率'] < max]
data = data[data['平均市盈率'] > min]
data['平均市盈率'] = data['平均市盈率'].round()
data['平均利润'] = data['平均利润'].round()
data['市净率'] = data['市净率'].round(1)
data['固定资产'] = data['固定资产'].round()
data['流动资产'] = data['流动资产'].round()
data['总股本'] = data['总股本'].round()
data['流通股本'] = data['流通股本'].round()
average_pe_file = os.path.join(current_folder, today + '-3年平均市盈率在%s和%s之间的公司.xlsx' % (min, max))
data.to_excel(average_pe_file)
if __name__ == '__main__':
filter_stock_by_average_pe(2, 20) # 这个函数是根据平均pe过滤股票
# calcu_3year_average_profit('000793', 2016)
print('完成')