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stock_financial_report.py
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#利润表=lrb，资产负债表=zcfzb，现金流量表=xjllb
#参考 https://zhuanlan.zhihu.com/p/44753154
import os
import threading
import time
import math
import numpy as np
import akshare as ak
import pandas as pd
import datetime
from bokeh.io import output_file, show
from bokeh.layouts import column
from bokeh.plotting import figure
from bokeh.models import LinearAxis, Range1d, VBar
from scipy.stats import linregress
from utils import *
import requests, urllib
cur_dir = os.path.dirname(__file__)
data_dir = os.path.join(cur_dir, 'data')
def transpose_csv(path):
df = pd.read_csv(path, header=None, encoding='utf-8')
data = df.values
# 删除最后一列的逗号
data = data[:, :-1]
# 把列的顺序反过来
data[:, 1:] = data[:, -1:0:-1]
# 转置
index1 = list(df.keys())[:-1]
data = list(map(list, zip(*data)))
data = pd.DataFrame(data, index = index1)
data.to_csv(path, header=None, index=None)
def get_table(url, path):
while True:
try:
content = urllib.request.urlopen(url, timeout=2).read()
content = content.decode("gbk")
content = content.replace('--', '')
content = content.replace(' ', '')
# content = content.replace(' 报告日期', 'time')
content = content.replace('报告日期', 'time')
content = content.replace('(万元,', '(万元),')
content = content.encode("utf8")
with open(path, 'wb') as f:
f.write(content)
f.close()
transpose_csv(path)
break
# sleep(1)
except urllib.error.HTTPError as e:
print(e)
continue
# except urllib.error.URLError as e:
# print(e)
except Exception as e:
print(e)
break
def get_tables(stock):
lrb_url = 'http://quotes.money.163.com/service/lrb_' + str(stock) + '.html'
zcfzb_url = 'http://quotes.money.163.com/service/zcfzb_' + str(stock) + '.html'
xjllb_url = 'http://quotes.money.163.com/service/xjllb_' + str(stock) + '.html'
stock_data_dir = os.path.join(data_dir, 'stock', stock)
if not os.path.exists(stock_data_dir):
os.mkdir(stock_data_dir)
print(stock_data_dir)
# 利润表
print('get income statement...')
get_table(lrb_url, os.path.join(stock_data_dir, 'income statement.csv'))
# 资产负债表
print('get balance sheet...')
get_table(zcfzb_url, os.path.join(stock_data_dir, 'balance sheet.csv'))
# 资金流量表
print('get cash flow statement...')
get_table(xjllb_url, os.path.join(stock_data_dir, 'cash flow statement.csv'))
# path = data_dir + 'income statement.csv'
# df = pd.read_csv(path)
# path = data_dir + 'balance sheet.csv'
# df = pd.read_csv(path)
# path = data_dir + 'cash flow statement.csv'
# df = pd.read_csv(path)
# print(df['销售商品、提供劳务收到的现金(万元)'])
def get_all_stock_tables():
stock_list_path = os.path.join(cur_dir, "stock_list.csv")
df = pd.read_csv(stock_list_path)
code = np.array(df['代码'])
name = np.array(df['名称'])
L = len(df)
for i in range(L):
# print(code[i][2:])
print(code[i][2:])
if(code[i][0:2] != 'bj'):
get_tables(code[i][2:])
pass
# def get_stock_category(code):
# df = ak.stock_industry_change_cninfo(symbol='688288', start_date="20161227", end_date="20220708")
# a = df.query('分类标准 == ["中证行业分类标准"]')
# print(a)
# 获取每个上市公司所处的行业(中证行业分类标准), 烂网站, 没拿完数据就挂了
def get_all_stock_category():
stock_list_path = os.path.join(cur_dir, "stock_list.csv")
df = pd.read_csv(stock_list_path)
df = pd.read_csv(stock_list_path)
code = np.array(df['代码'])
name = np.array(df['名称'])
lst = ['code', 'name', '一级行业', '二级行业', '三级行业', '四级行业']
df1 = pd.DataFrame(columns = lst)
L = len(df)
k = 0
for i in range(600,601):
# print(code[i][2:])
print(code[i][2:])
# try:
df = ak.stock_industry_change_cninfo(symbol=code[i][2:], start_date="20191227", end_date="20220901")
a = df.query('分类标准 == ["中证行业分类标准"]')
print(a)
df1.loc[k] = [code[i][2:], name[i], np.array(a['行业门类'])[-1], np.array(a['行业次类'])[-1], np.array(a['行业大类'])[-1], np.array(a['行业中类'])[-1]]
k = k + 1
# except Exception as e:
# print(e)
# continue
stock_category_path = os.path.join(cur_dir, "stock_category.csv")
df1.to_csv(stock_category_path, index=None)
# 统计上市企业财务报表
def stock_financial_statistics():
path = os.path.join(cur_dir, "中证行业分类结果.csv")
df = pd.read_csv(path, dtype='str')
level1 = np.array(df['新中证一级简称'])
level2 = np.array(df['新中证二级简称'])
level3 = np.array(df['新中证三级简称'])
level4 = np.array(df['新中证四级简称'])
idx = np.where(level4 == '焦炭')
# print(df.iloc[idx]['code'])
codes = df.iloc[idx]['code']
for i in range(len(idx)):
# 股票财务表的目录
print(codes.iloc[i])
stock_data_dir = os.path.join('D:\上市公司财报\stock\\', codes.iloc[i])
balance_sheet_path = os.path.join(stock_data_dir, 'income statement.csv')
# 表中没有的数据设成0
balance_sheet_df = pd.read_csv(balance_sheet_path).fillna('0')
# balance_sheet_df[balance_sheet_df == nan] = '0'
# print(balance_sheet_df == np.nan)
print(balance_sheet_df.iloc[2,2])
t0 = pd.DatetimeIndex(pd.to_datetime(balance_sheet_df['time'], format='%Y-%m-%d'))
income0 = np.array(balance_sheet_df['营业总收入(万元)'], dtype=float)
cost0 = np.array(balance_sheet_df['营业总成本(万元)'], dtype=float)
profit0 = income0 - cost0
if i == 0:
t = t0.copy()
profit = profit0.copy()
else:
t, profit = data_add(t, profit, t0, profit0)
plot_seasonality(t, profit, start_year=2014, title='上市公司利润 普钢(万元)')
stock_financial_statistics()
# get_all_stock_category()
# get_all_table('430047')
# get_all_stock_tables()