diff --git a/src/fund_statistic.py b/src/fund_statistic.py index eb9da49..3cd04f7 100644 --- a/src/fund_statistic.py +++ b/src/fund_statistic.py @@ -12,7 +12,6 @@ Copyright (c) 2020 Camel Lu import time import re import decimal -import os from pprint import pprint import pandas as pd import numpy as np @@ -35,11 +34,10 @@ def get_fund_code_pool(): 'operator': '=' } last_year_time = time.localtime(time.time() - 365 * 24 * 3600) - last_year_date = time.strftime('%Y-%m-%d', last_year_time) + # last_year_date = time.strftime('%Y-%m-%d', last_year_time) condition_dict = { 'morning_star_rating_5': morning_star_rating_5_condition, 'morning_star_rating_3': morning_star_rating_3_condition, - # 'manager_start_date': '2020-05-25' } fund_code_pool = each_statistic.select_fund_pool( **condition_dict, @@ -54,16 +52,12 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, fund_code_poo quarter_index = get_last_quarter_str(2) print("比较-->quarter_index", quarter_index) - last_quarter_input_file = './outcome/数据整理/strategy/all_stock_rank/' + \ - quarter_index + '.xlsx' - data_last_quarter = pd.read_excel(io=last_quarter_input_file, engine="openpyxl", dtype={ - "代码": np.str}, sheet_name=None) + last_quarter_input_file = './outcome/数据整理/strategy/all_stock_rank/' + quarter_index + '.xlsx' + data_last_quarter = pd.read_excel(io=last_quarter_input_file, engine="openpyxl", dtype={"代码": np.str}, sheet_name=None) if market: df_data_target_market = data_last_quarter.get(market) - df_data_target_market[quarter_index + '持有数量（只）'] = df_data_target_market[quarter_index + '持有数量（只）'].astype( - int) - each_statistic = FundStatistic() + df_data_target_market[quarter_index + '持有数量（只）'] = df_data_target_market[quarter_index + '持有数量（只）'].astype(int) filter_list = [] for stock in stock_list: @@ -76,7 +70,6 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, fund_code_poo holder_asset = stock_holder_detail.get('holder_asset') if not market: target_market = get_stock_market(stock_code) - print("target_market", target_market) df_data_target_market = data_last_quarter.get(target_market) target_loc = df_data_target_market[df_data_target_market['代码'] == stock_code] last_holder_count = 0 @@ -89,33 +82,21 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, fund_code_poo target_loc[col_target].iloc[0]), 4) diff_holder_count = holder_count - last_holder_count diff_holder_asset = holder_asset - last_holder_asset - - diff_holder_count_percent = '{:.2%}'.format( - diff_holder_count / last_holder_count) if last_holder_count != 0 else "+∞" - - diff_holder_asset_percent = '{:.2%}'.format( - diff_holder_asset / last_holder_asset) if last_holder_asset != 0 else "+∞" + diff_holder_count_percent = '{:.2%}'.format(diff_holder_count / last_holder_count) if last_holder_count != 0 else "+∞" + diff_holder_asset_percent = '{:.2%}'.format(diff_holder_asset / last_holder_asset) if last_holder_asset != 0 else "+∞" # flag = '📈' if diff_holder_count > 0 else '📉' # if diff_holder_count == 0: # flag = '⏸' flag_count = 'up' if diff_holder_count > 0 else 'down' - if diff_holder_count == 0: - flag = '=' flag_asset = 'up' if diff_holder_asset > 0 else 'down' - if diff_holder_asset == 0: - flag = '=' item_tuple = [stock_code, stock_name, holder_count, last_holder_count, diff_holder_count, diff_holder_count_percent, flag_count, holder_asset, last_holder_asset, diff_holder_asset, diff_holder_asset_percent, flag_asset] if is_A_stock: - industry_name_third = stock_holder_detail.get( - 'industry_name_third') - industry_name_second = stock_holder_detail.get( - 'industry_name_second') - industry_name_first = stock_holder_detail.get( - 'industry_name_first') - item_tuple = [*item_tuple, industry_name_third, - industry_name_second, industry_name_first] + industry_name_third = stock_holder_detail.get('industry_name_third') + industry_name_second = stock_holder_detail.get('industry_name_second') + industry_name_first = stock_holder_detail.get('industry_name_first') + item_tuple = [*item_tuple, industry_name_third,industry_name_second, industry_name_first] # if diff_percent == "+∞" or not float(diff_percent.rstrip('%')) < -20: filter_list.append(item_tuple) @@ -132,14 +113,12 @@ def t100_stocks_rank(each_statistic=None, *, quarter_index=None): last_quarter_index = get_last_quarter_str(2) output_file = './outcome/数据整理/strategy/top100_rank.xlsx' sheet_name = quarter_index + '基金重仓股T100' - columns = ['代码', - '名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降'] + columns = ['代码','名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降'] stock_top_list = each_statistic.all_stock_fund_count( quarter_index=quarter_index, filter_count=80) stock_top_list = stock_top_list[:100] # 获取top100权重股 - # pprint(stock_top_list) filter_list = stocks_compare(stock_top_list) df_filter_list = pd.DataFrame(filter_list, columns=columns) update_xlsx_file(output_file, df_filter_list, sheet_name) @@ -154,8 +133,7 @@ def all_stocks_rank(each_statistic=None): quarter_index = get_last_quarter_str(1) print("该quarter_index为", quarter_index) last_quarter_index = get_last_quarter_str(2) - columns = ['代码', - '名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降'] + columns = ['代码','名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降'] output_file = './outcome/数据整理/strategy/all_stock_rank/' + quarter_index + '.xlsx' stock_top_list = each_statistic.all_stock_fund_count( @@ -167,7 +145,6 @@ def all_stocks_rank(each_statistic=None): other_stock_list = [] for stock_name_code in stock_top_list: stock_code = stock_name_code[0].split('-', 1)[0] - #path = 'other' if bool(re.search("^\d{5}$", stock_code)): #path = '港股' @@ -176,8 +153,7 @@ def all_stocks_rank(each_statistic=None): # 'A股/深证主板'、'A股/创业板'、'A股/上证主板'、'A股/科创板' a_condition = bool(re.search( "^(00(0|1|2|3)\d{3})|(30(0|1)\d{3})|(60(0|1|2|3|5)\d{3})|68(8|9)\d{3}$", stock_code)) - target_item = find_from_list_of_dict( - all_a_stocks_industry_info_list, 'stock_code', stock_code) + target_item = find_from_list_of_dict(all_a_stocks_industry_info_list, 'stock_code', stock_code) if a_condition and target_item: stock_name_code[1]['industry_name_first'] = target_item.get( 'industry_name_first') @@ -204,7 +180,6 @@ def all_stocks_rank(each_statistic=None): a_columns = [*columns, '三级行业', '二级行业', '一级行业'] df_a_list = pd.DataFrame(a_stock_compare_list, columns=a_columns) - print("df_a_list", df_a_list) df_hk_list = pd.DataFrame(hk_stock_compare_list, columns=columns) df_other_list = pd.DataFrame(other_stock_compare_list, columns=columns) @@ -251,22 +226,16 @@ def all_stock_holder_detail(each_statistic=None, *, quarter_index=None, threshol path = 'A股/科创板' else: print('stock_name_code', stock_name_code) - hold_fund_count = stock[1]['count'] - hold_fund_list = sorted( - stock[1]['fund_list'], key=lambda x: x['持有市值(亿元)'], reverse=True) + hold_fund_list = sorted(stock[1]['fund_list'], key=lambda x: x['持有市值(亿元)'], reverse=True) df_list = pd.DataFrame(hold_fund_list) - # if stock_code == 'NTES': - # print('stock_code', df_list) stock_name_code = stock_name_code.replace('-*', '-').replace('/', '-') path = './outcome/数据整理/stocks/' + path + '/' + stock_name_code + '.xlsx' path = path.replace('\/', '-') - print("path", path) - update_xlsx_file(path, df_list, quarter_index) def get_special_fund_code_holder_stock_detail(each_statistic=None, quarter_index=None): - """ 获取某些基金的十大持仓股票信息 + """获取某些基金的十大持仓股票信息 """ if each_statistic == None: each_statistic = FundStatistic() @@ -337,11 +306,9 @@ def get_special_fund_code_holder_stock_detail(each_statistic=None, quarter_index # 基金组合信息 fund_portfolio = holder_history_list[1] fund_code_pool = list(fund_portfolio.keys()) - holder_stock_industry_list = each_statistic.summary_special_funds_stock_detail( - fund_code_pool, quarter_index) + holder_stock_industry_list = each_statistic.summary_special_funds_stock_detail(fund_code_pool, quarter_index) path = './outcome/数据整理/funds/高分权益基金组合十大持仓明细.xlsx' - columns = ['基金代码', '基金名称', '基金类型', '基金经理', '基金总资产（亿元）', '基金股票总仓位', - '十大股票仓位', '股票代码', '股票名称', '所占仓位', '所处仓位排名', '三级行业', '二级行业', '一级行业'] + columns = ['基金代码', '基金名称', '基金类型', '基金经理', '基金总资产（亿元）', '基金股票总仓位', '十大股票仓位', '股票代码', '股票名称', '所占仓位', '所处仓位排名', '三级行业', '二级行业', '一级行业'] df_a_list = pd.DataFrame(holder_stock_industry_list, columns=columns) # print("df_a_list", df_a_list)