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