wukan1986
diff --git a/‎reports/涨停分时炸板.py‎
Lines changed: 2 additions & 1 deletion b/‎reports/涨停分时炸板.py‎
Lines changed: 2 additions & 1 deletion
diff --git a/‎reports/涨跌停统计.py‎
Lines changed: 13 additions & 9 deletions b/‎reports/涨跌停统计.py‎
Lines changed: 13 additions & 9 deletions
@@ -25,7 +25,7 @@ def _code_block_1():
     最高涨停 = high >= high_limit - 0.001
     收盘涨停 = close >= high_limit - 0.001
     昨收涨停 = ts_delay(收盘涨停, 1, False)
-    # 化简后逻辑表达式更复杂了
+    # TODO 化简后逻辑表达式更复杂了，最好能简化一下
     封板 = (~昨收涨停 & 开盘涨停) | (~开盘涨停 & 最高涨停)
     炸板 = (昨收涨停 & ~开盘涨停) | (最高涨停 & ~收盘涨停)
 
@@ -38,6 +38,7 @@ def _code_block_1():
     首次封板=pl.col("datetime").filter(pl.col('封板')).first(),
     最后封板=pl.col("datetime").filter(pl.col('封板')).last(),
 )
+df.write_parquet(r"分时炸板.parquet")
 
 df = df.filter(pl.col("炸板次数") >= 5).sort("asset", "date")
 
 
@@ -19,7 +19,6 @@
     '参股券商',
     '参股新三板',
     '参股银行',
-
     '创业板综',
     '创业成份',
     '低价股',
@@ -38,7 +37,7 @@
     '宁组合',
     '破净股',
     'QFII重仓',
-    '融资融券',
+    # '融资融券',
     '社保重仓',
     '深成500',
     '深股通',
@@ -61,9 +60,9 @@
     '昨日涨停_含一字',
     '中特估',
     '中证500',
-    '转债标的',
+    # '转债标的',
     '中字头',
-    '国企改革',
+    # '国企改革',
 ]
 
 地区板块 = [
@@ -88,6 +87,9 @@
 
 # 读取个股数据
 df_stock = pl.read_parquet(r"M:\preprocessing\data2.parquet")
+# 读取分时数据
+df_min = pl.read_parquet(r"分时炸板.parquet")
+df_stock = df_stock.join(df_min, how='left', on=['asset', 'date'])
 df_stock = df_stock.with_columns(code=pl.col('asset').str.slice(0, 6))
 print(df_stock.schema)
 
@@ -97,6 +99,7 @@ def _code_block_1():
     收盘跌停 = close <= low_limit + 0.001
     连板天数 = ts_cum_sum_reset(收盘涨停)
     涨停T天, 涨停N板, _ = ts_up_stat(收盘涨停)
+    放量 = volume / volume[1]
 
 
 df_stock = codegen_exec(df_stock, _code_block_1)
@@ -109,22 +112,23 @@ def _code_block_1():
 DATE2 = pl.date(2024, 11, 25)
 df_stock = df_stock.filter(pl.col('date') >= DATE2)
 
-df_stock_board = df_stock.join(df_board, how='left', left_on=['code'], right_on=['代码']).filter(pl.col('board').is_not_null())
+df_stock_board = df_stock.join(df_board, how='left', left_on=['code'], right_on=['代码'])  # .filter(pl.col('board').is_not_null())
 del df_stock
 del df_board
-df_stock_board = df_stock_board.select('date', 'asset', '名称', '涨停T天', '涨停N板', '连板天数', '收盘涨停', 'board')
+
+columns = ['名称', "涨停T天", "涨停N板", "收盘涨停", '放量', '炸板次数', '首次封板', '最后封板']
 
 df_board_sorted = df_stock_board.group_by('date', 'board').agg(
     pl.col('收盘涨停').sum().alias('封板数'),
     (pl.col('连板天数') > 1).sum().alias('连板数'),
-    pl.col('名称', "asset", "涨停T天", "涨停N板", "收盘涨停").top_k_by('涨停N板', 5),
+    pl.col("asset", *columns).top_k_by('涨停N板', 5),
 ).sort('date', '封板数', descending=[False, True]).with_row_index()
-df_board_sorted.explode("asset", '名称', "涨停T天", "涨停N板", "收盘涨停").write_csv('涨停板块前5.csv')
+df_board_sorted.explode("asset", *columns).write_csv('涨停板块前5.csv')
 print(df_board_sorted)
 
 df_stock_board = df_stock_board.join(df_board_sorted.select('index', 'date', 'board'), how='left', on=['date', 'board'])
 df_stock_board = df_stock_board.sort('date', 'asset', 'index')
 
-df_stock_list = df_stock_board.group_by('date', 'asset').agg(pl.col('名称', '涨停T天', '涨停N板', '连板天数', '收盘涨停').first(), pl.col('board').str.join(','))
+df_stock_list = df_stock_board.group_by('date', 'asset').agg(pl.col(*columns).first(), pl.col('board').str.join(','))
 df_stock_list.sort('date', '涨停N板', descending=[False, True]).write_csv('涨停个股.csv')
 print(df_stock_list)