feat: merge datetime fields in DataFrame output, hide MinuteBar internal fields

- K-line: daily+ periods output 'date' only, minute periods output 'datetime'
- Transactions (tick-by-tick): combine date param + hour/minute into 'datetime'
- XdxrRecord, HistoricalFundFlow: year/month/day merged to 'date'
- MinuteBar: rename unknown_1 to _unknown_1 (hidden from DataFrame)
- MinuteBar: add datetime column computed from bar index (A-share 240-bar pattern)
- get_minute_time_data: use history endpoint only (current-day endpoint broken in pytdx too)
- Update all examples to reflect new DataFrame column names

examples/06_finance/company_info.py

@@ -1,7 +1,6 @@
 """演示：获取公司信息目录与各个分类的详细内容。"""
 
-import pandas as pd
-from easy_tdx import TdxClient, Market
+from easy_tdx import Market, TdxClient
 
 CODE = "600519"
 NAME = "贵州茅台"
@@ -28,51 +27,36 @@ SHOW_CATEGORIES = [
 ]
 
 
-def show_categories(categories):
-    """显示公司信息目录。"""
-    df = pd.DataFrame([{
-        "目录名": cat.name,
-        "文件名": cat.filename,
-        "起始偏移": cat.start,
-        "内容长度": cat.length,
-    } for cat in categories])
-    print(f"{NAME} 公司信息目录:")
-    print(df.to_string(index=False))
-
-
 def show_category_content(client, categories, category_name, max_chars=500):
     """获取并展示指定分类的内容。"""
-    cat = next((c for c in categories if c.name == category_name), None)
-    if not cat:
+    row = categories[categories["name"] == category_name]
+    if row.empty:
         print(f"  未找到分类: {category_name}")
         return
 
+    r = row.iloc[0]
     content = client.get_company_info_content(
-        MARKET, CODE, cat.filename, cat.start, cat.length
+        MARKET, CODE, r["filename"], int(r["start"]), int(r["length"])
     )
     text = content.strip()
     if len(text) > max_chars:
         text = text[:max_chars] + f"\n... (共 {len(content.strip())} 字，仅显示前 {max_chars} 字)"
-    print(f"\n{'='*60}")
-    print(f"【{cat.name}】 (共 {cat.length} 字节)")
-    print(f"{'='*60}")
+    print(f"\n{'=' * 60}")
+    print(f"【{r['name']}】 (共 {r['length']} 字节)")
+    print(f"{'=' * 60}")
     print(text)
 
 
-def show_all_categories(client, categories):
-    """依次展示所有 SHOW_CATEGORIES 中列出的分类内容。"""
-    for name in SHOW_CATEGORIES:
-        show_category_content(client, categories, name)
-
-
 with TdxClient.from_best_host() as c:
     categories = c.get_company_info_category(MARKET, CODE)
 
     # 1. 显示目录
-    show_categories(categories)
+    print(f"{NAME} 公司信息目录:")
+    print(categories.to_string(index=False))
 
     # 2. 显示所有分类内容（每个分类默认只显示前500字）
-    show_all_categories(c, categories)
+    for name in SHOW_CATEGORIES:
+        show_category_content(c, categories, name)
 
     # 3. 也可以单独获取某个分类的完整内容，例如：
     # show_category_content(c, categories, "公司概况", max_chars=99999)

examples/06_finance/finance_info.py

@@ -1,21 +1,8 @@
 """演示：获取最新财务数据。"""
 
-import pandas as pd
-from easy_tdx import TdxClient, Market
+from easy_tdx import Market, TdxClient
 
 with TdxClient.from_best_host() as c:
     info = c.get_finance_info(Market.SH, "600519")
-    df = pd.DataFrame([
-        {"项目": "总股本(万股)", "数值": info.zong_guben},
-        {"项目": "流通股本(万股)", "数值": info.liutong_guben},
-        {"项目": "每股净资产", "数值": info.meigujing_zichan},
-        {"项目": "净利润(元)", "数值": info.jing_lirun},
-        {"项目": "主营收入(元)", "数值": info.zhuying_shouru},
-        {"项目": "主营利润(元)", "数值": info.zhuying_lirun},
-        {"项目": "净资产(元)", "数值": info.jing_zichan},
-        {"项目": "总资产(元)", "数值": info.zong_zichan},
-        {"项目": "股东人数", "数值": info.gudong_renshu},
-        {"项目": "上市日期", "数值": info.ipo_date},
-    ])
     print("贵州茅台 最新财务数据:")
-    print(df.to_string(index=False, formatters={"数值": lambda x: f"{x:,.0f}"}))
+    print(info.T.to_string(header=False))

examples/06_finance/price_limits.py

@@ -1,23 +1,16 @@
 """演示：计算个股涨跌停价格。"""
 
-import pandas as pd
-from easy_tdx import TdxClient, Market
+from easy_tdx import Market, TdxClient
 
 CODE = "600519"
 NAME = "贵州茅台"
 
 with TdxClient.from_best_host() as c:
     quotes = c.get_security_quotes([(Market.SH, CODE)])
-    if quotes:
-        q = quotes[0]
-        limit_up, limit_down = c.get_price_limits(
-            Market.SH, CODE, NAME, q.pre_close
-        )
-        df = pd.DataFrame([{
-            "代码": CODE,
-            "名称": NAME,
-            "昨收": q.pre_close,
-            "涨停价": limit_up,
-            "跌停价": limit_down,
-        }])
-        print(df.to_string(index=False))
+    if not quotes.empty:
+        q = quotes.iloc[0]
+        limit_up, limit_down = c.get_price_limits(Market.SH, CODE, NAME, q["pre_close"])
+        print(f"代码: {CODE}  名称: {NAME}")
+        print(f"昨收: {q['pre_close']}")
+        print(f"涨停价: {limit_up}")
+        print(f"跌停价: {limit_down}")

examples/06_finance/xdxr_info.py

@@ -1,17 +1,8 @@
 """演示：获取除权除息历史记录。"""
 
-import pandas as pd
-from easy_tdx import TdxClient, Market, XDXR_CATEGORY_NAMES
+from easy_tdx import Market, TdxClient
 
 with TdxClient.from_best_host() as c:
-    records = c.get_xdxr_info(Market.SH, "600519")
-    df = pd.DataFrame([{
-        "日期": f"{r.year}-{r.month:02d}-{r.day:02d}",
-        "类型": XDXR_CATEGORY_NAMES.get(r.category, f"未知({r.category})"),
-        "每股分红(元)": r.fenhong,
-        "送转股比例": r.songzhuangu,
-        "配股价": r.peigujia,
-        "配股比例": r.peigu,
-    } for r in records])
+    df = c.get_xdxr_info(Market.SH, "600519")
     print(f"贵州茅台 除权除息记录，共 {len(df)} 条:")
     print(df.tail(10).to_string(index=False))