vault backup: 2026-11-06 09:29:04

.claudian/sessions/conv-1793925217144-zpzd4w5rp.meta.json

@@ -4,6 +4,20 @@
   "title": "Fix garbled text in document display",
   "titleGenerationStatus": "success",
   "createdAt": 1793925217144,
-  "updatedAt": 1793925225872,
-  "sessionId": null
+  "updatedAt": 1793928017499,
+  "lastResponseAt": 1793928017499,
+  "sessionId": "faab80b4-230c-4c59-9296-ba57e6af8986",
+  "providerState": {
+    "providerSessionId": "faab80b4-230c-4c59-9296-ba57e6af8986"
+  },
+  "usage": {
+    "model": "glm-5",
+    "inputTokens": 622,
+    "cacheCreationInputTokens": 0,
+    "cacheReadInputTokens": 67840,
+    "contextWindow": 200000,
+    "contextTokens": 68462,
+    "percentage": 34,
+    "contextWindowIsAuthoritative": true
+  }
 }

.obsidian/workspace.json

@@ -13,12 +13,12 @@
             "state": {
               "type": "markdown",
               "state": {
-                "file": "百家/野生动物+物理地形.md",
+                "file": "思睿/身高/第一医院/第一医院检查总结.md",
                 "mode": "source",
                 "source": false
               },
               "icon": "lucide-file",
-              "title": "野生动物+物理地形"
+              "title": "第一医院检查总结"
             }
           }
         ]
@@ -197,26 +197,28 @@
       "realclaudian:Open Claudian": false
     }
   },
-  "active": "80266ee6e0ac306d",
+  "active": "fdbcd1b46c89bc2a",
   "lastOpenFiles": [
+    "妹妹/妹妹身高.md",
     "思睿/身高/综合健康复诊分析.md",
     "思睿/身高/综合健康评估总结.md",
-    "generate_docs.py",
+    "思睿/身高/综合健康评估总结.md.tmp.19184.eef11a9104a9",
+    "思睿/哥哥身高.md",
+    "妹妹/妹妹身高.md.corrupt-20260916",
+    "思睿/哥哥身高.md.corrupt-20260916",
+    "思睿/身高/综合健康评估总结.md.corrupt-20260916",
+    "思睿/身高/综合健康复诊分析.md.corrupt-20260916",
+    "百家/analyze_baijiahao.py",
+    "思睿/身高/第一医院/病例/2026-10-19.pdf",
+    "思睿/身高/第一医院/病例/2026-03-07.pdf",
+    "思睿/身高/第一医院/病例/2026-07-18.pdf",
+    "思睿/身高/第一医院/病例/2026-07-11.pdf",
     "百家/野生动物+物理地形.md",
     "百家/code_artifact.md",
-    "百家",
-    "新建文件夹",
-    "temp_test_zip2.py",
-    "temp_test_zip.py",
-    "temp_check_zip.py",
-    "temp_check_zst.py",
     "思睿/思睿资料核对与待办清单.md",
-    "思睿/哥哥身高.md",
     "思睿/初中/观音山音乐学校分析.md",
     "思睿/身高/第一医院/第一医院检查总结.md",
-    "思睿/七年级/作文/照顾妹妹的一天-作文批改打印版.pdf",
     "思睿/七年级/作文/照顾妹妹的一天--原文.md",
-    "妹妹/妹妹身高.md",
     "思睿/身高/第一医院/报告/20261019报告/extracted_images/血常规 20261019_p1_img2.png",
     "思睿/身高/第一医院/报告/20261019报告/extracted_images/血常规 20261019_p1_img1.png",
     "思睿/身高/第一医院/报告/20261019报告/extracted_images/胰岛素测定 20261019_p1_img2.png",
@@ -227,8 +229,6 @@
     "思睿/身高/第一医院/报告/20261019报告/extracted_images/常规生化全套检查 20261019_p2_img1.png",
     "思睿/身高/第一医院/报告/20261019报告/extracted_images/常规生化全套检查 20261019_p1_img2.png",
     "思睿/身高/第一医院/报告/20261019报告/extracted_images/常规生化全套检查 20261019_p1_img1.png",
-    "思睿/身高/第一医院/报告/20261019报告/extracted_images",
-    "test.txt",
     "思睿/身高/第一医院/temp_zip_check/第一医院检查总结.md",
     "小鱼/闲鱼数据分析_2026-11-03.md",
     "小鱼/闲鱼选品与运营指导_2026-11-03.md",

百家/analyze_baijiahao.py

@@ -0,0 +1,75 @@
+# -*- coding: utf-8 -*-
+# 百家号 39 条视频数据归因分析：按题材分类汇总 + 互动率/点击率 + 输出 Excel 归因表
+import sys
+import pandas as pd
+import openpyxl
+
+sys.stdout.reconfigure(encoding="utf-8")
+
+df = pd.read_excel(r"E:\Download\单篇数据.xlsx", sheet_name="data")
+df.columns = [str(c).strip() for c in df.columns]
+
+# 题材人工归类（基于标题与策略文档对照）
+CAT = {
+    "大角羊IP（悬崖物理反杀）": ["悬崖冰桥上的极限遭遇战", "大角羊被狼群逼入绝境，竟靠这一招",
+                                "大角羊卡住悬崖窄道", "悬崖之巅的生死角逐", "罕见野外抓拍：大角羊",
+                                "绝地反击！大角羊引发落石"],
+    "农家院保卫战（护崽情感）": ["千万别惹看家大鹅", "迷你黄鼠狼进院偷小鸡", "黄鼠狼进院偷袭小鸡"],
+    "绝对防御（连XX都不敢惹）": ["为什么连鳄鱼都不敢惹河马", "为什么连狮子都忌惮非洲水牛",
+                                 "连狮子都咬不穿的防御", "穿山甲偶遇小花豹", "连狮子都扎嘴的豪猪",
+                                 "为什么说一猪二熊三老虎", "水牛轰然倒地"],
+    "高山其他蹄类（物理系）": ["物理学不存在了", "盘羊高处蹬落碎冰", "雪羊占据陡坡高地",
+                              "绝壁上的", "野狼仰攻野牦牛", "大自然的天然溜冰场", "雪地追击变成花样滑冰"],
+    "雪兔压强": ["受力面积的降维打击", "为什么雪兔在厚雪地里跑不陷脚"],
+    "北极狐走位": ["饥饿北极熊雪地狂追北极狐", "急眼了！北极熊狂追小狐狸"],
+    "水下题材": ["原来真有动物会用工具", "千万别和企鹅比灵活", "千万别惹"],
+    "萌宠表情/搞笑": ["高空猛禽突然掠过，兔狲", "谁能拒绝一只戴着派对帽的小猫咪", "水豚被大鸟"],
+    "其他（掠食视角/整蛊）": ["当北极熊在碎冰区发起冲锋", "大自然的", "雪原上的三方博弈"],
+}
+
+def cat_of(title):
+    for c, keys in CAT.items():
+        if any(k in title for k in keys):
+            return c
+    return "未分类"
+
+df["题材"] = df["标题"].apply(cat_of)
+df["点击转化率"] = (df["阅读量"] / df["推荐量"]).round(3)
+df["点赞率%"] = (df["点赞量"] / df["阅读量"].clip(lower=1) * 100).round(2)
+
+g = df.groupby("题材").agg(
+    条数=("标题", "count"),
+    总阅读=("阅读量", "sum"),
+    平均阅读=("阅读量", "mean"),
+    最好成绩=("阅读量", "max"),
+    总推荐=("推荐量", "sum"),
+    点击转化率=("点击转化率", "mean"),
+    总点赞=("点赞量", "sum"),
+    总评论=("评论量", "sum"),
+).round(1).sort_values("总阅读", ascending=False)
+
+print("=" * 88)
+print(g.to_string())
+print("=" * 88)
+
+top5 = df.nlargest(5, "阅读量")[["标题", "发布时间", "阅读量", "推荐量", "点赞量", "题材"]]
+print("\nTOP5 爆款：")
+print(top5.to_string(index=False))
+
+bottom5 = df.nsmallest(5, "阅读量")[["标题", "发布时间", "阅读量", "推荐量", "题材"]]
+print("\nBOTTOM5 扑街：")
+print(bottom5.to_string(index=False))
+
+# 违规词扫描（文档明令禁止）
+banned = ["实拍", "抓拍", "监控拍", "彻底绝望", "陷入绝望", "最高境界"]
+hits = df[df["标题"].str.contains("|".join(banned))][["标题", "阅读量"]]
+print("\n违规词命中（文档红线，需改标题）：")
+print(hits.to_string(index=False) if len(hits) else "无")
+
+# 输出归因表 Excel
+out = r"F:\AI\Obsidian Home\百家\单篇数据归因分析.xlsx"
+with pd.ExcelWriter(out, engine="xlsxwriter") as w:
+    df.to_excel(w, sheet_name="逐条明细", index=False)
+    g.reset_index().to_excel(w, sheet_name="题材汇总", index=False)
+    top5.to_excel(w, sheet_name="TOP5爆款", index=False)
+print(f"\nsaved: {out}")

百家/read_baijiahao_xlsx.py

@@ -0,0 +1,28 @@
+# -*- coding: utf-8 -*-
+# 读取百家号后台导出的《单篇数据.xlsx》：打印所有 sheet、表头与数据行
+import sys
+import openpyxl
+
+sys.stdout.reconfigure(encoding="utf-8")
+path = r"E:\Download\单篇数据.xlsx"
+
+wb = openpyxl.load_workbook(path, data_only=True, read_only=True)
+print(f"file: {path}")
+print(f"sheets: {wb.sheetnames}")
+
+for ws in wb.worksheets:
+    print(f"\n=== SHEET: {ws.title}  dims={ws.max_row} rows x {ws.max_column} cols ===")
+    empty_streak = 0
+    for i, row in enumerate(ws.iter_rows(values_only=True), 1):
+        vals = ["" if v is None else str(v).replace("\n", "\\n") for v in row]
+        if not any(vals):
+            empty_streak += 1
+            if empty_streak > 3:
+                continue
+        else:
+            empty_streak = 0
+        print(f"[{i}] " + " | ".join(vals))
+        if i >= 80:
+            print("...(over 80 rows, truncated for inspection)")
+            break
+wb.close()