feat: 新增各渠道收入占比

data/ppmt/ppmt_channel_share.csv

@@ -0,0 +1,8 @@
+period,retail,online,robot_store,wholesale,total_revenue
+2024H1,57.4,25.9,8.1,8.6,45.59
+2024H2,49.0,35.2,5.4,10.4,84.78
+2024FY,51.9,31.9,6.4,9.8,130.37
+2025H1,49.8,39.6,5.9,4.7,138.75
+2025H2,44.5,47.0,3.7,4.7,232.45
+2025FY,46.5,44.3,4.6,4.7,371.20
+2026H1,53.1,36.2,5.5,5.2,171.74

data/ppmt/ppmt_channel_share_annual.csv

@@ -0,0 +1,3 @@
+period,retail,online,robot_store,wholesale,total_revenue
+2024FY,51.9,31.9,6.4,9.8,130.37
+2025FY,46.5,44.3,4.6,4.7,371.20

data/ppmt/ppmt_channel_share_halfyear.csv

@@ -0,0 +1,6 @@
+period,retail,online,robot_store,wholesale,total_revenue
+2024H1,57.4,25.9,8.1,8.6,45.59
+2024H2,49.0,35.2,5.4,10.4,84.78
+2025H1,49.8,39.6,5.9,4.7,138.75
+2025H2,44.5,47.0,3.7,4.7,232.45
+2026H1,53.1,36.2,5.5,5.2,171.74

data/ppmt/ppmt_inventory.csv

@@ -0,0 +1,17 @@
+period,inventory,yoy
+2017FY,0.16,
+2018FY,0.29,87.0
+2019FY,0.96,231.4
+2020H1,2.24,
+2020FY,2.25,134.0
+2021H1,3.16,41.0
+2021FY,7.89,250.0
+2022H1,9.57,203.0
+2022FY,8.67,9.9
+2023H1,7.59,-20.8
+2023FY,9.05,4.4
+2024H1,9.17,20.8
+2024FY,15.25,68.5
+2025H1,22.74,148.0
+2025FY,54.73,259.0
+2026H1,61.02,168.4

data/ppmt/ppmt_inventory_annual.csv

@@ -0,0 +1,10 @@
+period,inventory,yoy
+2017FY,0.16,
+2018FY,0.29,87.0
+2019FY,0.96,231.4
+2020FY,2.25,134.0
+2021FY,7.89,250.0
+2022FY,8.67,9.9
+2023FY,9.05,4.4
+2024FY,15.25,68.5
+2025FY,54.73,259.0

data/ppmt/ppmt_inventory_halfyear.csv

@@ -0,0 +1,8 @@
+period,inventory,yoy
+2020H1,2.24,
+2021H1,3.16,41.0
+2022H1,9.57,203.0
+2023H1,7.59,-20.8
+2024H1,9.17,20.8
+2025H1,22.74,148.0
+2026H1,61.02,168.4

data/ppmt/ppmt_retail_store_revenue.csv

@@ -0,0 +1,8 @@
+period,china_retail_revenue,china_average_stores,china_per_store,apac_retail_revenue,apac_average_stores,apac_per_store,americas_retail_revenue,americas_average_stores,americas_per_store,europe_other_retail_revenue,europe_other_average_stores,europe_other_per_store
+2024H1,20.04,381.0,526.0,,,,,,,,,
+2024H2,25.97,415.0,625.8,11.83,46.5,2544.1,2.54,16.0,1587.5,1.16,11.5,1008.7
+2024FY,46.01,397.0,1158.9,,,,,,,,,
+2025H1,44.06,437.0,1008.2,14.93,61.5,2427.6,7.37,31.5,2339.7,2.72,16.0,1700.0
+2025H2,56.69,444.0,1276.8,28.26,77.0,3670.1,12.67,52.5,2413.3,5.84,27.0,2163.0
+2025FY,100.75,438.0,2300.2,43.19,69.5,6214.4,20.04,43.0,4660.5,8.56,25.0,3424.0
+2026H1,60.90,450.0,1353.3,17.16,87.5,1961.1,9.03,75.0,1204.0,4.03,40.5,995.1

data/ppmt/ppmt_retail_store_revenue_annual.csv

@@ -0,0 +1,3 @@
+period,china_retail_revenue,china_average_stores,china_per_store,apac_retail_revenue,apac_average_stores,apac_per_store,americas_retail_revenue,americas_average_stores,americas_per_store,europe_other_retail_revenue,europe_other_average_stores,europe_other_per_store
+2024FY,46.01,397.0,1158.9,,,,,,,,,
+2025FY,100.75,438.0,2300.2,43.19,69.5,6214.4,20.04,43.0,4660.5,8.56,25.0,3424.0

data/ppmt/ppmt_retail_store_revenue_halfyear.csv

@@ -0,0 +1,6 @@
+period,china_retail_revenue,china_average_stores,china_per_store,apac_retail_revenue,apac_average_stores,apac_per_store,americas_retail_revenue,americas_average_stores,americas_per_store,europe_other_retail_revenue,europe_other_average_stores,europe_other_per_store
+2024H1,20.04,381.0,526.0,,,,,,,,,
+2024H2,25.97,415.0,625.8,11.83,46.5,2544.1,2.54,16.0,1587.5,1.16,11.5,1008.7
+2025H1,44.06,437.0,1008.2,14.93,61.5,2427.6,7.37,31.5,2339.7,2.72,16.0,1700.0
+2025H2,56.69,444.0,1276.8,28.26,77.0,3670.1,12.67,52.5,2413.3,5.84,27.0,2163.0
+2026H1,60.90,450.0,1353.3,17.16,87.5,1961.1,9.03,75.0,1204.0,4.03,40.5,995.1

data/ppmt/ppmt_robot_store_revenue.csv

@@ -0,0 +1,8 @@
+period,china_robot_revenue,china_average_stores,china_per_store,overseas_robot_revenue,overseas_average_stores,overseas_per_store
+2024H1,3.38,2207.0,15.3,,,,
+2024H2,4.13,2281.5,18.1,0.49,,
+2024FY,7.51,2264.5,33.2,0.80,116.0,69.0
+2025H1,6.78,2388.0,28.4,1.42,146.5,96.9
+2025H2,6.68,2416.5,27.6,2.02,200.5,100.7
+2025FY,13.46,2367.5,56.9,3.44,187.0,184.0
+2026H1,7.79,2439.0,31.9,1.72,293.0,58.7

data/ppmt/ppmt_robot_store_revenue_annual.csv

@@ -0,0 +1,3 @@
+period,china_robot_revenue,china_average_stores,china_per_store,overseas_robot_revenue,overseas_average_stores,overseas_per_store
+2024FY,7.51,2264.5,33.2,0.80,116.0,69.0
+2025FY,13.46,2367.5,56.9,3.44,187.0,184.0

data/ppmt/ppmt_robot_store_revenue_halfyear.csv

@@ -0,0 +1,6 @@
+period,china_robot_revenue,china_average_stores,china_per_store,overseas_robot_revenue,overseas_average_stores,overseas_per_store
+2024H1,3.38,2207.0,15.3,,,,
+2024H2,4.13,2281.5,18.1,0.49,,
+2025H1,6.78,2388.0,28.4,1.42,146.5,96.9
+2025H2,6.68,2416.5,27.6,2.02,200.5,100.7
+2026H1,7.79,2439.0,31.9,1.72,293.0,58.7

data/ppmt/ppmt_stores_retail_share.csv

@@ -0,0 +1,6 @@
+period,global,china,apac,americas,europe,other
+2024H1,457,87.3,8.5,2.2,2.0,0.0
+2024FY,521,82.7,10.4,4.2,2.7,0.0
+2025H1,571,77.6,12.1,7.2,3.2,0.0
+2025FY,630,70.6,13.5,10.2,5.7,0.0
+2026H1,676,67.3,13.3,12.7,6.7,0.0

data/ppmt/ppmt_stores_retail_share_annual.csv

@@ -0,0 +1,3 @@
+period,global,china,apac,americas,europe,other
+2024FY,521,82.7,10.4,4.2,2.7,0.0
+2025FY,630,70.6,13.5,10.2,5.7,0.0

data/ppmt/ppmt_stores_retail_share_halfyear.csv

@@ -0,0 +1,4 @@
+period,global,china,apac,americas,europe,other
+2024H1,457,87.3,8.5,2.2,2.0,0.0
+2025H1,571,77.6,12.1,7.2,3.2,0.0
+2026H1,676,67.3,13.3,12.7,6.7,0.0

data/ppmt/ppmt_working_capital_days.csv

@@ -1,14 +1,14 @@
 period,inventory_days,receivable_days,payable_days,cash_conversion_cycle
-2020H1,101.4,9.6,27.6,83.3
+2020H1,102.0,9.6,27.8,83.8
-2020FY,63.0,8.9,28.4,43.5
+2020FY,63.9,9.0,28.8,44.1
-2021H1,74.3,10.9,40.9,44.3
+2021H1,74.7,10.9,41.1,44.6
-2021FY,105.4,10.0,29.9,85.5
+2021FY,106.9,10.1,30.4,86.6
-2022H1,159.0,11.6,44.7,125.9
+2022H1,159.9,11.7,44.9,126.6
-2022FY,151.8,14.3,46.3,119.8
+2022FY,154.0,14.5,47.0,121.5
-2023H1,131.2,12.9,54.4,89.7
+2023H1,131.9,13.0,54.7,90.2
-2023FY,130.9,14.7,51.2,94.4
+2023FY,132.7,14.9,51.9,95.7
-2024H1,100.0,11.6,54.5,57.1
+2024H1,100.6,11.6,54.8,57.4
-2024FY,101.0,11.0,52.9,59.1
+2024FY,102.4,11.2,53.6,59.9
-2025H1,83.1,9.4,48.8,43.7
+2025H1,83.5,9.5,49.1,43.9
-2025FY,121.6,6.8,36.1,92.3
+2025FY,123.3,6.9,36.6,93.6
-2026H1,200.0,8.1,42.6,165.5
+2026H1,201.2,8.2,42.9,166.5

data/ppmt/rawData/地区渠道收入.csv

@@ -0,0 +1,81 @@
+region,channel,period,revenue
+中国,零售店,2024H1,20.04
+中国,零售店,2024FY,46.01
+中国,零售店,2025H1,44.06
+中国,零售店,2025FY,100.75
+中国,零售店,2026H1,60.90
+中国,机器人商店,2024H1,3.38
+中国,机器人商店,2024FY,7.51
+中国,机器人商店,2025H1,6.78
+中国,机器人商店,2025FY,13.46
+中国,机器人商店,2026H1,7.79
+中国,线上渠道,2024H1,9.41
+中国,线上渠道,2024FY,27.72
+中国,线上渠道,2025H1,29.37
+中国,线上渠道,2025FY,85.22
+中国,线上渠道,2026H1,47.79
+中国,批发及其他,2024H1,2.39
+中国,批发及其他,2024FY,7.63
+中国,批发及其他,2025H1,2.61
+中国,批发及其他,2025FY,9.08
+中国,批发及其他,2026H1,5.53
+亚太,零售店,2024H1,4.85
+亚太,零售店,2024FY,16.68
+亚太,零售店,2025H1,14.93
+亚太,零售店,2025FY,43.19
+亚太,零售店,2026H1,17.16
+亚太,机器人商店,2024H1,0.17
+亚太,机器人商店,2024FY,0.40
+亚太,机器人商店,2025H1,0.33
+亚太,机器人商店,2025FY,0.95
+亚太,机器人商店,2026H1,0.57
+亚太,线上渠道,2024H1,1.65
+亚太,线上渠道,2024FY,9.72
+亚太,线上渠道,2025H1,10.69
+亚太,线上渠道,2025FY,30.53
+亚太,线上渠道,2026H1,6.44
+亚太,批发及其他,2024H1,1.29
+亚太,批发及其他,2024FY,4.30
+亚太,批发及其他,2025H1,2.56
+亚太,批发及其他,2025FY,5.44
+亚太,批发及其他,2026H1,1.59
+美洲,零售店,2024H1,0.87
+美洲,零售店,2024FY,3.41
+美洲,零售店,2025H1,7.37
+美洲,零售店,2025FY,20.04
+美洲,零售店,2026H1,9.03
+美洲,机器人商店,2024H1,0.13
+美洲,机器人商店,2024FY,0.38
+美洲,机器人商店,2025H1,1.05
+美洲,机器人商店,2025FY,2.32
+美洲,机器人商店,2026H1,1.04
+美洲,线上渠道,2024H1,0.64
+美洲,线上渠道,2024FY,3.64
+美洲,线上渠道,2025H1,13.27
+美洲,线上渠道,2025FY,43.54
+美洲,线上渠道,2026H1,7.22
+美洲,批发及其他,2024H1,0.19
+美洲,批发及其他,2024FY,0.58
+美洲,批发及其他,2025H1,0.96
+美洲,批发及其他,2025FY,2.17
+美洲,批发及其他,2026H1,1.62
+欧洲及其他,零售店,2024H1,0.41
+欧洲及其他,零售店,2024FY,1.57
+欧洲及其他,零售店,2025H1,2.72
+欧洲及其他,零售店,2025FY,8.56
+欧洲及其他,零售店,2026H1,4.03
+欧洲及其他,机器人商店,2024H1,0.01
+欧洲及其他,机器人商店,2024FY,0.02
+欧洲及其他,机器人商店,2025H1,0.04
+欧洲及其他,机器人商店,2025FY,0.17
+欧洲及其他,机器人商店,2026H1,0.11
+欧洲及其他,线上渠道,2024H1,0.11
+欧洲及其他,线上渠道,2024FY,0.55
+欧洲及其他,线上渠道,2025H1,1.65
+欧洲及其他,线上渠道,2025FY,5.05
+欧洲及其他,线上渠道,2026H1,0.68
+欧洲及其他,批发及其他,2024H1,0.05
+欧洲及其他,批发及其他,2024FY,0.25
+欧洲及其他,批发及其他,2025H1,0.36
+欧洲及其他,批发及其他,2025FY,0.73
+欧洲及其他,批发及其他,2026H1,0.24

js/charts/index.js

@@ -25,9 +25,14 @@ import { cashflowCompositionChart } from './ppmt_cashflow_composition.js';
 import { workingCapitalDaysChart } from './ppmt_working_capital_days.js';
 import { expenseStructureChart } from './ppmt_expense_structure.js';
 import { channelRevenueChart } from './ppmt_channel_revenue.js';
+import { channelShareChart } from './ppmt_channel_share.js';
 import { storesRetailChart } from './ppmt_stores_retail.js';
 import { storesRobotChart } from './ppmt_stores_robot.js';
 import { regionShareChart } from './ppmt_region_share.js';
+import { inventoryBalanceChart } from './ppmt_inventory.js';
+import { storesRetailShareChart } from './ppmt_stores_retail_share.js';
+import { retailStoreRevenueChart } from './ppmt_retail_store_revenue.js';
+import { robotStoreRevenueChart } from './ppmt_robot_store_revenue.js';
 
 /** 图表构建函数注册表。manifest 只引用这里的 key，不直接引用 JS 函数。 */
 export const chartRegistry = {
@@ -58,9 +63,14 @@ export const chartRegistry = {
   'ppmt-working-capital-days': workingCapitalDaysChart,
   'ppmt-expense-structure': expenseStructureChart,
   'ppmt-channel-revenue': channelRevenueChart,
+  'ppmt-channel-share': channelShareChart,
   'ppmt-stores-retail': storesRetailChart,
   'ppmt-stores-robot': storesRobotChart,
   'ppmt-region-share': regionShareChart,
+  'ppmt-inventory': inventoryBalanceChart,
+  'ppmt-stores-retail-share': storesRetailShareChart,
+  'ppmt-retail-store-revenue': retailStoreRevenueChart,
+  'ppmt-robot-store-revenue': robotStoreRevenueChart,
 };
 
 export function getChartBuilder(key) {

js/charts/ppmt_channel_revenue.js

@@ -31,6 +31,10 @@ export function channelRevenueChart(rows, { width, height, view = 'all' }) {
   const totalMax = Math.max(...rows.map((row) => num(row.total_revenue) || 0));
   const axisMax = NICE_MAX.find((max) => max >= totalMax * 1.02)
     ?? Math.ceil((totalMax * 1.2) / 100) * 100;
+  const yoyValues = col(rows, 'revenue_yoy').filter(Number.isFinite);
+  // 全部／半年视图存在 2022H2 的负增长，右轴需包含负区间，避免折线被 0 轴裁切。
+  const yoyMin = Math.min(0, Math.floor(Math.min(...yoyValues) / 50) * 50);
+  const yoyMax = Math.max(50, Math.ceil(Math.max(...yoyValues) / 50) * 50);
   // 绘图区像素高：画布高 − grid top 145 − grid bottom 90
   const pxPerUnit = (height - LAYOUT.gridTop - 90) / axisMax;
 
@@ -111,8 +115,8 @@ export function channelRevenueChart(rows, { width, height, view = 'all' }) {
         nameGap: 60,
         nameRotate: -90,
         nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
-        min: 0,
+        min: yoyMin,
-        max: 250,
+        max: yoyMax,
         interval: 50,
         axisLabel: { ...axisCommon.axisLabel, formatter: '{value}%' },
         splitLine: { show: false },

js/charts/ppmt_channel_share.js

@@ -0,0 +1,83 @@
+import { col } from '../csv.js';
+import {
+  CHANNEL_COLORS, PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
+  financialViewLabel, barSeries, footnote, watermarks, LAYOUT,
+} from '../theme.js';
+
+const CHANNELS = [
+  { key: 'retail', name: '零售店', color: CHANNEL_COLORS.retail, labelColor: '#fff' },
+  { key: 'online', name: '线上渠道', color: CHANNEL_COLORS.online, labelColor: '#fff' },
+  { key: 'robot_store', name: '机器人商店', color: CHANNEL_COLORS.robotStore, labelColor: '#fff' },
+  { key: 'wholesale', name: '批发及其他', color: CHANNEL_COLORS.wholesale, labelColor: PALETTE.ink },
+];
+
+function sharePoint(value, labelColor) {
+  if (!Number.isFinite(value) || value === 0) return null;
+  // 3.5% 以下的段放不下 11px 段内标签；当前数据最小为 3.7%（2025H2 机器人商店）
+  return {
+    value,
+    label: value >= 3.5
+      ? { position: 'inside', color: labelColor }
+      : { show: false },
+  };
+}
+
+/** 泡泡玛特全渠道收入占比：全部地区合并，每根柱按当期总收入归一化为 100%。 */
+export function channelShareChart(rows, { width, height, view = 'all' }) {
+  const periods = col(rows, 'period');
+  const barWidth = view === 'all' ? 48 : 80;
+
+  return {
+    backgroundColor: '#fff',
+    title: {
+      ...titleStyle,
+      text: `泡泡玛特渠道收入占比（${financialViewLabel(view)}）`,
+      subtext: '全部地区合并；归一化堆叠：每根柱为当期总收入的 100%',
+    },
+    legend: standardLegend(CHANNELS.map((item) => item.name)),
+    tooltip: {
+      trigger: 'axis',
+      axisPointer: { type: 'shadow' },
+      textStyle: { fontFamily: FONT },
+      formatter: (params) => {
+        const row = rows[periods.indexOf(params[0].axisValue)];
+        return `<b>${params[0].axisValue}</b>　总收入 ${row.total_revenue.toFixed(2)} 亿元<br/>${params
+          .filter((item) => item.value !== null)
+          .slice()
+          .reverse()
+          .map((item) => `${item.marker}${item.seriesName}: ${item.value.toFixed(1)}%`)
+          .join('<br/>')}`;
+      },
+    },
+    grid: { left: 78, right: 42, top: LAYOUT.gridTop, bottom: 100 },
+    xAxis: { ...standalonePeriodAxis, data: periods },
+    yAxis: {
+      ...axisCommon,
+      type: 'value',
+      min: 0,
+      max: 100,
+      interval: 20,
+      axisLabel: { ...axisCommon.axisLabel, formatter: '{value}%' },
+    },
+    series: CHANNELS.map((item) => barSeries({
+      name: item.name,
+      data: rows.map((row) => sharePoint(row[item.key], item.labelColor)),
+      color: item.color,
+      barWidth,
+      stack: 'channel-share',
+      label: {
+        show: true,
+        position: 'inside',
+        fontSize: 11,
+        fontFamily: FONT,
+        fontWeight: 500,
+        formatter: (point) => `${point.value.toFixed(1)}%`,
+      },
+      emphasis: { focus: 'series' },
+    })),
+    graphic: [
+      ...watermarks(width, height),
+      footnote('数据来源：泡泡玛特分地区渠道收入披露（中国含港澳台）；H2为单半年（全年−H1）\n线上渠道含抽盒机、天猫、抖音、自研APP及官网等 | @思考的Joey'),
+    ],
+  };
+}

js/charts/ppmt_inventory.js

@@ -0,0 +1,82 @@
+import { col } from '../csv.js';
+import {
+  FINANCIAL_COLORS, PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
+  financialViewLabel, barSeries, lineSeries, footnote, watermarks, LAYOUT,
+} from '../theme.js';
+
+/** 泡泡玛特存货余额与同报告期同比：存货为期末时点数。 */
+export function inventoryBalanceChart(rows, { width, height, view = 'all' }) {
+  const yoy = col(rows, 'yoy').filter(Number.isFinite);
+  const yoyMin = Math.min(0, Math.floor(Math.min(...yoy) / 20) * 20);
+  const yoyMax = Math.max(50, Math.ceil(Math.max(...yoy) / 50) * 50);
+  const barWidth = view === 'all' ? 28.8 : 60.8;
+
+  return {
+    backgroundColor: '#fff',
+    title: {
+      ...titleStyle,
+      text: `泡泡玛特存货余额及同比（${financialViewLabel(view)}）`,
+      subtext: '柱状为报告期末存货余额；折线为同报告期同比（H1 对 H1、全年对全年）',
+    },
+    legend: standardLegend(['存货余额', '存货同比']),
+    grid: { left: 78, right: 82, top: LAYOUT.gridTop, bottom: 90 },
+    tooltip: {
+      trigger: 'axis',
+      axisPointer: { type: 'shadow' },
+      textStyle: { fontFamily: FONT },
+      valueFormatter: (value) => `${value.toFixed(1)}`,
+    },
+    xAxis: { ...standalonePeriodAxis, data: col(rows, 'period') },
+    yAxis: [
+      {
+        ...axisCommon,
+        type: 'value',
+        name: '存货余额（亿元）',
+        nameLocation: 'middle',
+        nameGap: 52,
+        nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
+        min: 0,
+      },
+      {
+        ...axisCommon,
+        type: 'value',
+        name: '同比（%）',
+        nameLocation: 'middle',
+        nameGap: 58,
+        nameRotate: -90,
+        nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
+        min: yoyMin,
+        max: yoyMax,
+        interval: (yoyMax - yoyMin) / 5,
+        axisLabel: { ...axisCommon.axisLabel, formatter: '{value}%' },
+        splitLine: { show: false },
+      },
+    ],
+    series: [
+      {
+        ...barSeries({
+          name: '存货余额',
+          data: col(rows, 'inventory'),
+          color: FINANCIAL_COLORS.investingCashFlow,
+          barWidth,
+          formatter: (point) => point.value.toFixed(1),
+        }),
+        emphasis: { focus: 'series' },
+      },
+      {
+        ...lineSeries({
+          name: '存货同比',
+          data: col(rows, 'yoy'),
+          color: FINANCIAL_COLORS.cashConversion,
+          formatter: (point) => `${point.value.toFixed(1)}%`,
+        }),
+        yAxisIndex: 1,
+        z: 10,
+      },
+    ],
+    graphic: [
+      ...watermarks(width, height),
+      footnote('数据来源：泡泡玛特历年合并资产负债表；存货为报告期末时点数 | @思考的Joey'),
+    ],
+  };
+}

js/charts/ppmt_retail_store_revenue.js

@@ -0,0 +1,110 @@
+import { col } from '../csv.js';
+import {
+  PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
+  financialViewLabel, barSeries, lineSeries, footnote, watermarks, LAYOUT,
+} from '../theme.js';
+
+const REGIONS = [
+  { key: 'china', name: '中国（含港澳台）', color: '#3F7FBE' },
+  { key: 'apac', name: '亚太', color: '#36A28F' },
+  { key: 'americas', name: '美洲', color: '#E4A349' },
+  { key: 'europe_other', name: '欧洲及其他', color: PALETTE.brown },
+];
+
+function yoyByPeriod(rows, key) {
+  const values = new Map(rows.map((row) => [row.period, row[key]]));
+  return rows.map((row) => {
+    const year = Number(row.period.slice(0, 4));
+    const prior = values.get(`${year - 1}${row.period.slice(4)}`);
+    return Number.isFinite(row[key]) && Number.isFinite(prior) && prior !== 0
+      ? (row[key] / prior - 1) * 100
+      : null;
+  });
+}
+
+/** 各地区零售店单店收入：收入 ÷ 期初、期末平均零售店数。 */
+export function retailStoreRevenueChart(rows, { width, height, view = 'all' }) {
+  const values = REGIONS.flatMap((region) => col(rows, `${region.key}_per_store`)).filter(Number.isFinite);
+  const yMax = Math.ceil(Math.max(...values) / 1000) * 1000;
+  const yoySeries = REGIONS.map((region) => ({ ...region, data: yoyByPeriod(rows, `${region.key}_per_store`) }));
+  const yoyValues = yoySeries.flatMap((region) => region.data).filter(Number.isFinite);
+  const yoyMin = Math.min(0, Math.floor(Math.min(...yoyValues) / 50) * 50);
+  const yoyMax = Math.max(50, Math.ceil(Math.max(...yoyValues) / 50) * 50);
+  const legendItems = REGIONS.flatMap((region) => [region.name, `${region.name}同比`]);
+
+  return {
+    backgroundColor: '#fff',
+    title: {
+      ...titleStyle,
+      text: `泡泡玛特各地区零售店单店收入（${financialViewLabel(view)}）`,
+      subtext: '柱状为单店收入；同色虚线为单店收入同比；H2为下半年单期',
+    },
+    legend: standardLegend(legendItems, { itemGap: 18 }),
+    grid: { left: 78, right: 42, top: LAYOUT.gridTop, bottom: 90 },
+    tooltip: {
+      trigger: 'axis',
+      axisPointer: { type: 'shadow' },
+      textStyle: { fontFamily: FONT },
+      formatter: (params) => `<b>${params[0].axisValue}</b><br/>${params
+        .filter((item) => Number.isFinite(item.value))
+        .map((item) => `${item.marker}${item.seriesName}: ${Number(item.value).toFixed(1)}${item.seriesName.endsWith('同比') ? '%' : ' 万元/店'}`)
+        .join('<br/>')}`,
+    },
+    xAxis: { ...standalonePeriodAxis, data: col(rows, 'period') },
+    yAxis: [
+      {
+        ...axisCommon,
+        type: 'value',
+        name: '单店收入（万元/店）',
+        nameLocation: 'middle',
+        nameGap: 58,
+        nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
+        min: 0,
+        max: yMax,
+        interval: yMax / 5,
+      },
+      {
+        ...axisCommon,
+        type: 'value',
+        name: '单店收入同比（%）',
+        nameLocation: 'middle',
+        nameGap: 60,
+        nameRotate: -90,
+        nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
+        min: yoyMin,
+        max: yoyMax,
+        interval: 50,
+        axisLabel: { ...axisCommon.axisLabel, formatter: '{value}%' },
+        splitLine: { show: false },
+      },
+    ],
+    series: [
+      ...REGIONS.map((region) => ({
+        ...barSeries({
+          name: region.name,
+          data: col(rows, `${region.key}_per_store`),
+          color: region.color,
+          barWidth: view === 'all' ? 17 : 34,
+          formatter: (point) => point.value.toFixed(0),
+        }),
+        emphasis: { focus: 'series' },
+      })),
+      ...yoySeries.map((region) => ({
+        ...lineSeries({
+          name: `${region.name}同比`,
+          data: region.data,
+          color: region.color,
+          width: 2,
+          formatter: (point) => `${point.value.toFixed(0)}%`,
+        }),
+        yAxisIndex: 1,
+        lineStyle: { color: region.color, width: 2, type: 'dashed' },
+        z: 10,
+      })),
+    ],
+    graphic: [
+      ...watermarks(width, height),
+      footnote('数据来源：泡泡玛特历年公告；收入仅含“零售店”渠道；H2收入=全年−H1\n2024年海外各区域缺少期初店数，相关单店收入留空 | @思考的Joey'),
+    ],
+  };
+}

js/charts/ppmt_robot_store_revenue.js

@@ -0,0 +1,108 @@
+import { col } from '../csv.js';
+import {
+  PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
+  financialViewLabel, barSeries, lineSeries, footnote, watermarks, LAYOUT,
+} from '../theme.js';
+
+const REGIONS = [
+  { key: 'china', name: '中国（含港澳台）', color: '#71AD81' },
+  { key: 'overseas', name: '海外', color: PALETTE.brown },
+];
+
+function yoyByPeriod(rows, key) {
+  const values = new Map(rows.map((row) => [row.period, row[key]]));
+  return rows.map((row) => {
+    const year = Number(row.period.slice(0, 4));
+    const prior = values.get(`${year - 1}${row.period.slice(4)}`);
+    return Number.isFinite(row[key]) && Number.isFinite(prior) && prior !== 0
+      ? (row[key] / prior - 1) * 100
+      : null;
+  });
+}
+
+/** 中国与海外机器人商店单店收入：收入 ÷ 期初、期末平均机器人商店数。 */
+export function robotStoreRevenueChart(rows, { width, height, view = 'all' }) {
+  const values = REGIONS.flatMap((region) => col(rows, `${region.key}_per_store`)).filter(Number.isFinite);
+  const yMax = Math.ceil(Math.max(...values) / 50) * 50;
+  const yoySeries = REGIONS.map((region) => ({ ...region, data: yoyByPeriod(rows, `${region.key}_per_store`) }));
+  const yoyValues = yoySeries.flatMap((region) => region.data).filter(Number.isFinite);
+  const yoyMin = Math.min(0, Math.floor(Math.min(...yoyValues) / 50) * 50);
+  const yoyMax = Math.max(50, Math.ceil(Math.max(...yoyValues) / 50) * 50);
+  const legendItems = REGIONS.flatMap((region) => [region.name, `${region.name}同比`]);
+
+  return {
+    backgroundColor: '#fff',
+    title: {
+      ...titleStyle,
+      text: `泡泡玛特机器人商店单店收入（${financialViewLabel(view)}）`,
+      subtext: '柱状为单店收入；同色虚线为单店收入同比；H2为下半年单期',
+    },
+    legend: standardLegend(legendItems, { itemGap: 18 }),
+    grid: { left: 78, right: 42, top: LAYOUT.gridTop, bottom: 90 },
+    tooltip: {
+      trigger: 'axis',
+      axisPointer: { type: 'shadow' },
+      textStyle: { fontFamily: FONT },
+      formatter: (params) => `<b>${params[0].axisValue}</b><br/>${params
+        .filter((item) => Number.isFinite(item.value))
+        .map((item) => `${item.marker}${item.seriesName}: ${Number(item.value).toFixed(1)}${item.seriesName.endsWith('同比') ? '%' : ' 万元/店'}`)
+        .join('<br/>')}`,
+    },
+    xAxis: { ...standalonePeriodAxis, data: col(rows, 'period') },
+    yAxis: [
+      {
+        ...axisCommon,
+        type: 'value',
+        name: '单店收入（万元/店）',
+        nameLocation: 'middle',
+        nameGap: 58,
+        nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
+        min: 0,
+        max: yMax,
+        interval: yMax / 5,
+      },
+      {
+        ...axisCommon,
+        type: 'value',
+        name: '单店收入同比（%）',
+        nameLocation: 'middle',
+        nameGap: 60,
+        nameRotate: -90,
+        nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
+        min: yoyMin,
+        max: yoyMax,
+        interval: 50,
+        axisLabel: { ...axisCommon.axisLabel, formatter: '{value}%' },
+        splitLine: { show: false },
+      },
+    ],
+    series: [
+      ...REGIONS.map((region) => ({
+        ...barSeries({
+          name: region.name,
+          data: col(rows, `${region.key}_per_store`),
+          color: region.color,
+          barWidth: view === 'all' ? 28 : 52,
+          formatter: (point) => point.value.toFixed(0),
+        }),
+        emphasis: { focus: 'series' },
+      })),
+      ...yoySeries.map((region) => ({
+        ...lineSeries({
+          name: `${region.name}同比`,
+          data: region.data,
+          color: region.color,
+          width: 2,
+          formatter: (point) => `${point.value.toFixed(0)}%`,
+        }),
+        yAxisIndex: 1,
+        lineStyle: { color: region.color, width: 2, type: 'dashed' },
+        z: 10,
+      })),
+    ],
+    graphic: [
+      ...watermarks(width, height),
+      footnote('数据来源：泡泡玛特历年公告；海外收入=亚太+美洲+欧洲及其他的机器人商店收入；H2收入=全年−H1\n2024H1海外期末机器人商店数未披露，相关单店收入留空 | @思考的Joey'),
+    ],
+  };
+}

js/charts/ppmt_stores_retail_share.js

@@ -0,0 +1,83 @@
+import { col } from '../csv.js';
+import {
+  PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
+  financialViewLabel, barSeries, footnote, watermarks, LAYOUT,
+} from '../theme.js';
+
+/** 泡泡玛特分地区零售门店占比：每根柱标准化为各期末全球门店数的 100%。 */
+const REGIONS = [
+  { key: 'china', name: '中国（含港澳台）', color: '#3F7FBE', labelColor: '#fff' },
+  { key: 'apac', name: '亚太', color: '#36A28F', labelColor: '#fff' },
+  { key: 'americas', name: '美洲', color: '#E4A349', labelColor: PALETTE.ink },
+  { key: 'europe', name: '欧洲', color: PALETTE.brown, labelColor: '#fff' },
+  { key: 'other', name: '其他', color: PALETTE.sand, labelColor: PALETTE.ink },
+];
+
+function sharePoint(value, labelColor) {
+  if (!Number.isFinite(value) || value === 0) return null;
+  return {
+    value,
+    label: value >= 5
+      ? { position: 'inside', color: labelColor }
+      : { show: false },
+  };
+}
+
+export function storesRetailShareChart(rows, { width, height, view = 'all' }) {
+  const periods = col(rows, 'period');
+  const barWidth = view === 'all' ? 48 : 80;
+
+  return {
+    backgroundColor: '#fff',
+    title: {
+      ...titleStyle,
+      text: `泡泡玛特分地区零售门店数量占比（${financialViewLabel(view)}）`,
+      subtext: '归一化堆叠：每根柱为当期末全球零售门店数的 100%',
+    },
+    legend: standardLegend(REGIONS.map((item) => item.name), { itemGap: 20 }),
+    tooltip: {
+      trigger: 'axis',
+      axisPointer: { type: 'shadow' },
+      textStyle: { fontFamily: FONT },
+      formatter: (params) => {
+        const row = rows[periods.indexOf(params[0].axisValue)];
+        return `<b>${params[0].axisValue}</b>　全球合计 ${row.global} 家<br/>${params
+          .filter((item) => item.value !== null)
+          .slice()
+          .reverse()
+          .map((item) => `${item.marker}${item.seriesName}: ${item.value.toFixed(1)}%`)
+          .join('<br/>')}`;
+      },
+    },
+    grid: { left: 78, right: 42, top: LAYOUT.gridTop, bottom: 100 },
+    xAxis: { ...standalonePeriodAxis, data: periods },
+    yAxis: {
+      ...axisCommon,
+      type: 'value',
+      min: 0,
+      max: 100,
+      interval: 20,
+      axisLabel: { ...axisCommon.axisLabel, formatter: '{value}%' },
+    },
+    series: REGIONS.map((item) => barSeries({
+      name: item.name,
+      data: rows.map((row) => sharePoint(row[item.key], item.labelColor)),
+      color: item.color,
+      barWidth,
+      stack: 'stores-retail-share',
+      label: {
+        show: true,
+        position: 'inside',
+        fontSize: 11,
+        fontFamily: FONT,
+        fontWeight: 500,
+        formatter: (point) => `${point.value.toFixed(1)}%`,
+      },
+      emphasis: { focus: 'series' },
+    })),
+    graphic: [
+      ...watermarks(width, height),
+      footnote('数据来源：泡泡玛特历年公告；门店数为各报告期末时点数\n中国=中国内地+港澳台；其他=全球合计−中国−亚太−美洲−欧洲 | @思考的Joey'),
+    ],
+  };
+}

js/charts/ppmt_working_capital_days.js

@@ -36,7 +36,7 @@ export function workingCapitalDaysChart(rows, { width, height }) {
     title: {
       ...titleStyle,
       text: '泡泡玛特营运资本效率',
-      subtext: '现金转换周期 = 存货周转天数 + 应收周转天数 − 应付周转天数',
+      subtext: '现金转换周期 = 存货周转天数 + 应收周转天数 − 应付周转天数（中报按181天、年报按365天）',
     },
     legend: { ...legendStyle, top: LAYOUT.legendTop, data: SERIES.map((item) => item.name) },
     grid: { left: 78, right: 42, top: LAYOUT.gridTop, bottom: 90 },
@@ -78,7 +78,7 @@ export function workingCapitalDaysChart(rows, { width, height }) {
     })),
     graphic: [
       ...watermarks(width, height),
-      footnote('数据来源：泡泡玛特财务指标（合并报表）| @思考的Joey'),
+      footnote('数据来源：泡泡玛特财务指标（合并报表）；原始180/360天口径已换算为181/365天 | @思考的Joey'),
     ],
   };
 }

manifest.json

@@ -12,6 +12,7 @@
         "ppmt-bridge": { "key": "ppmt-bridge", "title": "净利率同比拆解", "csv": "data/ppmt/ppmt_margin_bridge.csv", "height": 700, "filename": "泡泡玛特净利率同比拆解" },
         "ppmt-margins": { "key": "ppmt-margins", "title": "利润率与费用率拆解", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_margins.csv", "annual": "data/ppmt/ppmt_margins_annual.csv", "halfyear": "data/ppmt/ppmt_margins_halfyear.csv" }, "height": 680, "filename": "泡泡玛特利润率与费用率拆解" },
         "ppmt-assets": { "key": "ppmt-assets", "title": "资产结构演变", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_assets.csv", "annual": "data/ppmt/ppmt_assets_annual.csv", "halfyear": "data/ppmt/ppmt_assets_halfyear.csv" }, "height": 680, "filename": "泡泡玛特资产结构" },
+        "ppmt-inventory": { "key": "ppmt-inventory", "title": "存货余额及同比", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_inventory.csv", "annual": "data/ppmt/ppmt_inventory_annual.csv", "halfyear": "data/ppmt/ppmt_inventory_halfyear.csv" }, "height": 680, "filename": "泡泡玛特存货余额及同比" },
         "ppmt-ip": { "key": "ppmt-ip", "title": "主要 IP 收入趋势", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_ip.csv", "annual": "data/ppmt/ppmt_ip_annual.csv", "halfyear": "data/ppmt/ppmt_ip_halfyear.csv" }, "height": 720, "filename": "泡泡玛特IP收入趋势" },
         "ppmt-ip-share": { "key": "ppmt-ip-share", "title": "主要 IP 收入占比", "csv": "data/ppmt/ppmt_ip_share_2026h1.csv", "height": 720, "filename": "泡泡玛特IP收入占比2026H1" },
         "ppmt-ip-share-history": { "key": "ppmt-ip-share-history", "title": "各 IP 半年收入占比", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_ip_share_history.csv", "annual": "data/ppmt/ppmt_ip_share_history_annual.csv", "halfyear": "data/ppmt/ppmt_ip_share_history_halfyear.csv" }, "height": 700, "filename": "泡泡玛特各IP半年收入占比" },
@@ -26,17 +27,22 @@
         "ppmt-working-capital-days": { "key": "ppmt-working-capital-days", "title": "营运资本效率", "csv": "data/ppmt/ppmt_working_capital_days.csv", "height": 700, "filename": "泡泡玛特营运资本效率" },
         "ppmt-expense-structure": { "key": "ppmt-expense-structure", "title": "费用结构与费用率", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_expense_structure.csv", "annual": "data/ppmt/ppmt_expense_structure_annual.csv", "halfyear": "data/ppmt/ppmt_expense_structure_halfyear.csv" }, "height": 700, "filename": "泡泡玛特费用结构与费用率" },
         "ppmt-channel-revenue": { "key": "ppmt-channel-revenue", "title": "渠道收入结构与增速", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_channel_revenue.csv", "annual": "data/ppmt/ppmt_channel_revenue_annual.csv", "halfyear": "data/ppmt/ppmt_channel_revenue_halfyear.csv" }, "height": 720, "filename": "泡泡玛特渠道收入结构与增速" },
+        "ppmt-channel-share": { "key": "ppmt-channel-share", "title": "渠道收入占比", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_channel_share.csv", "annual": "data/ppmt/ppmt_channel_share_annual.csv", "halfyear": "data/ppmt/ppmt_channel_share_halfyear.csv" }, "height": 680, "filename": "泡泡玛特渠道收入占比" },
         "ppmt-stores-retail": { "key": "ppmt-stores-retail", "title": "分地区零售门店数量与同比增速", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_stores_retail.csv", "annual": "data/ppmt/ppmt_stores_retail_annual.csv", "halfyear": "data/ppmt/ppmt_stores_retail_halfyear.csv" }, "height": 680, "filename": "泡泡玛特分地区零售门店数量与同比增速" },
+        "ppmt-stores-retail-share": { "key": "ppmt-stores-retail-share", "title": "分地区零售门店数量占比", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_stores_retail_share.csv", "annual": "data/ppmt/ppmt_stores_retail_share_annual.csv", "halfyear": "data/ppmt/ppmt_stores_retail_share_halfyear.csv" }, "height": 680, "filename": "泡泡玛特分地区零售门店数量占比" },
+        "ppmt-retail-store-revenue": { "key": "ppmt-retail-store-revenue", "title": "各地区零售店单店收入", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_retail_store_revenue.csv", "annual": "data/ppmt/ppmt_retail_store_revenue_annual.csv", "halfyear": "data/ppmt/ppmt_retail_store_revenue_halfyear.csv" }, "height": 680, "filename": "泡泡玛特各地区零售店单店收入" },
         "ppmt-stores-robot": { "key": "ppmt-stores-robot", "title": "分地区机器人商店数量与同比增速", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_stores_robot.csv", "annual": "data/ppmt/ppmt_stores_robot_annual.csv", "halfyear": "data/ppmt/ppmt_stores_robot_halfyear.csv" }, "height": 680, "filename": "泡泡玛特分地区机器人商店数量与同比增速" },
+        "ppmt-robot-store-revenue": { "key": "ppmt-robot-store-revenue", "title": "机器人商店单店收入", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_robot_store_revenue.csv", "annual": "data/ppmt/ppmt_robot_store_revenue_annual.csv", "halfyear": "data/ppmt/ppmt_robot_store_revenue_halfyear.csv" }, "height": 680, "filename": "泡泡玛特机器人商店单店收入" },
         "ppmt-region-share": { "key": "ppmt-region-share", "title": "分地区营收占比", "defaultView": "all", "views": { "all": "data/ppmt/ppmt_region_share.csv", "annual": "data/ppmt/ppmt_region_share_annual.csv", "halfyear": "data/ppmt/ppmt_region_share_halfyear.csv" }, "height": 680, "filename": "泡泡玛特分地区营收占比" }
       },
       "tabs": [
         { "id": "overview", "name": "概览", "chartRefs": ["ppmt-growth", "ppmt-profit", "ppmt-ip-share", "ppmt-region-channel"] },
         { "id": "profitability", "name": "盈利能力", "chartRefs": ["ppmt-growth", "ppmt-core-profit", "ppmt-core-margin", "ppmt-bridge", "ppmt-sankey", "ppmt-cash-conversion", "ppmt-cashflow-composition"] },
         { "id": "expense", "name": "费用率", "chartRefs": ["ppmt-margins", "ppmt-expense-structure"] },
-        { "id": "balance-sheet", "name": "资产负债", "chartRefs": ["ppmt-assets", "ppmt-liquidity-working-capital", "ppmt-working-capital-days"] },
+        { "id": "balance-sheet", "name": "资产负债", "chartRefs": ["ppmt-assets", "ppmt-inventory", "ppmt-liquidity-working-capital", "ppmt-working-capital-days"] },
         { "id": "ip-category", "name": "IP 与品类", "chartRefs": ["ppmt-ip", "ppmt-ip-share", "ppmt-ip-share-history", "ppmt-ip-ex-monsters", "ppmt-category"] },
-        { "id": "region-channel", "name": "区域渠道", "chartRefs": ["ppmt-region-channel", "ppmt-region-yoy", "ppmt-region-yoy-timeseries", "ppmt-channel-revenue", "ppmt-stores-retail", "ppmt-stores-robot", "ppmt-region-share"] }
+        { "id": "region-channel", "name": "区域渠道", "chartRefs": ["ppmt-region-channel", "ppmt-region-yoy", "ppmt-region-yoy-timeseries", "ppmt-channel-revenue", "ppmt-channel-share", "ppmt-stores-retail", "ppmt-stores-retail-share", "ppmt-stores-robot", "ppmt-region-share"] },
+        { "id": "store-revenue", "name": "单店收入", "chartRefs": ["ppmt-retail-store-revenue", "ppmt-robot-store-revenue"] }
       ]
     },
     {

scripts/normalize_ppmt_financials.mjs

@@ -4,6 +4,7 @@ import { fileURLToPath } from 'node:url';
 
 const ROOT = path.resolve(path.dirname(fileURLToPath(import.meta.url)), '..');
 const RAW_DIR = path.join(ROOT, 'data/ppmt/raw');
+const RAWDATA_DIR = path.join(ROOT, 'data/ppmt/rawData');
 const OUTPUT_DIR = path.join(ROOT, 'data/ppmt');
 
 const FILES = {
@@ -184,13 +185,21 @@ const workingCapitalDaysRows = indicators.dates.map((date, index) => ({
 })).filter((item) => (
   item.date >= '2020-01-01'
   && item.inventory !== null && item.receivable !== null && item.payable !== null
-)).map((item) => [
+)).map((item) => {
-  periodFor(item.date),
+  const period = periodFor(item.date);
-  item.inventory.toFixed(1),
+  // 原始指标表按半年 180 天、全年 360 天计算；此处统一换算为自然日 181/365 天。
-  item.receivable.toFixed(1),
+  const factor = period.endsWith('H1') ? 181 / 180 : 365 / 360;
-  item.payable.toFixed(1),
+  const inventory = item.inventory * factor;
-  (item.inventory + item.receivable - item.payable).toFixed(1),
+  const receivable = item.receivable * factor;
-]).reverse();
+  const payable = item.payable * factor;
+  return [
+    period,
+    inventory.toFixed(1),
+    receivable.toFixed(1),
+    payable.toFixed(1),
+    (inventory + receivable - payable).toFixed(1),
+  ];
+}).reverse();
 
 writeCSV('ppmt_working_capital_days.csv', [
   'period', 'inventory_days', 'receivable_days', 'payable_days', 'cash_conversion_cycle',
@@ -341,9 +350,9 @@ function yoyFor(rows, key, outputKey = key) {
   });
 }
 
-function toOutputRows(rows, headers, digits = {}) {
+function toOutputRows(rows, headers, digits = {}, startYear = OUTPUT_START_YEAR) {
   return rows
-    .filter((row) => Number(row.period.slice(0, 4)) >= OUTPUT_START_YEAR)
+    .filter((row) => Number(row.period.slice(0, 4)) >= startYear)
     .map((row) => headers.map((header) => {
       if (header === 'period') return row.period;
       const value = row[header];
@@ -351,14 +360,14 @@ function toOutputRows(rows, headers, digits = {}) {
     }));
 }
 
-function writeViewFiles(base, headers, views, digits) {
+function writeViewFiles(base, headers, views, digits, startYear = OUTPUT_START_YEAR) {
   const filenames = {
     all: `${base}.csv`,
     annual: `${base}_annual.csv`,
     halfyear: `${base}_halfyear.csv`,
   };
   Object.entries(filenames).forEach(([view, filename]) => {
-    writeCSV(filename, headers, toOutputRows(views[view], headers, digits));
+    writeCSV(filename, headers, toOutputRows(views[view], headers, digits, startYear));
   });
 }
 
@@ -557,8 +566,8 @@ writeViewFiles('ppmt_expense_structure', ['period', 'sales_expense', 'admin_expe
   sales_expense: 2, admin_expense: 2, financial_expense: 2, four_expense_rate: 1,
 });
 
-function readRuntimeRows(filename) {
+function readCsvRows(dir, filename) {
-  const [header, ...lines] = fs.readFileSync(path.join(OUTPUT_DIR, filename), 'utf8').trim().split(/\r?\n/);
+  const [header, ...lines] = fs.readFileSync(path.join(dir, filename), 'utf8').trim().split(/\r?\n/);
   const headers = header.split(',');
   return lines.map((line) => Object.fromEntries(line.split(',').map((cell, index) => {
     const value = Number(cell);
@@ -566,6 +575,10 @@ function readRuntimeRows(filename) {
   })));
 }
 
+function readRuntimeRows(filename) {
+  return readCsvRows(OUTPUT_DIR, filename);
+}
+
 function writeRuntimeViews(base, headers, views, digits = {}) {
   writeViewFiles(base, headers, views, digits);
 }
@@ -614,6 +627,31 @@ writeRuntimeViews('ppmt_category', ['period', 'plush', 'figure', 'mega', 'other'
   plush: 2, figure: 2, mega: 2, other: 2,
 });
 
+// 2024H1 起门店披露可将中国内地与港澳台合并，并按全球总数归一化为地区占比。
+const retailStoreRows = readRuntimeRows('ppmt_stores_retail.csv');
+const retailStoreShareViews = { all: [], annual: [], halfyear: [] };
+retailStoreRows.filter((row) => (
+  Number(row.period.slice(0, 4)) >= 2024
+  && ['mainland', 'hkmtw', 'apac', 'americas', 'europe', 'global'].every((key) => Number.isFinite(row[key]))
+)).forEach((row) => {
+  const china = row.mainland + row.hkmtw;
+  const other = row.global - china - row.apac - row.americas - row.europe;
+  const shareRow = {
+    period: row.period,
+    global: row.global,
+    china: china / row.global * 100,
+    apac: row.apac / row.global * 100,
+    americas: row.americas / row.global * 100,
+    europe: row.europe / row.global * 100,
+    other: other / row.global * 100,
+  };
+  retailStoreShareViews.all.push(shareRow);
+  retailStoreShareViews[row.period.endsWith('FY') ? 'annual' : 'halfyear'].push(shareRow);
+});
+writeRuntimeViews('ppmt_stores_retail_share', ['period', 'global', 'china', 'apac', 'americas', 'europe', 'other'], retailStoreShareViews, {
+  global: 0, china: 1, apac: 1, americas: 1, europe: 1, other: 1,
+});
+
 // 资产负债表为时点指标：H2 是年末时点，而非“全年累计”。
 function buildSnapshotViews(base, headers, digits) {
   const source = readRuntimeRows(`${base}.csv`);
@@ -643,4 +681,67 @@ buildSnapshotViews('ppmt_liquidity_working_capital', ['period', 'cash', 'total_l
   cash: 2, total_liabilities: 2, net_working_capital: 2,
 });
 
+// 存货为资产负债表期末时点数：半年仅取中报期末，年度仅取年报期末。
+// 同比严格按相同报告期（H1 对 H1、FY 对 FY）计算，不把中报与年报交叉比较。
+const inventoryBalances = row(balance, '存货');
+const inventoryViews = { all: [], annual: [], halfyear: [] };
+balance.dates.map((date, index) => ({
+  date,
+  inventory: inventoryBalances[index],
+})).filter(({ date, inventory }) => (
+  date >= '2017-01-01' && inventory > 0 && (date.endsWith('-06-30') || date.endsWith('-12-31'))
+)).sort((a, b) => a.date.localeCompare(b.date)).forEach(({ date, inventory }) => {
+  const row = { period: periodFor(date), inventory: inventory / HUNDRED_MILLION };
+  inventoryViews.all.push(row);
+  inventoryViews[row.period.endsWith('FY') ? 'annual' : 'halfyear'].push(row);
+});
+Object.keys(inventoryViews).forEach((view) => {
+  inventoryViews[view] = yoyFor(inventoryViews[view], 'inventory', 'yoy');
+});
+writeViewFiles('ppmt_inventory', ['period', 'inventory', 'yoy'], inventoryViews, {
+  inventory: 2, yoy: 1,
+}, 2017);
+
 console.log('已生成第二批连续图表的全部、年度、半年 CSV。');
+
+// 渠道收入占比：底表 data/ppmt/rawData/地区渠道收入.csv 整理自
+// 泡泡玛特-rawdata.xlsx「各地区渠道收入」工作表（中国含港澳台的四地区 × 四渠道明细）。
+// 全球合计 = 四地区加总；披露口径只有 H1 与全年，H2 单半年 = 全年 − H1；
+// 占比在金额视图之后计算，按当期四渠道合计归一化，不可用占比直接相减。
+const CHANNEL_NAME_TO_KEY = {
+  零售店: 'retail',
+  机器人商店: 'robot_store',
+  线上渠道: 'online',
+  批发及其他: 'wholesale',
+};
+const channelRevenueByPeriod = new Map();
+readCsvRows(RAWDATA_DIR, '地区渠道收入.csv').forEach(({ region, channel, period, revenue }) => {
+  const key = CHANNEL_NAME_TO_KEY[channel];
+  if (!key) throw new Error(`地区渠道收入底表存在未知渠道：${channel}`);
+  if (!period || !Number.isFinite(revenue)) throw new Error(`地区渠道收入底表行不完整：${region} ${channel} ${period} ${revenue}`);
+  if (!channelRevenueByPeriod.has(period)) {
+    channelRevenueByPeriod.set(period, { retail: 0, online: 0, robot_store: 0, wholesale: 0 });
+  }
+  channelRevenueByPeriod.get(period)[key] += revenue;
+});
+
+const channelAmountViews = buildViews((year, type) => {
+  const bucket = channelRevenueByPeriod.get(type === 'H1' ? `${year}H1` : `${year}FY`);
+  return bucket ?? null;
+});
+const channelShareViews = Object.fromEntries(Object.entries(channelAmountViews).map(([view, rows]) => [
+  view,
+  rows.map(({ period, ...amounts }) => {
+    const total = Object.values(amounts).reduce((sum, value) => sum + value, 0);
+    return {
+      period,
+      ...Object.fromEntries(Object.entries(amounts).map(([key, value]) => [key, value / total * 100])),
+      total_revenue: total,
+    };
+  }),
+]));
+writeRuntimeViews('ppmt_channel_share', ['period', 'retail', 'online', 'robot_store', 'wholesale', 'total_revenue'], channelShareViews, {
+  retail: 1, online: 1, robot_store: 1, wholesale: 1, total_revenue: 2,
+});
+
+console.log('已生成渠道收入占比的全部、年度、半年 CSV。');