feat: 更新泡泡玛特图表,加入单店收入
This commit is contained in:
@@ -0,0 +1,17 @@
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period,inventory,yoy
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2017FY,0.16,
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2018FY,0.29,87.0
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2019FY,0.96,231.4
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2020H1,2.24,
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2020FY,2.25,134.0
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2021H1,3.16,41.0
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2021FY,7.89,250.0
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2022H1,9.57,203.0
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2022FY,8.67,9.9
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2023H1,7.59,-20.8
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2023FY,9.05,4.4
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2024H1,9.17,20.8
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2024FY,15.25,68.5
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2025H1,22.74,148.0
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2025FY,54.73,259.0
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2026H1,61.02,168.4
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@@ -0,0 +1,10 @@
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period,inventory,yoy
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2017FY,0.16,
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2018FY,0.29,87.0
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2019FY,0.96,231.4
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2020FY,2.25,134.0
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2021FY,7.89,250.0
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2022FY,8.67,9.9
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2023FY,9.05,4.4
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2024FY,15.25,68.5
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2025FY,54.73,259.0
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@@ -0,0 +1,8 @@
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period,inventory,yoy
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2020H1,2.24,
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2021H1,3.16,41.0
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2022H1,9.57,203.0
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2023H1,7.59,-20.8
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2024H1,9.17,20.8
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2025H1,22.74,148.0
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2026H1,61.02,168.4
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@@ -0,0 +1,8 @@
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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
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2024H1,20.04,381.0,526.0,,,,,,,,,
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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
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2024FY,46.01,397.0,1158.9,,,,,,,,,
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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
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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
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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
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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
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@@ -0,0 +1,3 @@
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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
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2024FY,46.01,397.0,1158.9,,,,,,,,,
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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
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@@ -0,0 +1,6 @@
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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
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2024H1,20.04,381.0,526.0,,,,,,,,,
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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
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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
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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
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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
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@@ -0,0 +1,8 @@
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period,china_robot_revenue,china_average_stores,china_per_store,overseas_robot_revenue,overseas_average_stores,overseas_per_store
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2024H1,3.38,2207.0,15.3,,,,
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2024H2,4.13,2281.5,18.1,0.49,,
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2024FY,7.51,2264.5,33.2,0.80,116.0,69.0
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2025H1,6.78,2388.0,28.4,1.42,146.5,96.9
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2025H2,6.68,2416.5,27.6,2.02,200.5,100.7
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2025FY,13.46,2367.5,56.9,3.44,187.0,184.0
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2026H1,7.79,2439.0,31.9,1.72,293.0,58.7
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@@ -0,0 +1,3 @@
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period,china_robot_revenue,china_average_stores,china_per_store,overseas_robot_revenue,overseas_average_stores,overseas_per_store
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2024FY,7.51,2264.5,33.2,0.80,116.0,69.0
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2025FY,13.46,2367.5,56.9,3.44,187.0,184.0
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@@ -0,0 +1,6 @@
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period,china_robot_revenue,china_average_stores,china_per_store,overseas_robot_revenue,overseas_average_stores,overseas_per_store
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2024H1,3.38,2207.0,15.3,,,,
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2024H2,4.13,2281.5,18.1,0.49,,
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2025H1,6.78,2388.0,28.4,1.42,146.5,96.9
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2025H2,6.68,2416.5,27.6,2.02,200.5,100.7
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2026H1,7.79,2439.0,31.9,1.72,293.0,58.7
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@@ -0,0 +1,6 @@
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period,global,china,apac,americas,europe,other
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2024H1,457,87.3,8.5,2.2,2.0,0.0
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2024FY,521,82.7,10.4,4.2,2.7,0.0
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2025H1,571,77.6,12.1,7.2,3.2,0.0
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2025FY,630,70.6,13.5,10.2,5.7,0.0
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2026H1,676,67.3,13.3,12.7,6.7,0.0
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@@ -0,0 +1,3 @@
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period,global,china,apac,americas,europe,other
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2024FY,521,82.7,10.4,4.2,2.7,0.0
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2025FY,630,70.6,13.5,10.2,5.7,0.0
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@@ -0,0 +1,4 @@
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period,global,china,apac,americas,europe,other
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2024H1,457,87.3,8.5,2.2,2.0,0.0
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2025H1,571,77.6,12.1,7.2,3.2,0.0
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2026H1,676,67.3,13.3,12.7,6.7,0.0
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@@ -1,14 +1,14 @@
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period,inventory_days,receivable_days,payable_days,cash_conversion_cycle
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2020H1,101.4,9.6,27.6,83.3
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2020FY,63.0,8.9,28.4,43.5
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2021H1,74.3,10.9,40.9,44.3
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2021FY,105.4,10.0,29.9,85.5
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2022H1,159.0,11.6,44.7,125.9
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2022FY,151.8,14.3,46.3,119.8
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2023H1,131.2,12.9,54.4,89.7
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2023FY,130.9,14.7,51.2,94.4
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2024H1,100.0,11.6,54.5,57.1
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2024FY,101.0,11.0,52.9,59.1
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2025H1,83.1,9.4,48.8,43.7
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2025FY,121.6,6.8,36.1,92.3
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2026H1,200.0,8.1,42.6,165.5
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2020H1,102.0,9.6,27.8,83.8
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2020FY,63.9,9.0,28.8,44.1
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2021H1,74.7,10.9,41.1,44.6
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2021FY,106.9,10.1,30.4,86.6
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2022H1,159.9,11.7,44.9,126.6
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2022FY,154.0,14.5,47.0,121.5
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2023H1,131.9,13.0,54.7,90.2
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2023FY,132.7,14.9,51.9,95.7
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2024H1,100.6,11.6,54.8,57.4
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2024FY,102.4,11.2,53.6,59.9
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2025H1,83.5,9.5,49.1,43.9
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2025FY,123.3,6.9,36.6,93.6
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2026H1,201.2,8.2,42.9,166.5
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@@ -28,6 +28,10 @@ import { channelRevenueChart } from './ppmt_channel_revenue.js';
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import { storesRetailChart } from './ppmt_stores_retail.js';
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import { storesRobotChart } from './ppmt_stores_robot.js';
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import { regionShareChart } from './ppmt_region_share.js';
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import { inventoryBalanceChart } from './ppmt_inventory.js';
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import { storesRetailShareChart } from './ppmt_stores_retail_share.js';
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import { retailStoreRevenueChart } from './ppmt_retail_store_revenue.js';
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import { robotStoreRevenueChart } from './ppmt_robot_store_revenue.js';
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/** 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。 */
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export const chartRegistry = {
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@@ -61,6 +65,10 @@ export const chartRegistry = {
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'ppmt-stores-retail': storesRetailChart,
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'ppmt-stores-robot': storesRobotChart,
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'ppmt-region-share': regionShareChart,
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'ppmt-inventory': inventoryBalanceChart,
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'ppmt-stores-retail-share': storesRetailShareChart,
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'ppmt-retail-store-revenue': retailStoreRevenueChart,
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'ppmt-robot-store-revenue': robotStoreRevenueChart,
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};
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export function getChartBuilder(key) {
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@@ -31,6 +31,10 @@ export function channelRevenueChart(rows, { width, height, view = 'all' }) {
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const totalMax = Math.max(...rows.map((row) => num(row.total_revenue) || 0));
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const axisMax = NICE_MAX.find((max) => max >= totalMax * 1.02)
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?? Math.ceil((totalMax * 1.2) / 100) * 100;
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const yoyValues = col(rows, 'revenue_yoy').filter(Number.isFinite);
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// 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。
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const yoyMin = Math.min(0, Math.floor(Math.min(...yoyValues) / 50) * 50);
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const yoyMax = Math.max(50, Math.ceil(Math.max(...yoyValues) / 50) * 50);
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// 绘图区像素高:画布高 − grid top 145 − grid bottom 90
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const pxPerUnit = (height - LAYOUT.gridTop - 90) / axisMax;
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@@ -111,8 +115,8 @@ export function channelRevenueChart(rows, { width, height, view = 'all' }) {
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nameGap: 60,
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nameRotate: -90,
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nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
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min: 0,
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max: 250,
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min: yoyMin,
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max: yoyMax,
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interval: 50,
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axisLabel: { ...axisCommon.axisLabel, formatter: '{value}%' },
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splitLine: { show: false },
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@@ -0,0 +1,82 @@
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import { col } from '../csv.js';
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import {
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FINANCIAL_COLORS, PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
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financialViewLabel, barSeries, lineSeries, footnote, watermarks, LAYOUT,
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} from '../theme.js';
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/** 泡泡玛特存货余额与同报告期同比:存货为期末时点数。 */
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export function inventoryBalanceChart(rows, { width, height, view = 'all' }) {
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const yoy = col(rows, 'yoy').filter(Number.isFinite);
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const yoyMin = Math.min(0, Math.floor(Math.min(...yoy) / 20) * 20);
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const yoyMax = Math.max(50, Math.ceil(Math.max(...yoy) / 50) * 50);
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const barWidth = view === 'all' ? 28.8 : 60.8;
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return {
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backgroundColor: '#fff',
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title: {
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...titleStyle,
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text: `泡泡玛特存货余额及同比(${financialViewLabel(view)})`,
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subtext: '柱状为报告期末存货余额;折线为同报告期同比(H1 对 H1、全年对全年)',
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},
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legend: standardLegend(['存货余额', '存货同比']),
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grid: { left: 78, right: 82, top: LAYOUT.gridTop, bottom: 90 },
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tooltip: {
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trigger: 'axis',
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axisPointer: { type: 'shadow' },
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textStyle: { fontFamily: FONT },
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valueFormatter: (value) => `${value.toFixed(1)}`,
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},
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xAxis: { ...standalonePeriodAxis, data: col(rows, 'period') },
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yAxis: [
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{
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...axisCommon,
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type: 'value',
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name: '存货余额(亿元)',
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nameLocation: 'middle',
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nameGap: 52,
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nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
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min: 0,
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},
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{
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...axisCommon,
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type: 'value',
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name: '同比(%)',
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nameLocation: 'middle',
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nameGap: 58,
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nameRotate: -90,
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nameTextStyle: { color: PALETTE.grey, fontSize: 13, fontFamily: FONT },
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min: yoyMin,
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max: yoyMax,
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interval: (yoyMax - yoyMin) / 5,
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axisLabel: { ...axisCommon.axisLabel, formatter: '{value}%' },
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splitLine: { show: false },
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},
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],
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series: [
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{
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...barSeries({
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name: '存货余额',
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data: col(rows, 'inventory'),
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color: FINANCIAL_COLORS.investingCashFlow,
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barWidth,
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formatter: (point) => point.value.toFixed(1),
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}),
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emphasis: { focus: 'series' },
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},
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{
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...lineSeries({
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name: '存货同比',
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data: col(rows, 'yoy'),
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color: FINANCIAL_COLORS.cashConversion,
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formatter: (point) => `${point.value.toFixed(1)}%`,
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}),
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yAxisIndex: 1,
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z: 10,
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},
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],
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graphic: [
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...watermarks(width, height),
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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'),
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],
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};
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}
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@@ -0,0 +1,110 @@
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import { col } from '../csv.js';
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import {
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PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
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financialViewLabel, barSeries, lineSeries, footnote, watermarks, LAYOUT,
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} from '../theme.js';
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const REGIONS = [
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{ key: 'china', name: '中国(含港澳台)', color: '#3F7FBE' },
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{ key: 'apac', name: '亚太', color: '#36A28F' },
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{ key: 'americas', name: '美洲', color: '#E4A349' },
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{ key: 'europe_other', name: '欧洲及其他', color: PALETTE.brown },
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];
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function yoyByPeriod(rows, key) {
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const values = new Map(rows.map((row) => [row.period, row[key]]));
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return rows.map((row) => {
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const year = Number(row.period.slice(0, 4));
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const prior = values.get(`${year - 1}${row.period.slice(4)}`);
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return Number.isFinite(row[key]) && Number.isFinite(prior) && prior !== 0
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? (row[key] / prior - 1) * 100
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: null;
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});
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}
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/** 各地区零售店单店收入:收入 ÷ 期初、期末平均零售店数。 */
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export function retailStoreRevenueChart(rows, { width, height, view = 'all' }) {
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const values = REGIONS.flatMap((region) => col(rows, `${region.key}_per_store`)).filter(Number.isFinite);
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const yMax = Math.ceil(Math.max(...values) / 1000) * 1000;
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const yoySeries = REGIONS.map((region) => ({ ...region, data: yoyByPeriod(rows, `${region.key}_per_store`) }));
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const yoyValues = yoySeries.flatMap((region) => region.data).filter(Number.isFinite);
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const yoyMin = Math.min(0, Math.floor(Math.min(...yoyValues) / 50) * 50);
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const yoyMax = Math.max(50, Math.ceil(Math.max(...yoyValues) / 50) * 50);
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const legendItems = REGIONS.flatMap((region) => [region.name, `${region.name}同比`]);
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return {
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backgroundColor: '#fff',
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title: {
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...titleStyle,
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text: `泡泡玛特各地区零售店单店收入(${financialViewLabel(view)})`,
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subtext: '柱状为单店收入;同色虚线为单店收入同比;H2为下半年单期',
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},
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legend: standardLegend(legendItems, { itemGap: 18 }),
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grid: { left: 78, right: 42, top: LAYOUT.gridTop, bottom: 90 },
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tooltip: {
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trigger: 'axis',
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axisPointer: { type: 'shadow' },
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textStyle: { fontFamily: FONT },
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formatter: (params) => `<b>${params[0].axisValue}</b><br/>${params
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.filter((item) => Number.isFinite(item.value))
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.map((item) => `${item.marker}${item.seriesName}: ${Number(item.value).toFixed(1)}${item.seriesName.endsWith('同比') ? '%' : ' 万元/店'}`)
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.join('<br/>')}`,
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},
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xAxis: { ...standalonePeriodAxis, data: col(rows, 'period') },
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yAxis: [
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{
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...axisCommon,
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type: 'value',
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name: '单店收入(万元/店)',
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nameLocation: 'middle',
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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) => `${point.value.toFixed(0)}%`,
|
||||
}),
|
||||
yAxisIndex: 1,
|
||||
lineStyle: { color: region.color, width: 2, type: 'dashed' },
|
||||
z: 10,
|
||||
})),
|
||||
],
|
||||
graphic: [
|
||||
...watermarks(width, height),
|
||||
footnote('数据来源:泡泡玛特历年公告;收入仅含“零售店”渠道;H2收入=全年−H1\n2024年海外各区域缺少期初店数,相关单店收入留空 | @思考的Joey'),
|
||||
],
|
||||
};
|
||||
}
|
||||
@@ -0,0 +1,108 @@
|
||||
import { col } from '../csv.js';
|
||||
import {
|
||||
PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
|
||||
financialViewLabel, barSeries, lineSeries, footnote, watermarks, LAYOUT,
|
||||
} from '../theme.js';
|
||||
|
||||
const REGIONS = [
|
||||
{ key: 'china', name: '中国(含港澳台)', color: '#71AD81' },
|
||||
{ key: 'overseas', name: '海外', color: PALETTE.brown },
|
||||
];
|
||||
|
||||
function yoyByPeriod(rows, key) {
|
||||
const values = new Map(rows.map((row) => [row.period, row[key]]));
|
||||
return rows.map((row) => {
|
||||
const year = Number(row.period.slice(0, 4));
|
||||
const prior = values.get(`${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) => `${point.value.toFixed(0)}%`,
|
||||
}),
|
||||
yAxisIndex: 1,
|
||||
lineStyle: { color: region.color, width: 2, type: 'dashed' },
|
||||
z: 10,
|
||||
})),
|
||||
],
|
||||
graphic: [
|
||||
...watermarks(width, height),
|
||||
footnote('数据来源:泡泡玛特历年公告;海外收入=亚太+美洲+欧洲及其他的机器人商店收入;H2收入=全年−H1\n2024H1海外期末机器人商店数未披露,相关单店收入留空 | @思考的Joey'),
|
||||
],
|
||||
};
|
||||
}
|
||||
@@ -0,0 +1,83 @@
|
||||
import { col } from '../csv.js';
|
||||
import {
|
||||
PALETTE, FONT, axisCommon, standalonePeriodAxis, titleStyle, standardLegend,
|
||||
financialViewLabel, barSeries, footnote, watermarks, LAYOUT,
|
||||
} from '../theme.js';
|
||||
|
||||
/** 泡泡玛特分地区零售门店占比:每根柱标准化为各期末全球门店数的 100%。 */
|
||||
const REGIONS = [
|
||||
{ key: 'china', name: '中国(含港澳台)', color: '#3F7FBE', labelColor: '#fff' },
|
||||
{ key: 'apac', name: '亚太', color: '#36A28F', labelColor: '#fff' },
|
||||
{ key: 'americas', name: '美洲', color: '#E4A349', labelColor: PALETTE.ink },
|
||||
{ key: 'europe', name: '欧洲', color: PALETTE.brown, labelColor: '#fff' },
|
||||
{ key: 'other', name: '其他', color: PALETTE.sand, labelColor: PALETTE.ink },
|
||||
];
|
||||
|
||||
function sharePoint(value, labelColor) {
|
||||
if (!Number.isFinite(value) || value === 0) return null;
|
||||
return {
|
||||
value,
|
||||
label: value >= 5
|
||||
? { position: 'inside', color: labelColor }
|
||||
: { show: false },
|
||||
};
|
||||
}
|
||||
|
||||
export function storesRetailShareChart(rows, { width, height, view = 'all' }) {
|
||||
const periods = col(rows, 'period');
|
||||
const barWidth = view === 'all' ? 48 : 80;
|
||||
|
||||
return {
|
||||
backgroundColor: '#fff',
|
||||
title: {
|
||||
...titleStyle,
|
||||
text: `泡泡玛特分地区零售门店数量占比(${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'),
|
||||
],
|
||||
};
|
||||
}
|
||||
@@ -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'),
|
||||
],
|
||||
};
|
||||
}
|
||||
|
||||
+7
-2
@@ -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" },
|
||||
@@ -27,16 +28,20 @@
|
||||
"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-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-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"] }
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@@ -184,13 +184,21 @@ 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) => [
|
||||
periodFor(item.date),
|
||||
item.inventory.toFixed(1),
|
||||
item.receivable.toFixed(1),
|
||||
item.payable.toFixed(1),
|
||||
(item.inventory + item.receivable - item.payable).toFixed(1),
|
||||
]).reverse();
|
||||
)).map((item) => {
|
||||
const period = periodFor(item.date);
|
||||
// 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。
|
||||
const factor = period.endsWith('H1') ? 181 / 180 : 365 / 360;
|
||||
const inventory = item.inventory * factor;
|
||||
const receivable = item.receivable * factor;
|
||||
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 +349,9 @@ 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 +359,14 @@ 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: `${base}_halfyear.csv`,
|
||||
};
|
||||
Object.entries(filenames).forEach(([view, filename]) => {
|
||||
writeCSV(filename, headers, toOutputRows(views[view], headers, digits));
|
||||
writeCSV(filename, headers, toOutputRows(views[view], headers, digits, startYear));
|
||||
});
|
||||
}
|
||||
|
||||
@@ -614,6 +622,31 @@ writeRuntimeViews('ppmt_category', ['period', 'plush', 'figure', 'mega', 'other'
|
||||
plush: 2, figure: 2, mega: 2, other: 2,
|
||||
});
|
||||
|
||||
// 2024H1 起门店披露可将中国内地与港澳台合并,并按全球总数归一化为地区占比。
|
||||
const retailStoreRows = readRuntimeRows('ppmt_stores_retail.csv');
|
||||
const retailStoreShareViews = { all: [], annual: [], halfyear: [] };
|
||||
retailStoreRows.filter((row) => (
|
||||
Number(row.period.slice(0, 4)) >= 2024
|
||||
&& ['mainland', 'hkmtw', 'apac', 'americas', 'europe', 'global'].every((key) => Number.isFinite(row[key]))
|
||||
)).forEach((row) => {
|
||||
const china = row.mainland + row.hkmtw;
|
||||
const other = row.global - china - row.apac - row.americas - row.europe;
|
||||
const shareRow = {
|
||||
period: row.period,
|
||||
global: row.global,
|
||||
china: china / row.global * 100,
|
||||
apac: row.apac / row.global * 100,
|
||||
americas: row.americas / row.global * 100,
|
||||
europe: row.europe / row.global * 100,
|
||||
other: other / row.global * 100,
|
||||
};
|
||||
retailStoreShareViews.all.push(shareRow);
|
||||
retailStoreShareViews[row.period.endsWith('FY') ? 'annual' : 'halfyear'].push(shareRow);
|
||||
});
|
||||
writeRuntimeViews('ppmt_stores_retail_share', ['period', 'global', 'china', 'apac', 'americas', 'europe', 'other'], retailStoreShareViews, {
|
||||
global: 0, china: 1, apac: 1, americas: 1, europe: 1, other: 1,
|
||||
});
|
||||
|
||||
// 资产负债表为时点指标:H2 是年末时点,而非“全年累计”。
|
||||
function buildSnapshotViews(base, headers, digits) {
|
||||
const source = readRuntimeRows(`${base}.csv`);
|
||||
@@ -643,4 +676,25 @@ 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。');
|
||||
|
||||
Reference in New Issue
Block a user