Segments: Home Use, Portable, Hospital. For 2021: Home=500, Portable=300, Hospital=200. Total 1B. Then each year, Home increases by 10%, Portable by 15%, Hospital by 5%. Let's calculate for 2021 to 2025. 2021: 500,300,200. 2022: 550, 345, 210. 2023: 605, 396.75, 220.5. 2024: 665.5, 456.26, 231.5. 2025: 732.05, 524.69, 243.1. These are approximate. Then for the forecast period up to 2033, I can extend the trend. But the chart should include periods from 2021 to 2033. However, the user's base year is 2025, and forecast until 2033. So maybe the historical data is from 2021-2025, and the forecast from 2026-2033. But the chart needs periods as years, which the example includes all the way to 2033. Let me adjust the data to cover all periods. Maybe from 2021 to 2033. The example shows 2020-2033, but in this case, the study period is 2021-2033. So periods would be ["2021", "2022", "2023", "2024", "2025", "2026", "2027", "2028", "2029", "2030", "2031", "2032", "2033"]. The values for each segment should be an array of numbers for each year. Let me create a more realistic data set. Let's assume the Home Use segment grows from 500 million in 2021 to 1.2 billion in 2033, Portables from 300 to 800, and Hospital remains around 200 to 300. But I need to make sure the numbers are consistent with the CAGR mentioned earlier. Let me just create some approximate values. For example, Home Use could be [500, 550, 605, 666, 733, 806, 887, 976, 1073, 1179, 1296, 1426, 1569], Portables [300, 345, 397, 456, 524, 597, 676, 764, 861, 967, 1083, 1212, 1354], Hospital [200, 210, 221, 232, 244, 256, 269, 283, 297, 312, 328, 345, 362]. These are approximate and would need to be adjusted for realism, but for the purpose of the example, they can suffice.
