Philippines vs Rwanda: Sugar cane — Gross Production Value
Sugar cane — Gross Production Value over time
- Philippines
- Rwanda
How they compare
Rwanda currently reports 89.07 million 1000 SLC against 69.21 million 1000 SLC in Philippines, a difference of 19.86 million 1000 SLC.
That makes Rwanda's figure about 1.3 times Philippines's.
The two have swapped places 1 time across 34 shared years of data; in 1991 it was Philippines ahead.
Philippines ranks 18th and Rwanda ranks 17th of 71 countries.
Philippines has averaged higher in every one of the 4 decades both report.
Head to head by decade
| Decade | Philippines | Rwanda | Difference | Ahead |
|---|---|---|---|---|
| 1990s | 24.81 million 1000 SLC | 238,380 1000 SLC | 24.58 million 1000 SLC | Philippines |
| 2000s | 39.58 million 1000 SLC | 1.65 million 1000 SLC | 37.92 million 1000 SLC | Philippines |
| 2010s | 71.29 million 1000 SLC | 13.22 million 1000 SLC | 58.07 million 1000 SLC | Philippines |
| 2020s | 77.13 million 1000 SLC | 53.91 million 1000 SLC | 23.22 million 1000 SLC | Philippines |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher sugar cane — gross production value, Philippines or Rwanda?
- Rwanda, at 89.07 million 1000 SLC against 69.21 million 1000 SLC in Philippines as of 2024.
- What is the difference in sugar cane — gross production value between Philippines and Rwanda?
- 19.86 million 1000 SLC, with Rwanda ahead.
- How many years of comparable data are there for Philippines and Rwanda?
- 34 years are reported by both, from 1991 to 2024.
- How do Philippines and Rwanda rank globally for sugar cane — gross production value?
- Philippines ranks 18th and Rwanda ranks 17th of 71 countries.
- Where does this data come from?
- Food and Agriculture Organization of the United Nations, published as Sugar cane — Gross Production Value (current thousand SLC). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The domain provides detailed data on the value of agricultural production that is calculated by the agricultural production data and the price data at farm gate. Thus, the value of production measures the agricultural production in monetary terms at the farm gate level.