Cameroon vs Philippines: Watermelons — Gross Production Value
Watermelons — Gross Production Value over time
- Cameroon
- Philippines
How they compare
Cameroon currently reports 4.59 million 1000 SLC against 2.64 million 1000 SLC in Philippines, a difference of 1.95 million 1000 SLC.
That makes Cameroon's figure about 1.7 times Philippines's.
The two have swapped places 5 times across 34 shared years of data; in 1991 it was Philippines ahead.
Cameroon ranks 28th and Philippines ranks 31st of 91 countries.
Across the 4 decades both report, Cameroon averaged higher in 3 and Philippines in 1.
Head to head by decade
| Decade | Cameroon | Philippines | Difference | Ahead |
|---|---|---|---|---|
| 1990s | 429,553 1000 SLC | 504,364 1000 SLC | 74,811 1000 SLC | Philippines |
| 2000s | 958,082 1000 SLC | 811,771 1000 SLC | 146,311 1000 SLC | Cameroon |
| 2010s | 2.46 million 1000 SLC | 1.60 million 1000 SLC | 856,076 1000 SLC | Cameroon |
| 2020s | 4.14 million 1000 SLC | 2.47 million 1000 SLC | 1.67 million 1000 SLC | Cameroon |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher watermelons — gross production value, Cameroon or Philippines?
- Cameroon, at 4.59 million 1000 SLC against 2.64 million 1000 SLC in Philippines as of 2024.
- What is the difference in watermelons — gross production value between Cameroon and Philippines?
- 1.95 million 1000 SLC, with Cameroon ahead.
- How many years of comparable data are there for Cameroon and Philippines?
- 34 years are reported by both, from 1991 to 2024.
- How do Cameroon and Philippines rank globally for watermelons — gross production value?
- Cameroon ranks 28th and Philippines ranks 31st of 91 countries.
- Where does this data come from?
- Food and Agriculture Organization of the United Nations, published as Watermelons — 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.