Pakistan vs Peru: Watermelons — Gross per capita Production Index Number
Pakistan
185.75
in 2024
Peru
172.09
in 2024
Pakistan rank
13th
Peru rank
15th
Watermelons — Gross per capita Production Index Number over time
- Pakistan
- Peru
How they compare
Pakistan currently reports 185.75 against 172.09 in Peru, a difference of 13.66.
That makes Pakistan's figure about 1.1 times Peru's.
The two have swapped places 8 times across 64 shared years of data; in 1961 it was Pakistan ahead.
Pakistan ranks 13th and Peru ranks 15th of 109 countries.
Across the 7 decades both report, Pakistan averaged higher in 6 and Peru in 1.
Head to head by decade
| Decade | Pakistan | Peru | Difference | Ahead |
|---|---|---|---|---|
| 1960s | 114.94 | 125.62 | 10.68 | Peru |
| 1970s | 143.99 | 83.1 | 60.89 | Pakistan |
| 1980s | 118.49 | 73.02 | 45.47 | Pakistan |
| 1990s | 135.42 | 73.9 | 61.52 | Pakistan |
| 2000s | 90.48 | 80.94 | 9.54 | Pakistan |
| 2010s | 113.29 | 105.6 | 7.69 | Pakistan |
| 2020s | 236.53 | 138.53 | 98.01 | Pakistan |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher watermelons — gross per capita production index number, Pakistan or Peru?
- Pakistan, at 185.75 against 172.09 in Peru as of 2024.
- What is the difference in watermelons — gross per capita production index number between Pakistan and Peru?
- 13.66, with Pakistan ahead.
- How many years of comparable data are there for Pakistan and Peru?
- 64 years are reported by both, from 1961 to 2024.
- How do Pakistan and Peru rank globally for watermelons — gross per capita production index number?
- Pakistan ranks 13th and Peru ranks 15th of 109 countries.
- Where does this data come from?
- Food and Agriculture Organization of the United Nations, published as Watermelons — Gross per capita Production Index Number (2014-2016 = 100). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 2014-2016. Indices for meat production are computed based on data on production from indigenous animals.