India vs San Marino: Statistical performance indicators (SPI): Pillar 5 data infrastructure
Statistical performance indicators (SPI): Pillar 5 data infrastructure over time
- India
- San Marino
How they compare
India currently reports 50 scale 0-100 against 50 scale 0-100 in San Marino, a difference of 0 scale 0-100.
The two have swapped places 3 times across 9 shared years of data; in 2016 it was India ahead.
India ranks 136th and San Marino ranks 136th of 190 countries.
Head to head by decade
| Decade | India | San Marino | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 51.25 scale 0-100 | 51.25 scale 0-100 | 0 scale 0-100 | — |
| 2020s | 53 scale 0-100 | 53 scale 0-100 | 0 scale 0-100 | — |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 5 data infrastructure, India or San Marino?
- India, at 50 scale 0-100 against 50 scale 0-100 in San Marino as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 5 data infrastructure between India and San Marino?
- 0 scale 0-100, with India ahead.
- How many years of comparable data are there for India and San Marino?
- 9 years are reported by both, from 2016 to 2024.
- How do India and San Marino rank globally for statistical performance indicators (spi): pillar 5 data infrastructure?
- India ranks 136th and San Marino ranks 136th of 190 countries.
- Where does this data come from?
- Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 5 data infrastructure score (scale 0-100). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The data infrastructure pillar overall score measures the hard and soft infrastructure segments, itemizing essential cross cutting requirements for an effective statistical system. The segments are: (i) legislation and governance covering the existence of laws and a functioning institutional framework for the statistical system; (ii) standards and methods addressing compliance with recognized frameworks and concepts; (iii) skills including level of skills within the statistical system and among users (statistical literacy); (iv) partnerships reflecting the need for the statistical system to be inclusive and coherent; and (v) finance mobilized both domestically and from donors.