Argentina vs ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437): Enrolment in pre-primary education, female (number), gaps filled

Argentina
773,753
in 2023
ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)
27.62 million
in 2024
Argentina rank
25th
ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) rank
27th

Enrolment in pre-primary education, female (number), gaps filled over time

  • Argentina
  • ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)
010.0M20.0M30.0M197019972024

How they compare

ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) currently reports 27.62 million against 773,753 in Argentina, a difference of 26.85 million.

That makes ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)'s figure about 35.7 times Argentina's.

Across all 34 years both countries report, ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) has been ahead every year.

Argentina ranks 25th and ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) ranks 27th of 208 countries.

ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) has averaged higher in every one of the 5 decades both report.

Head to head by decade

Decade Argentina ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) Difference Ahead
1980s 353,459 10.39 million 10.03 million ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)
1990s 578,411 16.22 million 15.65 million ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)
2000s 658,954 15.14 million 14.48 million ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)
2010s 798,437 25.51 million 24.71 million ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)
2020s 803,689 30.62 million 29.82 million ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)

Averages of every year both report within each decade.

Frequently asked questions

Which has higher enrolment in pre-primary education, female (number), gaps filled, Argentina or ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)?
ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437), at 27.62 million against 773,753 in Argentina as of 2024.
What is the difference in enrolment in pre-primary education, female (number), gaps filled between Argentina and ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)?
26.85 million, with ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) ahead.
How many years of comparable data are there for Argentina and ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437)?
34 years are reported by both, from 1983 to 2023.
How do Argentina and ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) rank globally for enrolment in pre-primary education, female (number), gaps filled?
Argentina ranks 25th and ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437) ranks 27th of 208 countries.
Where does this data come from?
Statizoid (derived), published as Enrolment in pre-primary education, female (number), gaps filled. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Argentina vs ESCAP: Wb Upper Middle Income Economies (wb_upper_mid) (unsdcode:98437): Enrolment in pre-primary education, female (number), gaps filled. Statizoid, drawing on Statizoid (derived). Retrieved 14 September 2026, from https://education.statizoid.com/compare/enrolment-in-pre-primary-education-female-number-gaps-filled/argentina/escap-wb-upper-middle-income-economies-wb-upper-mid-unsdcode-98437/

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About this data

Indicator
Enrolment in pre-primary education, female (number), gaps filled
Source
Statizoid (derived)
Licence
Derived by Statizoid from the sources named on the page
Coverage
429 places, 17,609 data points, 1970–2025
Last refreshed

Enrolment in pre-primary education, female (number) with 697 missing years estimated by linear interpolation between the nearest real observations. Only gaps of 4 years or fewer are filled, and never beyond the first or last actual measurement — these are filled holes, not forecasts.