Nevada charter schools added 17,000 students since 2021 while traditional districts bled 30,000 – and the state’s kindergarten pipeline is swinging wildly year to year.
Part of the njschooldata family of state education data packages.
Full documentation – all 15 stories with interactive charts, getting-started guide, and complete function reference.
Highlights
library(nvschooldata)
library(dplyr)
library(tidyr)
library(ggplot2)
enr <- fetch_enr_multi(2021:2026, use_cache = TRUE)1. Charter enrollment surged 33% while traditional districts lost 30,000 students
The State Public Charter School Authority (SPCSA) oversees Nevada’s charter sector. Charters grew from 53,223 students in 2021 to 70,534 in 2026 – a 33% increase – while traditional districts lost 30,287 students in the same period.
charter_trend <- enr |>
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL") |>
group_by(end_year, is_charter) |>
summarize(students = sum(n_students, na.rm = TRUE),
n_districts = n(), .groups = "drop") |>
mutate(sector = ifelse(is_charter, "Charter", "Traditional"))
stopifnot(nrow(charter_trend) > 0)
charter_trend |> select(end_year, sector, students, n_districts)
#> # A tibble: 10 x 4
#> end_year sector students n_districts
#> <dbl> <chr> <dbl> <int>
#> 1 2021 Charter 53223 37
#> 2 2021 Traditional 433410 19
#> 3 2022 Charter 55415 38
#> 4 2022 Traditional 436923 19
#> 5 2023 Charter 59670 43
#> 6 2023 Traditional 429927 19
#> 7 2024 Charter 61883 44
#> 8 2024 Traditional 423687 19
#> 9 2026 Charter 70534 51
#> 10 2026 Traditional 403123 19
Charter vs traditional enrollment trends
2. Nevada lost nearly 13,000 students between 2021 and 2026
Nevada was one of America’s fastest-growing states for decades, but school enrollment has declined since 2022. The state shed 18,681 students from its 2022 peak to 2026.
state_totals <- enr |>
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL") |>
group_by(end_year) |>
summarize(n_students = sum(n_students, na.rm = TRUE), .groups = "drop") |>
mutate(change = n_students - lag(n_students),
pct_change = round(change / lag(n_students) * 100, 2))
stopifnot(nrow(state_totals) > 0)
state_totals
#> # A tibble: 5 x 4
#> end_year n_students change pct_change
#> <dbl> <dbl> <dbl> <dbl>
#> 1 2021 486633 NA NA
#> 2 2022 492338 5705 1.17
#> 3 2023 489597 -2741 -0.56
#> 4 2024 485570 -4027 -0.82
#> 5 2026 473657 -11913 -2.45
Nevada statewide enrollment trends
3. Kindergarten enrollment swung wildly: up 8% in 2022, down 9% in 2024
Kindergarten enrollment is a leading indicator of future trends. Nevada K enrollment hit 34,641 in 2022 then crashed to 28,931 in 2024 before recovering to 30,490 in 2026. Grade-level data is available at the school level.
k_data <- enr |>
filter(is_school, subgroup == "total_enrollment", grade_level == "K") |>
group_by(end_year) |>
summarize(k_students = sum(n_students, na.rm = TRUE), .groups = "drop") |>
mutate(change = k_students - lag(k_students),
pct_change = round(change / lag(k_students) * 100, 2))
stopifnot(nrow(k_data) > 0)
k_data
#> # A tibble: 5 x 4
#> end_year k_students change pct_change
#> <dbl> <dbl> <dbl> <dbl>
#> 1 2021 31995 NA NA
#> 2 2022 34641 2646 8.27
#> 3 2023 31951 -2690 -7.77
#> 4 2024 28931 -3020 -9.45
#> 5 2026 30490 1559 5.39
Kindergarten enrollment trends
Data Taxonomy
| Category | Years | Function | Details |
|---|---|---|---|
| Enrollment | 2016-2026 |
fetch_enr() / fetch_enr_multi()
|
District, school. Race, gender, FRL, SpEd, LEP |
| Assessments | — | — | Not yet available |
| Graduation | — | — | Not yet available |
| Directory | Current | fetch_directory() |
School-level. Contact info, charter status, locale |
| Per-Pupil Spending | — | — | Not yet available |
| Accountability | — | — | Not yet available |
| Chronic Absence | — | — | Not yet available |
| EL Progress | — | — | Not yet available |
| Special Ed | — | — | Not yet available |
See the full data category taxonomy
Quick Start
R
# install.packages("remotes")
remotes::install_github("almartin82/nvschooldata")
library(nvschooldata)
library(dplyr)
# Fetch one year
enr_2026 <- fetch_enr(2026)
# Fetch multiple years
enr_multi <- fetch_enr_multi(c(2021:2024, 2026))
# State totals
get_state_enrollment(c(2021:2024, 2026))
# Filter to a specific district
enr_2026 |>
filter_district("02") # Clark County
# Filter to Clark County schools
enr_2026 |>
filter_county("Clark")
# District breakdown
enr_2026 |>
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL") |>
arrange(desc(n_students))
# School directory
dir_data <- fetch_directory()Python
import pynvschooldata as nv
# Check available years
years = nv.get_available_years()
print(f"Data available from {years['min_year']} to {years['max_year']}")
# Fetch one year
df = nv.fetch_enr(2026)
# Fetch multiple years
df_multi = nv.fetch_enr_multi([2024, 2026])
# Filter to district totals
district_totals = df[
(df['is_district'] == True) &
(df['grade_level'] == 'TOTAL') &
(df['subgroup'] == 'total_enrollment')
].sort_values('n_students', ascending=False)
print(district_totals[['district_name', 'n_students']])Explore More
Full analysis with 15 stories: - Enrollment trends – 15 stories - Function reference
Data Notes
Data Source
Nevada Department of Education: Enrollment Data
Available Years
| Years | Format | Aggregation Levels | Demographics | Notes |
|---|---|---|---|---|
| 2021-2026 | Modern | District, School | Race, Gender, Special Populations | Full LEA codes, complete data |
| 2018-2020 | Intermediate | District, School | Race, Gender | Consolidated format |
| 2016-2017 | Legacy | Limited | Limited | Partial data extraction |
Census Day
Data is collected on October 1 “validation day” each year. This is Nevada’s official enrollment count date.
Suppression Rules
Nevada does not suppress small counts in the publicly available enrollment files. All counts are reported as provided by districts.
Nevada District Codes
| Code | District |
|---|---|
| 02 | Clark County School District (Las Vegas) |
| 16 | Washoe County School District (Reno) |
| 13 | Carson City School District |
| 18 | State Public Charter School Authority (SPCSA) |
Deeper Dive
4. Charter schools crack the top 10 in Nevada
Clark County dominates, but three charter networks (Somerset, Pinecrest, Doral) now enroll more students than most county school districts. Somerset Academy alone enrolls more than 14 of the 17 county districts.
enr_2026 <- fetch_enr(2026, use_cache = TRUE)
top_districts <- enr_2026 |>
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL") |>
arrange(desc(n_students)) |>
head(10) |>
select(district_name, n_students, is_charter)
stopifnot(nrow(top_districts) == 10)
top_districts
#> # A tibble: 10 x 3
#> district_name n_students is_charter
#> <chr> <dbl> <lgl>
#> 1 Clark County School District 291587 FALSE
#> 2 Washoe County School District 63655 FALSE
#> 3 Somerset Academy of Las Vegas 9534 TRUE
#> 4 Elko County School District 9293 FALSE
#> 5 Lyon County School District 9060 FALSE
#> 6 Pinecrest Academy of Nevada 8474 TRUE
#> 7 Carson City School District 7281 FALSE
#> 8 Doral Academy 6442 TRUE
#> 9 Nye County School District 5794 FALSE
#> 10 Coral Academy of Science Las Vegas 5552 TRUE
Top Nevada districts
5. Clark County lost 27,706 students since 2021 while Washoe held steady
Clark County (Las Vegas) and Washoe County (Reno) are Nevada’s two urban anchors. Clark dropped 8.7% from 2021 to 2026 while Washoe only dropped 2.1%.
growth_data <- enr |>
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL",
grepl("Clark|Washoe", district_name)) |>
mutate(county = case_when(
grepl("Clark", district_name) ~ "Clark County",
grepl("Washoe", district_name) ~ "Washoe County"
)) |>
group_by(county, end_year) |>
summarize(n_students = sum(n_students, na.rm = TRUE), .groups = "drop") |>
group_by(county) |>
mutate(index = round(n_students / first(n_students) * 100, 1)) |>
ungroup()
stopifnot(nrow(growth_data) > 0)
growth_data
#> # A tibble: 10 x 4
#> county end_year n_students index
#> <chr> <dbl> <dbl> <dbl>
#> 1 Clark County 2021 319293 100
#> 2 Clark County 2022 320245 100.3
#> 3 Clark County 2023 314372 98.5
#> 4 Clark County 2024 309397 96.9
#> 5 Clark County 2026 291587 91.3
#> 6 Washoe County 2021 64988 100
#> 7 Washoe County 2022 66541 102.4
#> 8 Washoe County 2023 64990 100
#> 9 Washoe County 2024 64755 99.6
#> 10 Washoe County 2026 63655 97.9
Clark vs Washoe enrollment trends
6. Hispanic students are 46% of Nevada enrollment, down slightly from 47% in 2021
Hispanic students are the largest demographic group in Nevada public schools at 45.9%, followed by white students at 25.9%. Hispanic share dipped from 46.8% in 2021 to 45.9% in 2026, a modest decrease even as Hispanic students remain the largest group.
demographics <- enr_2026 |>
filter(is_district, grade_level == "TOTAL",
subgroup %in% c("white", "black", "hispanic", "asian",
"native_american", "multiracial", "pacific_islander")) |>
group_by(subgroup) |>
summarize(n_students = sum(n_students, na.rm = TRUE), .groups = "drop") |>
mutate(pct = round(n_students / sum(n_students) * 100, 1)) |>
arrange(desc(n_students))
stopifnot(nrow(demographics) == 7)
demographics
#> # A tibble: 7 x 3
#> subgroup n_students pct
#> <chr> <dbl> <dbl>
#> 1 hispanic 217320 45.9
#> 2 white 122852 25.9
#> 3 black 58830 12.4
#> 4 multiracial 37516 7.9
#> 5 asian 27170 5.7
#> 6 pacific_islander 6622 1.4
#> 7 native_american 3347 0.7
Nevada student demographics
7. Las Vegas Metro has 61.6% of all Nevada students
Beyond Las Vegas and Reno, the remaining 68 entities (15 rural county districts plus charter schools) account for 25% of enrollment.
regional <- enr_2026 |>
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL") |>
mutate(region = case_when(
grepl("Clark", district_name) ~ "Las Vegas Metro",
grepl("Washoe", district_name) ~ "Reno Metro",
TRUE ~ "Rest of Nevada"
)) |>
group_by(region) |>
summarize(
n_entities = n_distinct(district_name),
total_enrollment = sum(n_students, na.rm = TRUE),
.groups = "drop"
) |>
mutate(pct = round(total_enrollment / sum(total_enrollment) * 100, 1))
stopifnot(nrow(regional) == 3)
regional
#> # A tibble: 3 x 4
#> region n_entities total_enrollment pct
#> <chr> <int> <dbl> <dbl>
#> 1 Las Vegas Metro 1 291587 61.6
#> 2 Reno Metro 1 63655 13.4
#> 3 Rest of Nevada 68 118415 25.0
Enrollment by region
8. Fifteen districts report 100% FRL eligibility
FRL eligibility is a proxy for economic disadvantage. Many charter schools report 100% FRL, along with two rural counties (Esmeralda and Pershing). The variation across districts is enormous.
frl_data <- enr_2026 |>
filter(is_district, grade_level == "TOTAL", subgroup == "free_reduced_lunch") |>
mutate(pct_display = round(pct * 100, 1)) |>
arrange(desc(pct)) |>
head(15) |>
select(district_name, n_students, pct_display)
stopifnot(nrow(frl_data) > 0)
frl_data
#> # A tibble: 15 x 3
#> district_name n_students pct_display
#> <chr> <dbl> <dbl>
#> 1 Esmeralda County School District 69 100
#> 2 Pershing County School District 647 100
#> 3 Futuro Academy 484 100
#> 4 Mater Academy of Northern Nevada 514 100
#> 5 Democracy Prep 927 100
#> 6 Sports Leadership and Management Academy 1988 100
#> 7 Equipo Academy 949 100
#> 8 Mater Academy of Nevada 5297 100
#> 9 Rainbow Dreams Early Learning Academy 229 100
#> 10 The Delta Academy 1315 100
#> 11 Innovations International Charter School 619 100
#> 12 Quest Academy 415 100
#> 13 FuturEdge Academy 318 100
#> 14 Southern Nevada Trades High School 250 100
#> 15 Vegas Vista Academy 270 100
FRL eligibility by district
9. Futuro Academy has the highest EL concentration at 41%
English Learner populations vary dramatically. Clark County leads in absolute numbers (45,993), but several charter schools have much higher EL concentrations. Futuro Academy leads at 41.1% EL students, followed by Equipo Academy at 38.5%.
el_data <- enr_2026 |>
filter(is_district, grade_level == "TOTAL", subgroup == "lep") |>
arrange(desc(n_students)) |>
head(10) |>
select(district_name, n_students, pct)
stopifnot(nrow(el_data) == 10)
el_data
#> # A tibble: 10 x 3
#> district_name n_students pct
#> <chr> <dbl> <dbl>
#> 1 Clark County School District 45993 0.158
#> 2 Washoe County School District 9229 0.145
#> 3 Mater Academy of Nevada 1816 0.343
#> 4 Carson City School District 916 0.126
#> 5 Elko County School District 774 0.083
#> 6 Lyon County School District 637 0.070
#> 7 Nye County School District 449 0.077
#> 8 Somerset Academy of Las Vegas 405 0.042
#> 9 CIVICA Academy 403 0.280
#> 10 Equipo Academy 365 0.385
English Learner enrollment by district
10. Clark County has 5x more EL students than Washoe but similar FRL rates
English Learners, students with IEPs, and Free/Reduced Lunch eligible students represent key populations for educational policy. Clark County has ~46,000 EL students vs Washoe’s ~9,200.
special_pops <- enr_2026 |>
filter(is_district, grade_level == "TOTAL",
subgroup %in% c("free_reduced_lunch", "special_ed", "lep"),
grepl("Clark|Washoe", district_name)) |>
mutate(county = ifelse(grepl("Clark", district_name), "Clark County", "Washoe County")) |>
group_by(county, subgroup) |>
summarize(n_students = sum(n_students, na.rm = TRUE), .groups = "drop")
stopifnot(nrow(special_pops) == 6)
special_pops
#> # A tibble: 6 x 3
#> county subgroup n_students
#> <chr> <chr> <dbl>
#> 1 Clark County free_reduced_lunch 282969
#> 2 Clark County lep 45993
#> 3 Clark County special_ed 44484
#> 4 Washoe County free_reduced_lunch 39010
#> 5 Washoe County lep 9229
#> 6 Washoe County special_ed 10537
Special populations by district
11. 12th grade has the most students; PK has the fewest
Tracking enrollment by grade reveals a classic pattern: PK is small (13,852), enrollment jumps at K (30,490), and peaks at 12th grade (37,730). Grade-level data is available at the school level.
grade_data <- enr_2026 |>
filter(is_school, subgroup == "total_enrollment",
!grade_level %in% c("TOTAL", "UG", "AD")) |>
group_by(grade_level) |>
summarize(n_students = sum(n_students, na.rm = TRUE), .groups = "drop") |>
mutate(grade_level = factor(grade_level, levels = c("PK", "K", sprintf("%02d", 1:12)))) |>
filter(!is.na(grade_level))
stopifnot(nrow(grade_data) > 0)
grade_data
#> # A tibble: 14 x 2
#> grade_level n_students
#> <fct> <dbl>
#> 1 PK 13852
#> 2 K 30490
#> 3 01 31486
#> 4 02 30265
#> 5 03 33417
#> 6 04 35890
#> 7 05 34847
#> 8 06 35814
#> 9 07 36276
#> 10 08 36577
#> 11 09 37251
#> 12 10 37010
#> 13 11 37217
#> 14 12 37730
Enrollment by grade level
12. Nevada’s smallest LEAs are charter schools, not counties
While Esmeralda County (69 students) is the smallest county district, Nevada’s smallest LEAs are micro-charters. Nevada State High School II has just 18 students.
smallest <- enr_2026 |>
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL") |>
arrange(n_students) |>
head(10) |>
select(district_name, n_students, is_charter)
stopifnot(nrow(smallest) == 10)
smallest
#> # A tibble: 10 x 3
#> district_name n_students is_charter
#> <chr> <dbl> <lgl>
#> 1 Nevada State High School II 18 TRUE
#> 2 Independence High School 37 FALSE
#> 3 Esmeralda County School District 69 FALSE
#> 4 Nevada Classical Academy Elko 83 TRUE
#> 5 Young Women's Leadership Academy of Las Vegas 108 TRUE
#> 6 Learning Bridge 171 TRUE
#> 7 Davidson Academy 171 FALSE
#> 8 Do & Be Arts Academy of Excellence 175 TRUE
#> 9 Silver Sands Montessori 188 TRUE
#> 10 Honors Academy of Literature 202 TRUE
Nevada’s smallest districts
13. Lyon County has the highest IEP rate among large districts at 17%
Students with IEPs require specialized services. Clark County has the most IEP students by count (44,484), but Lyon County has the highest rate among sizable districts at 17%.
iep_data <- enr_2026 |>
filter(is_district, grade_level == "TOTAL", subgroup == "special_ed") |>
mutate(pct_display = round(pct * 100, 1)) |>
arrange(desc(n_students)) |>
head(10) |>
select(district_name, n_students, pct_display)
stopifnot(nrow(iep_data) == 10)
iep_data
#> # A tibble: 10 x 3
#> district_name n_students pct_display
#> <chr> <dbl> <dbl>
#> 1 Clark County School District 44484 15.3
#> 2 Washoe County School District 10537 16.6
#> 3 Lyon County School District 1541 17.0
#> 4 Somerset Academy of Las Vegas 1258 13.2
#> 5 Elko County School District 1238 13.3
#> 6 Carson City School District 943 13.0
#> 7 Nye County School District 882 15.2
#> 8 Pinecrest Academy of Nevada 840 9.9
#> 9 Douglas County School District 692 14.6
#> 10 Doral Academy 674 10.5
IEP students by district
14. Washoe County lost 1,333 students over 5 years
Washoe County (Reno-Sparks) is Nevada’s second-largest district. It peaked at 66,541 in 2022 before declining.
washoe_data <- enr |>
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL",
grepl("Washoe", district_name)) |>
group_by(end_year) |>
summarize(n_students = sum(n_students, na.rm = TRUE), .groups = "drop") |>
mutate(change = n_students - lag(n_students),
pct_change = round(change / lag(n_students) * 100, 2))
stopifnot(nrow(washoe_data) > 0)
washoe_data
#> # A tibble: 5 x 4
#> end_year n_students change pct_change
#> <dbl> <dbl> <dbl> <dbl>
#> 1 2021 64988 NA NA
#> 2 2022 66541 1553 2.39
#> 3 2023 64990 -1551 -2.33
#> 4 2024 64755 -235 -0.36
#> 5 2026 63655 -1100 -1.70
Washoe County enrollment
15. Boys outnumber girls 51.3% to 48.7% statewide
The gender split across Nevada schools is close to even, with a slight male skew consistent with national patterns.
gender_data <- enr_2026 |>
filter(is_district, grade_level == "TOTAL",
subgroup %in% c("male", "female")) |>
group_by(subgroup) |>
summarize(n_students = sum(n_students, na.rm = TRUE), .groups = "drop") |>
mutate(pct = round(n_students / sum(n_students) * 100, 1))
stopifnot(nrow(gender_data) == 2)
gender_data
#> # A tibble: 2 x 3
#> subgroup n_students pct
#> <chr> <dbl> <dbl>
#> 1 female 230511 48.7
#> 2 male 243022 51.3
Enrollment by gender