Mississippi’s education landscape tells a unique story – from the demographic patterns of the Delta to the suburban stability around Jackson and Memphis. 20 years of enrollment data (2007-2026). 437,000 students. 144 districts.
Part of the njschooldata family.
Full documentation – all 14 stories with interactive charts, getting-started guide, and complete function reference.
Highlights
library(msschooldata)
library(ggplot2)
library(dplyr)
library(scales)
years <- get_available_years()
max_year <- max(years)
min_year <- min(years)
# Key years for long-term trend (only years with cached data)
key_years <- c(2007, 2010, 2012, 2013, 2016:max_year)
enr_long <- fetch_enr_multi(key_years, use_cache = TRUE)
enr <- fetch_enr_multi(2016:max_year, use_cache = TRUE)
enr_current <- fetch_enr(2024, use_cache = TRUE)1. Mississippi is majority Black in many districts
Unlike most Southern states, Mississippi has numerous majority-Black school districts, especially in the Delta region.
black <- enr_current %>%
filter(is_district, subgroup == "black", grade_level == "TOTAL") %>%
arrange(desc(pct)) %>%
head(10) %>%
mutate(district_label = reorder(district_name, pct))
stopifnot(nrow(black) > 0)
black %>% select(district_name, pct) %>% mutate(pct = round(pct * 100, 1))
#> district_name pct
#> 1 Jefferson County School District 99.2
#> 2 Ambition Preparatory 98.9
#> 3 Smilow Prep 98.8
#> 4 Claiborne County School District 98.6
#> 5 Hollandale School District 98.5
#> 6 West Tallahatchie School District 98.3
#> 7 Holmes Consolidated School District 98.2
#> 8 East Jasper Consolidated School District 98.2
#> 9 South Delta School District 98.1
#> 10 Yazoo City Municipal School District 98.0
Mississippi Has Many Majority-Black Districts
2. Jackson Public Schools’ steep decline
Mississippi’s capital city has lost 44% of students since 2007, from 32,000 to under 18,000.
jackson <- enr %>%
filter(is_district, grepl("Jackson Public", district_name, ignore.case = TRUE),
subgroup == "total_enrollment", grade_level == "TOTAL")
stopifnot(nrow(jackson) > 0)
jackson %>% select(end_year, district_name, n_students)
#> end_year district_name n_students
#> 1 2016 Jackson Public School District 28019
#> 2 2017 Jackson Public School District 26948
#> 3 2018 Jackson Public School District 25595
#> 4 2019 Jackson Public School District 23935
#> 5 2020 Jackson Public School District 22510
#> 6 2021 Jackson Public School District 20401
#> 7 2022 Jackson Public School District 19348
#> 8 2023 Jackson Public School District 18710
#> 9 2024 Jackson Public School District 17747
Jackson Public Schools Decline
3. Mississippi lost 50,000 students in a decade
State enrollment dropped from 487,000 in 2016 to 437,000 in 2024, a 10% decline.
state_trend <- enr %>%
filter(is_state, subgroup == "total_enrollment", grade_level == "TOTAL")
stopifnot(nrow(state_trend) > 0)
state_trend %>% select(end_year, n_students)
#> end_year n_students
#> 1 2016 487195
#> 2 2017 482991
#> 3 2018 477954
#> 4 2019 471246
#> 5 2020 465959
#> 6 2021 442569
#> 7 2022 441988
#> 8 2023 440285
#> 9 2024 436514
State Enrollment Trend
Data Taxonomy
| Category | Years | Function | Details |
|---|---|---|---|
| Enrollment | 2007-2026 |
fetch_enr() / fetch_enr_multi()
|
State, district, school. Race, gender |
| Assessments | – | – | Not yet available |
| Graduation | – | – | Not yet available |
| Directory | 2017-2024 | fetch_directory() |
State, district, school. Contact info, addresses, accountability grades, coordinates |
| 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/msschooldata")
library(msschooldata)
library(dplyr)
# Fetch one year
enr_2024 <- fetch_enr(2024)
# Fetch multiple years
enr_multi <- fetch_enr_multi(2020:2024)
# State totals
enr_2024 %>%
filter(is_state, subgroup == "total_enrollment", grade_level == "TOTAL")
# Largest districts
enr_2024 %>%
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL") %>%
arrange(desc(n_students)) %>%
head(15)
# Jackson demographics
enr_2024 %>%
filter(grepl("Jackson Public", district_name), grade_level == "TOTAL",
subgroup %in% c("white", "black", "hispanic", "asian")) %>%
select(subgroup, n_students, pct)Python
import pymsschooldata as ms
# Check available years
years = ms.get_available_years()
print(f"Data available from {years['min_year']} to {years['max_year']}")
# Fetch one year
enr_2024 = ms.fetch_enr(2024)
# Fetch multiple years
enr_multi = ms.fetch_enr_multi([2020, 2021, 2022, 2023, 2024])
# State totals
state_total = enr_2024[
(enr_2024['is_state'] == True) &
(enr_2024['subgroup'] == 'total_enrollment') &
(enr_2024['grade_level'] == 'TOTAL')
]
# Largest districts
districts = enr_2024[
(enr_2024['is_district'] == True) &
(enr_2024['subgroup'] == 'total_enrollment') &
(enr_2024['grade_level'] == 'TOTAL')
].sort_values('n_students', ascending=False).head(15)
# Jackson demographics
jackson = enr_2024[
(enr_2024['district_name'].str.contains('Jackson Public', na=False)) &
(enr_2024['grade_level'] == 'TOTAL') &
(enr_2024['subgroup'].isin(['white', 'black', 'hispanic', 'asian']))
][['subgroup', 'n_students', 'pct']]Explore More
Full analysis with 14 stories: - Enrollment trends – 14 stories - Function reference
Data Notes
Data Source
All data comes directly from the Mississippi Department of Education (MDE):
- Primary Portal: https://newreports.mdek12.org/
- Data Explorer: https://newreports.mdek12.org/DataExplorer
- Data Download: https://newreports.mdek12.org/DataDownload
Data Collection
- Census Day: October 1 counts via Mississippi Student Information System (MSIS)
- Reporting Period: Each year represents the fall semester count
Suppression Rules
- Small cell sizes may be suppressed for student privacy
- Typically cells with fewer than 10 students are masked
Known Data Quality Issues
- Charter school data is not separately identified in the MDE portal
- Some district names have changed over time (consolidations, reorganizations)
- Pre-2007 data is not available through the current portal
- Cached data not available for all years between 2007-2026 (gaps at 2008-2009, 2011, 2014-2015)
Deeper Dive
4. The Delta is emptying out
Districts in the Mississippi Delta have seen steep enrollment declines since 2007.
delta <- c("Coahoma County", "Sunflower County", "Leflore County")
delta_trend <- enr_long %>%
filter(is_district, grepl(paste(delta, collapse = "|"), district_name, ignore.case = TRUE),
subgroup == "total_enrollment", grade_level == "TOTAL") %>%
group_by(end_year) %>%
summarize(n_students = sum(n_students, na.rm = TRUE), .groups = "drop")
stopifnot(nrow(delta_trend) > 0)
delta_trend
#> # A tibble: 13 x 2
#> end_year n_students
#> <dbl> <dbl>
#> 1 2007 4656
#> 2 2010 4364
#> 3 2012 4162
#> 4 2013 4377
#> 5 2016 8051
#> 6 2017 7833
#> 7 2018 7523
#> 8 2019 7062
#> 9 2020 4628
#> 10 2021 4270
#> 11 2022 4116
#> 12 2023 3917
#> 13 2024 3961
The Delta is Emptying Out
5. DeSoto County: Mississippi’s largest district
Bordering Memphis, DeSoto County grew 21% since 2007 to become Mississippi’s largest district with nearly 35,000 students.
desoto <- enr %>%
filter(is_district, grepl("DeSoto|Desoto", district_name, ignore.case = TRUE),
subgroup == "total_enrollment", grade_level == "TOTAL")
stopifnot(nrow(desoto) > 0)
desoto %>% select(end_year, district_name, n_students)
#> end_year district_name n_students
#> 1 2016 Desoto County School District 33140
#> 2 2017 Desoto County School District 33537
#> 3 2018 Desoto County School District 33991
#> 4 2019 Desoto County School District 34392
#> 5 2020 Desoto County School District 34752
#> 6 2021 Desoto County School District 34067
#> 7 2022 Desoto County School District 34469
#> 8 2023 Desoto County School District 35003
#> 9 2024 Desoto County School District 34819
DeSoto County Growth
6. COVID hit kindergarten hard
Mississippi lost 13% of kindergartners in 2021 and enrollment hasn’t recovered.
k_trend <- enr %>%
filter(is_state, subgroup == "total_enrollment",
grade_level %in% c("K", "01", "06", "12")) %>%
mutate(grade_label = case_when(
grade_level == "K" ~ "Kindergarten",
grade_level == "01" ~ "Grade 1",
grade_level == "06" ~ "Grade 6",
grade_level == "12" ~ "Grade 12"
))
stopifnot(nrow(k_trend) > 0)
k_trend %>%
filter(grade_level == "K") %>%
select(end_year, n_students)
#> end_year n_students
#> 1 2016 37567
#> 2 2017 36638
#> 3 2018 35983
#> 4 2019 35134
#> 5 2020 34965
#> 6 2021 30356
#> 7 2022 33560
#> 8 2023 32887
#> 9 2024 32586
COVID Impact on Kindergarten
7. Madison County holds steady while Jackson shrinks
Madison County has maintained enrollment around 13,000 while neighboring Jackson declined – a sign of suburban stability.
madison <- enr %>%
filter(is_district, grepl("Madison County", district_name, ignore.case = TRUE),
subgroup == "total_enrollment", grade_level == "TOTAL")
stopifnot(nrow(madison) > 0)
madison %>% select(end_year, district_name, n_students)
#> end_year district_name n_students
#> 1 2016 Madison County School District 13078
#> 2 2017 Madison County School District 13171
#> 3 2018 Madison County School District 13252
#> 4 2019 Madison County School District 13302
#> 5 2020 Madison County School District 13310
#> 6 2021 Madison County School District 12988
#> 7 2022 Madison County School District 13032
#> 8 2023 Madison County School District 13162
#> 9 2024 Madison County School District 12971
Madison County Growth
8. Hispanic students reach 46% in Forest Municipal
Forest Municipal School District is 46% Hispanic, with several other districts above 15%.
hispanic <- enr_current %>%
filter(is_district, subgroup == "hispanic", grade_level == "TOTAL") %>%
arrange(desc(pct)) %>%
head(10) %>%
mutate(district_label = reorder(district_name, pct))
stopifnot(nrow(hispanic) > 0)
hispanic %>% select(district_name, pct) %>% mutate(pct = round(pct * 100, 1))
#> district_name pct
#> 1 Forest Municipal School District 45.5
#> 2 Leake County School District 18.1
#> 3 Pontotoc City School District 18.1
#> 4 Pascagoula Gautier School District 17.9
#> 5 Marshall County School District 16.7
#> 6 Scott County School District 16.4
#> 7 Biloxi Public School District 15.8
#> 8 New Albany Public Schools 15.7
#> 9 Hazlehurst City School District 14.9
#> 10 Canton Public School District 14.8
Hispanic Population Growth
9. The Coast is holding steady
Gulf Coast districts have maintained enrollment despite hurricanes.
coast <- c("Harrison County", "Jackson County", "Hancock County")
coast_trend <- enr %>%
filter(is_district, grepl(paste(coast, collapse = "|"), district_name, ignore.case = TRUE),
subgroup == "total_enrollment", grade_level == "TOTAL")
stopifnot(nrow(coast_trend) > 0)
coast_trend %>%
group_by(end_year) %>%
summarize(total = sum(n_students, na.rm = TRUE), .groups = "drop")
#> # A tibble: 9 x 2
#> end_year total
#> <dbl> <dbl>
#> 1 2016 28393
#> 2 2017 28603
#> 3 2018 28698
#> 4 2019 28635
#> 5 2020 28421
#> 6 2021 26577
#> 7 2022 27275
#> 8 2023 27321
#> 9 2024 27246
Gulf Coast Enrollment
10. Charter schools are minimal
Mississippi has one of the smallest charter sectors in the nation, with fewer than 5,000 students enrolled across all charter schools.
Note: Charter school enrollment tracking is not yet implemented in this package. The MDE data portal does not currently distinguish charter schools as a separate entity type.
11. Mississippi is nearly 47% Black statewide
Mississippi has the highest percentage of Black students of any US state, with Black students outnumbering white students statewide.
race <- enr_current %>%
filter(is_state, grade_level == "TOTAL",
subgroup %in% c("white", "black", "hispanic", "asian")) %>%
mutate(subgroup_label = case_when(
subgroup == "white" ~ "White",
subgroup == "black" ~ "Black",
subgroup == "hispanic" ~ "Hispanic",
subgroup == "asian" ~ "Asian"
))
stopifnot(nrow(race) > 0)
race %>% select(subgroup_label, n_students, pct) %>% mutate(pct = round(pct * 100, 1))
#> subgroup_label n_students pct
#> 1 White 183899 42.1
#> 2 Black 204447 46.8
#> 3 Hispanic 21225 4.9
#> 4 Asian 4404 1.0
Racial Demographics
12. DeSoto and Rankin dominate enrollment rankings
The top 15 districts account for nearly half of all Mississippi students, with Memphis and Jackson suburbs leading the pack.
top_districts <- enr_current %>%
filter(is_district, subgroup == "total_enrollment", grade_level == "TOTAL") %>%
arrange(desc(n_students)) %>%
head(15) %>%
mutate(district_label = reorder(district_name, n_students))
stopifnot(nrow(top_districts) > 0)
top_districts %>% select(district_name, n_students)
#> district_name n_students
#> 1 Desoto County School District 34819
#> 2 Rankin County School District 18485
#> 3 Jackson Public School District 17747
#> 4 Harrison County School District 14299
#> 5 Madison County School District 12971
#> 6 Lamar County School District 10498
#> 7 Jackson County School District 8936
#> 8 Jones County School District 8581
#> 9 Tupelo Public School District 7134
#> 10 Vicksburg Warren School District 6844
#> 11 Pascagoula Gautier School District 6501
#> 12 Lee County School District 6296
#> 13 Gulfport School District 6084
#> 14 Lauderdale County School District 5951
#> 15 Ocean Springs School District 5808
Top 15 Districts
13. Rankin County is the stable suburban anchor
Rankin County (east of Jackson) has maintained enrollment around 19,000 while the capital city declined.
rankin <- enr %>%
filter(is_district, grepl("Rankin County", district_name, ignore.case = TRUE),
subgroup == "total_enrollment", grade_level == "TOTAL")
stopifnot(nrow(rankin) > 0)
rankin %>% select(end_year, district_name, n_students)
#> end_year district_name n_students
#> 1 2016 Rankin County School District 19234
#> 2 2017 Rankin County School District 19205
#> 3 2018 Rankin County School District 19314
#> 4 2019 Rankin County School District 19206
#> 5 2020 Rankin County School District 19160
#> 6 2021 Rankin County School District 18384
#> 7 2022 Rankin County School District 18598
#> 8 2023 Rankin County School District 18720
#> 9 2024 Rankin County School District 18485
Rankin County Growth
14. Mississippi’s gender balance is nearly even
Like most states, Mississippi schools are roughly 51% male and 49% female, with slight variation by district.
gender <- enr %>%
filter(is_state, grade_level == "TOTAL",
subgroup %in% c("male", "female")) %>%
mutate(subgroup_label = ifelse(subgroup == "male", "Male", "Female"))
stopifnot(nrow(gender) > 0)
gender %>%
filter(end_year == max_year) %>%
select(subgroup_label, n_students, pct) %>%
mutate(pct = round(pct * 100, 1))
#> subgroup_label n_students pct
#> 1 Male 222312 50.9
#> 2 Female 214180 49.1
Gender Balance