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Graduation Rates

The percentage of students who graduate high school within four years, by school.

rcd_acc_cgr
Rows
239,072
Schools & agencies
913
Years covered
2005–06 to 2023–24
Values suppressed
20.8%
by the state's privacy rules
Clear
suppressed means the state deliberately hid that value. When a student group is small enough that a published number could identify individual students — fewer than 10 students measured, or a rate above 95% or below 5% — states suppress it. Hover a suppressed cell to see which rule applied. This site keeps every suppression intact.
School Rate Type Students in Cohort % Graduating Student Group School Year
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 432 59.7 All Students 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 92 60.9 Black 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 237 63.3 Economically Disadvantaged 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 239 61.5 Female 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 61 52.5 Hispanic 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 21 38.1 Homeless 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 193 57.5 Male 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 42 69 Two or More Races 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 195 55.4 Not Economically Disadvantaged 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 424 60.1 Not English Learners 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 376 59.8 Not Students With Disabilities 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 56 58.9 Students With Disabilities 2023–24
North Carolina Cyber Academy 00A000 5-Year Cohort Graduation rate 224 59.4 White 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 375 60 All Students 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 86 59.3 Black 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 232 61.6 Economically Disadvantaged 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 10 40 English Learners 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 228 61.8 Female 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 59 64.4 Hispanic 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 12 33.3 Homeless 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 147 57.1 Male 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 20 40 Two or More Races 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 143 57.3 Not Economically Disadvantaged 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 365 60.5 Not English Learners 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 307 62.2 Not Students With Disabilities 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 68 50 Students With Disabilities 2023–24
North Carolina Cyber Academy 00A000 4-Year Cohort Graduation Rate 201 61.7 White 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 221 79.6 All Students 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 48 87.5 Black 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 116 87.9 Economically Disadvantaged 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 134 81.3 Female 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 25 76 Hispanic 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 87 77 Male 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 16 87.5 Two or More Races 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 105 70.5 Not Economically Disadvantaged 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 219 79.9 Not English Learners 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 186 81.2 Not Students With Disabilities 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 35 71.4 Students With Disabilities 2023–24
NC Virtual Academy 00B000 5-Year Cohort Graduation rate 128 75.8 White 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 218 72 All Students 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 55 74.5 Black 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 109 72.5 Economically Disadvantaged 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 122 76.2 Female 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 18 77.8 Hispanic 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 96 66.7 Male 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 13 61.5 Two or More Races 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 109 71.6 Not Economically Disadvantaged 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 216 71.8 Not English Learners 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 187 74.3 Not Students With Disabilities 2023–24
NC Virtual Academy 00B000 4-Year Cohort Graduation Rate 31 58.1 Students With Disabilities 2023–24
Column dictionary — the state's own definitions
Shown as State's column Data type State's description Codes
School key agency_code VARCHAR(6) 010303/010LEA/NC-SEA
Rate Type key cgr_type VARCHAR(3) Report Type (STD/EXT)
2 codes
  • EXT → 5-Year Cohort Graduation rate
  • STD → 4-Year Cohort Graduation Rate
Students in Cohort den NUMERIC(38,0) Denominator
% Graduating pct NUMERIC(4,1) Percent (<5,>95 masked as 5,95, and no row for den<10)
Student Group key subgroup VARCHAR(6) Subgroup
26 codes
  • AIAN → American Indian / Alaskan Native
  • AIG → Academically / Intellectually Gifted
  • ALL → All Students
  • AM7 → American Indian
  • AS7 → Asian
  • ASPI → Pacific Islander / Asian
  • BL7 → Black
  • EDS → Economically Disadvantaged
  • ELS → English Learners
  • FCS → Foster Care
  • FEM → Female
  • HI7 → Hispanic
  • HMS → Homeless
  • MALE → Male
  • MIG → Migrant
  • MIL → Military Connected
  • MU7 → Two or More Races
  • NAIG → Not Academically / Intellectually Gifted
  • NEDS → Not Economically Disadvantaged
  • NELS → Not English Learners
  • NOT_EDS → Not Economically Disadvantaged
  • NSWD → Not Students With Disabilities
  • Other → Other
  • PI7 → Pacific Islander
  • SWD → Students With Disabilities
  • WH7 → White
School Year key year VARCHAR(4) YYYY (i.e. 2006 for the 2005/06 school year)
About this table

State's description: accountability - indicator data - cohort graduation rate

Listed in the state's table index as rcd_acc_cgr (active, 2016)

239,072 rows loaded, covering 913 schools and agencies, 2005–06 to 2023–24.

How this table got here
  1. The state publishes an Excel data dictionary. This demo reads it: 66 table definitions, 525 column definitions, and 181 code definitions — the same ones behind the Decoded view above.
  2. From those definitions it writes a Django database model for each table, so nobody has to type the columns in by hand. This table's model came out like this:
class RcdAccCgr(SRCBaseModel):
    agency_code = models.CharField(max_length=6)
    cgr_type = models.CharField(max_length=3)
    den = models.DecimalField(max_digits=38, decimal_places=0, null=True, blank=True)
    masking = models.CharField(
        max_length=192,
        null=True,
        blank=True,
        choices=[
            ("1", ">95%"),
            ("2", "<5%"),
            ("3", "<10 in denominator"),
            (
                "4",
                "Insufficient Data (per business area, specific alternate minimum denominator, there is not enough"
                " data to provide a meaningful answer - additional set of masking rules on a case by case basis)",
            ),
        ],
    )
    pct = models.DecimalField(max_digits=4, decimal_places=1, null=True, blank=True)
    subgroup = models.CharField(
        max_length=40,
        choices=[
            ("EDS", "Economically Disadvantaged"),
            ("NEDS", "Not Economically Disadvantaged"),
            ("NOT_EDS", "Not Economically Disadvantaged"),
            ("ELS", "English Learners"),
            ("NELS", "Not English Learners"),
            ("SWD", "Students With Disabilities"),
            ("NSWD", "Not Students With Disabilities"),
            ("WH7", "White"),
            ("BL7", "Black"),
            ("HI7", "Hispanic"),
            ("AM7", "American Indian"),
            ("AS7", "Asian"),
            ("MU7", "Two or More Races"),
            ("MALE", "Male"),
            ("FEM", "Female"),
            ("ALL", "All Students"),
            ("AIG", "Academically / Intellectually Gifted"),
            ("NAIG", "Not Academically / Intellectually Gifted"),
            ("PI7", "Pacific Islander"),
            ("HMS", "Homeless"),
            ("FCS", "Foster Care"),
            ("MIL", "Military Connected"),
            ("MIG", "Migrant"),
            ("AIAN", "American Indian / Alaskan Native"),
            ("ASPI", "Pacific Islander / Asian"),
            ("Other", "Other"),
        ],
    )
    year = models.CharField(max_length=4)

    class Meta:
        db_table = "rcd_acc_cgr"
        managed = True
        unique_together = ("year", "agency_code", "cgr_type", "subgroup")
  1. 239,072 rows were then loaded from the state's raw data files into RcdAccCgr.
  2. It also takes a fingerprint (SHA-256) of the dictionary's general-rules sheet. If the state quietly rewrites its rules document, the next rebuild flags the change instead of absorbing it silently.
Want something like this for your program? Schedule a conversation or email matt@mattniksch.com.