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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

This is exactly how the state publishes it — raw column names, raw codes.

Decode this table
id agency_code cgr_type den masking pct subgroup year
218425 00A000 EXT 432 59.7 ALL 2024
218426 00A000 EXT 92 60.9 BL7 2024
218427 00A000 EXT 237 63.3 EDS 2024
218428 00A000 EXT 239 61.5 FEM 2024
218429 00A000 EXT 61 52.5 HI7 2024
218430 00A000 EXT 21 38.1 HMS 2024
218431 00A000 EXT 193 57.5 MALE 2024
218432 00A000 EXT 42 69.0 MU7 2024
218433 00A000 EXT 195 55.4 NEDS 2024
218434 00A000 EXT 424 60.1 NELS 2024
218435 00A000 EXT 376 59.8 NSWD 2024
218436 00A000 EXT 56 58.9 SWD 2024
218437 00A000 EXT 224 59.4 WH7 2024
218438 00A000 STD 375 60.0 ALL 2024
218439 00A000 STD 86 59.3 BL7 2024
218440 00A000 STD 232 61.6 EDS 2024
218441 00A000 STD 10 40.0 ELS 2024
218442 00A000 STD 228 61.8 FEM 2024
218443 00A000 STD 59 64.4 HI7 2024
218444 00A000 STD 12 33.3 HMS 2024
218445 00A000 STD 147 57.1 MALE 2024
218446 00A000 STD 20 40.0 MU7 2024
218447 00A000 STD 143 57.3 NEDS 2024
218448 00A000 STD 365 60.5 NELS 2024
218449 00A000 STD 307 62.2 NSWD 2024
218450 00A000 STD 68 50.0 SWD 2024
218451 00A000 STD 201 61.7 WH7 2024
218452 00B000 EXT 221 79.6 ALL 2024
218453 00B000 EXT 48 87.5 BL7 2024
218454 00B000 EXT 116 87.9 EDS 2024
218455 00B000 EXT 134 81.3 FEM 2024
218456 00B000 EXT 25 76.0 HI7 2024
218457 00B000 EXT 87 77.0 MALE 2024
218458 00B000 EXT 16 87.5 MU7 2024
218459 00B000 EXT 105 70.5 NEDS 2024
218460 00B000 EXT 219 79.9 NELS 2024
218461 00B000 EXT 186 81.2 NSWD 2024
218462 00B000 EXT 35 71.4 SWD 2024
218463 00B000 EXT 128 75.8 WH7 2024
218464 00B000 STD 218 72.0 ALL 2024
218465 00B000 STD 55 74.5 BL7 2024
218466 00B000 STD 109 72.5 EDS 2024
218467 00B000 STD 122 76.2 FEM 2024
218468 00B000 STD 18 77.8 HI7 2024
218469 00B000 STD 96 66.7 MALE 2024
218470 00B000 STD 13 61.5 MU7 2024
218471 00B000 STD 109 71.6 NEDS 2024
218472 00B000 STD 216 71.8 NELS 2024
218473 00B000 STD 187 74.3 NSWD 2024
218474 00B000 STD 31 58.1 SWD 2024
Column dictionary — the state's own definitions
Shown as State's column Data type State's description Codes
agency_code key agency_code VARCHAR(6) 010303/010LEA/NC-SEA
cgr_type key cgr_type VARCHAR(3) Report Type (STD/EXT)
2 codes
  • EXT → 5-Year Cohort Graduation rate
  • STD → 4-Year Cohort Graduation Rate
den den NUMERIC(38,0) Denominator
masking masking VARCHAR(1) Masking Code
4 codes
  • 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 pct NUMERIC(4,1) Percent (<5,>95 masked as 5,95, and no row for den<10)
subgroup 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
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.