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Chronic Absenteeism

The share of students who miss 10% or more of the school year.

rcd_chronic_absent
Rows
174,768
Schools & agencies
2,933
Years covered
2017–18 to 2023–24
Values suppressed
8.8%
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 count den masking pct subgroup year
146776 00A000 783.00 2969 0.3 ALL 2024
146777 00A000 12.00 29 0.4 AM7 2024
146778 00A000 13.00 77 0.2 AS7 2024
146779 00A000 243.00 841 0.3 BL7 2024
146780 00A000 585.00 2028 0.3 EDS 2024
146781 00A000 40.00 81 0.5 ELS 2024
146782 00A000 406.00 1630 0.2 FEM 2024
146783 00A000 143.00 493 0.3 HI7 2024
146784 00A000 377.00 1339 0.3 MALE 2024
146785 00A000 79.00 238 0.3 MU7 2024
146786 00A000 110.00 448 0.2 SWD 2024
146787 00A000 290.00 1282 0.2 WH7 2024
146788 00B000 3389 2.0 0.1 ALL 2024
146789 00B000 48 2.0 0.1 AM7 2024
146790 00B000 51 2.0 0.1 AS7 2024
146791 00B000 1032 2.0 0.1 BL7 2024
146792 00B000 2264 2.0 0.1 EDS 2024
146793 00B000 76 2.0 0.1 ELS 2024
146794 00B000 1750 2.0 0.1 FEM 2024
146795 00B000 471 2.0 0.1 HI7 2024
146796 00B000 1639 2.0 0.1 MALE 2024
146797 00B000 352 2.0 0.1 MU7 2024
146798 00B000 400 2.0 0.1 SWD 2024
146799 00B000 1426 2.0 0.1 WH7 2024
146800 010303 233 2.0 0.1 ALL 2024
146801 010303 12 2.0 0.1 AS7 2024
146802 010303 35 2.0 0.1 BL7 2024
146803 010303 79 2.0 0.1 EDS 2024
146804 010303 141 2.0 0.1 FEM 2024
146805 010303 67 2.0 0.1 HI7 2024
146806 010303 92 2.0 0.1 MALE 2024
146807 010303 13 2.0 0.1 MU7 2024
146808 010303 104 2.0 0.1 WH7 2024
146809 010304 97.00 613 0.2 ALL 2024
146810 010304 16 2.0 0.1 AS7 2024
146811 010304 9.00 67 0.1 BL7 2024
146812 010304 71.00 336 0.2 EDS 2024
146813 010304 15.00 86 0.2 ELS 2024
146814 010304 45.00 286 0.2 FEM 2024
146815 010304 30.00 166 0.2 HI7 2024
146816 010304 52.00 327 0.2 MALE 2024
146817 010304 7.00 48 0.1 MU7 2024
146818 010304 23.00 82 0.3 SWD 2024
146819 010304 51.00 315 0.2 WH7 2024
146820 010308 149.00 621 0.2 ALL 2024
146821 010308 21.00 87 0.2 BL7 2024
146822 010308 109.00 376 0.3 EDS 2024
146823 010308 26.00 76 0.3 ELS 2024
146824 010308 65.00 295 0.2 FEM 2024
146825 010308 41.00 143 0.3 HI7 2024
Column dictionary — the state's own definitions
Shown as State's column Data type State's description Codes
agency_code agency_code VARCHAR(6) 010303/010LEA/NC-SEA
count count NUMERIC COUNT Percentage
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 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 year VARCHAR(4) YYYY (i.e. 2006 for the 2005/06 school year)
About this table

State's description: 2021-2022 Percentage of students who were enrolled for at least 10 days in a school/district who are chronically absent from school. A student is defined as chronically absent when they are enrolled in a NC public school for at least 10 school days at any time during the school year, and whose total number of absences is = or > 10% of the total number of days that the student has been enrolled at any school during a given school year.

Listed in the state's table index as rcd_chronic_absent (active, 2018)

174,768 rows loaded, covering 2,933 schools and agencies, 2017–18 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 RcdChronicAbsent(SRCBaseModel):
    agency_code = models.CharField(max_length=6, null=True, blank=True)
    count = models.DecimalField(max_digits=10, decimal_places=2, null=True, blank=True)
    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,
        null=True,
        blank=True,
        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, null=True, blank=True)

    class Meta:
        db_table = "rcd_chronic_absent"
        managed = True
  1. 174,768 rows were then loaded from the state's raw data files into RcdChronicAbsent.
  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.