Overview

Dataset statistics

Number of variables9
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory80.5 B

Variable types

Numeric3
Categorical2
Text3
DateTime1

Dataset

Description경상북도 청도군 폐교 학교 현황자료이며 활용/미활용/매각 현황, 토지/건물의 면적, 활용/사용현황 자료임
Author경상북도교육청 경상북도청도교육지원청
URLhttps://www.data.go.kr/data/3069200/fileData.do

Alerts

번호 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
관리현황 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
번호 has unique valuesUnique
폐지학교명 has unique valuesUnique
소재지 has unique valuesUnique
토지면적(㎡) has unique valuesUnique
건물면적(㎡) has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:26:15.045542
Analysis finished2023-12-12 19:26:16.797363
Duration1.75 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T04:26:16.864957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2023-12-13T04:26:17.013316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
매각된 폐교
13 
활용중인 폐교
9 
미활용 폐교
2 

Length

Max length7
Median length6
Mean length6.375
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row활용중인 폐교
2nd row활용중인 폐교
3rd row활용중인 폐교
4th row활용중인 폐교
5th row활용중인 폐교

Common Values

ValueCountFrequency (%)
매각된 폐교 13
54.2%
활용중인 폐교 9
37.5%
미활용 폐교 2
 
8.3%

Length

2023-12-13T04:26:17.181989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:26:17.331362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐교 24
50.0%
매각된 13
27.1%
활용중인 9
 
18.8%
미활용 2
 
4.2%

폐지학교명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T04:26:17.561127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.7083333
Min length3

Characters and Unicode

Total characters137
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row매전초등학교
2nd row풍각초서부분교
3rd row동곡초김전분교
4th row대산초등학교
5th row청도동부초등학교
ValueCountFrequency (%)
매전초등학교 1
 
4.2%
풍각초서부분교 1
 
4.2%
관하초 1
 
4.2%
중남초 1
 
4.2%
유천초대현분교 1
 
4.2%
각북초 1
 
4.2%
풍각초성곡분교 1
 
4.2%
방지초봉하분교 1
 
4.2%
동곡초소천분교 1
 
4.2%
금천초임호분교 1
 
4.2%
Other values (14) 14
58.3%
2023-12-13T04:26:17.957921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 23
16.8%
교 17
 
12.4%
분 10
 
7.3%
등 8
 
5.8%
학 7
 
5.1%
각 6
 
4.4%
곡 5
 
3.6%
동 4
 
2.9%
천 4
 
2.9%
풍 4
 
2.9%
Other values (31) 49
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 23
16.8%
교 17
 
12.4%
분 10
 
7.3%
등 8
 
5.8%
학 7
 
5.1%
각 6
 
4.4%
곡 5
 
3.6%
동 4
 
2.9%
천 4
 
2.9%
풍 4
 
2.9%
Other values (31) 49
35.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 23
16.8%
교 17
 
12.4%
분 10
 
7.3%
등 8
 
5.8%
학 7
 
5.1%
각 6
 
4.4%
곡 5
 
3.6%
동 4
 
2.9%
천 4
 
2.9%
풍 4
 
2.9%
Other values (31) 49
35.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 23
16.8%
교 17
 
12.4%
분 10
 
7.3%
등 8
 
5.8%
학 7
 
5.1%
각 6
 
4.4%
곡 5
 
3.6%
동 4
 
2.9%
천 4
 
2.9%
풍 4
 
2.9%
Other values (31) 49
35.8%

폐교연도
Date

Distinct16
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum1987-03-01 00:00:00
Maximum2018-03-01 00:00:00
2023-12-13T04:26:18.081955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:18.208985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

소재지
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T04:26:18.408883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length20.916667
Min length19

Characters and Unicode

Total characters502
Distinct characters61
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row경상북도 청도군 매전면 온막리 42-4
2nd row경상북도 청도군 풍각면 안산리 585
3rd row경상북도 청도군 금천면 김전리 52
4th row경상북도 청도군 각남면 옥산리 15
5th row경상북도 청도군 청도읍 원리 412
ValueCountFrequency (%)
경상북도 24
20.0%
청도군 24
20.0%
운문면 5
 
4.2%
금천면 5
 
4.2%
매전면 3
 
2.5%
풍각면 3
 
2.5%
청도읍 2
 
1.7%
이서면 2
 
1.7%
남산리 2
 
1.7%
각북면 2
 
1.7%
Other values (48) 48
40.0%
2023-12-13T04:26:18.780282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
19.1%
도 50
 
10.0%
북 26
 
5.2%
청 26
 
5.2%
경 24
 
4.8%
리 24
 
4.8%
상 24
 
4.8%
군 24
 
4.8%
면 21
 
4.2%
1 20
 
4.0%
Other values (51) 167
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
62.0%
Space Separator 96
 
19.1%
Decimal Number 85
 
16.9%
Dash Punctuation 10
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 50
16.1%
북 26
 
8.4%
청 26
 
8.4%
경 24
 
7.7%
리 24
 
7.7%
상 24
 
7.7%
군 24
 
7.7%
면 21
 
6.8%
천 7
 
2.3%
전 6
 
1.9%
Other values (39) 79
25.4%
Decimal Number
ValueCountFrequency (%)
1 20
23.5%
2 12
14.1%
4 9
10.6%
3 8
 
9.4%
0 8
 
9.4%
5 7
 
8.2%
8 7
 
8.2%
7 5
 
5.9%
6 5
 
5.9%
9 4
 
4.7%
Space Separator
ValueCountFrequency (%)
96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
62.0%
Common 191
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 50
16.1%
북 26
 
8.4%
청 26
 
8.4%
경 24
 
7.7%
리 24
 
7.7%
상 24
 
7.7%
군 24
 
7.7%
면 21
 
6.8%
천 7
 
2.3%
전 6
 
1.9%
Other values (39) 79
25.4%
Common
ValueCountFrequency (%)
96
50.3%
1 20
 
10.5%
2 12
 
6.3%
- 10
 
5.2%
4 9
 
4.7%
3 8
 
4.2%
0 8
 
4.2%
5 7
 
3.7%
8 7
 
3.7%
7 5
 
2.6%
Other values (2) 9
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
62.0%
ASCII 191
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
50.3%
1 20
 
10.5%
2 12
 
6.3%
- 10
 
5.2%
4 9
 
4.7%
3 8
 
4.2%
0 8
 
4.2%
5 7
 
3.7%
8 7
 
3.7%
7 5
 
2.6%
Other values (2) 9
 
4.7%
Hangul
ValueCountFrequency (%)
도 50
16.1%
북 26
 
8.4%
청 26
 
8.4%
경 24
 
7.7%
리 24
 
7.7%
상 24
 
7.7%
군 24
 
7.7%
면 21
 
6.8%
천 7
 
2.3%
전 6
 
1.9%
Other values (39) 79
25.4%

토지면적(㎡)
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9104.4583
Minimum2420
Maximum21384
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T04:26:18.917562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2420
5-th percentile4191.6
Q16160.75
median9166
Q310494.75
95-th percentile15699.6
Maximum21384
Range18964
Interquartile range (IQR)4334

Descriptive statistics

Standard deviation4160.5383
Coefficient of variation (CV)0.45697812
Kurtosis2.2368352
Mean9104.4583
Median Absolute Deviation (MAD)2065
Skewness1.1226295
Sum218507
Variance17310079
MonotonicityNot monotonic
2023-12-13T04:26:19.107030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
15747 1
 
4.2%
10619 1
 
4.2%
11518 1
 
4.2%
15431 1
 
4.2%
6211 1
 
4.2%
8817 1
 
4.2%
8926 1
 
4.2%
5119 1
 
4.2%
9930 1
 
4.2%
4433 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
2420 1
4.2%
4149 1
4.2%
4433 1
4.2%
5119 1
4.2%
5205 1
4.2%
6010 1
4.2%
6211 1
4.2%
6680 1
4.2%
7388 1
4.2%
8817 1
4.2%
ValueCountFrequency (%)
21384 1
4.2%
15747 1
4.2%
15431 1
4.2%
11518 1
4.2%
10619 1
4.2%
10581 1
4.2%
10466 1
4.2%
10004 1
4.2%
9930 1
4.2%
9649 1
4.2%

건물면적(㎡)
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1090.805
Minimum217.7
Maximum1893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T04:26:19.267980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum217.7
5-th percentile472.0185
Q1854.2475
median1040.615
Q31449.875
95-th percentile1706.679
Maximum1893
Range1675.3
Interquartile range (IQR)595.6275

Descriptive statistics

Standard deviation425.39515
Coefficient of variation (CV)0.38998276
Kurtosis-0.48219543
Mean1090.805
Median Absolute Deviation (MAD)324.89
Skewness-0.024953901
Sum26179.32
Variance180961.03
MonotonicityNot monotonic
2023-12-13T04:26:19.414541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1893.0 1
 
4.2%
710.0 1
 
4.2%
1658.96 1
 
4.2%
1501.49 1
 
4.2%
1432.67 1
 
4.2%
1000.01 1
 
4.2%
1375.73 1
 
4.2%
878.82 1
 
4.2%
1055.25 1
 
4.2%
470.61 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
217.7 1
4.2%
470.61 1
4.2%
480.0 1
4.2%
710.0 1
4.2%
721.45 1
4.2%
811.55 1
4.2%
868.48 1
4.2%
878.82 1
4.2%
927.1 1
4.2%
962.42 1
4.2%
ValueCountFrequency (%)
1893.0 1
4.2%
1715.1 1
4.2%
1658.96 1
4.2%
1534.31 1
4.2%
1522.6 1
4.2%
1501.49 1
4.2%
1432.67 1
4.2%
1375.73 1
4.2%
1248.93 1
4.2%
1095.0 1
4.2%

관리현황
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
유상대부
8 
수몰
3 
교육시설
3 
농업생산
3 
문화예술
3 
Other values (3)
4 

Length

Max length4
Median length4
Mean length3.6666667
Min length2

Unique

Unique2 ?
Unique (%)8.3%

Sample

1st row유상대부
2nd row유상대부
3rd row유상대부
4th row유상대부
5th row유상대부

Common Values

ValueCountFrequency (%)
유상대부 8
33.3%
수몰 3
 
12.5%
교육시설 3
 
12.5%
농업생산 3
 
12.5%
문화예술 3
 
12.5%
자체활용 2
 
8.3%
매각 1
 
4.2%
체험시설 1
 
4.2%

Length

2023-12-13T04:26:19.551146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:26:19.685220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유상대부 8
33.3%
수몰 3
 
12.5%
교육시설 3
 
12.5%
농업생산 3
 
12.5%
문화예술 3
 
12.5%
자체활용 2
 
8.3%
매각 1
 
4.2%
체험시설 1
 
4.2%

활용/사용 현황
Text

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T04:26:19.899365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11.5
Mean length5.7916667
Min length1

Characters and Unicode

Total characters139
Distinct characters63
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)41.7%

Sample

1st row소득증대
2nd row문화예술(작업실)
3rd row문화예술(작업실)
4th row문화예술(작업실)
5th row사회복지(청소년복지)
ValueCountFrequency (%)
7
23.3%
문화예술(작업실 4
13.3%
운문댐 3
10.0%
청도군 3
10.0%
활용계획 1
 
3.3%
감물염색전시판매장 1
 
3.3%
농촌체험관광센터 1
 
3.3%
지방자치단체 1
 
3.3%
수립중 1
 
3.3%
도서관 1
 
3.3%
Other values (7) 7
23.3%
2023-12-13T04:26:20.274937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
문 8
 
5.8%
. 7
 
5.0%
( 6
 
4.3%
) 6
 
4.3%
6
 
4.3%
화 5
 
3.6%
예 5
 
3.6%
술 5
 
3.6%
업 5
 
3.6%
사 4
 
2.9%
Other values (53) 82
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114
82.0%
Other Punctuation 7
 
5.0%
Open Punctuation 6
 
4.3%
Close Punctuation 6
 
4.3%
Space Separator 6
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
문 8
 
7.0%
화 5
 
4.4%
예 5
 
4.4%
술 5
 
4.4%
업 5
 
4.4%
사 4
 
3.5%
작 4
 
3.5%
실 4
 
3.5%
도 4
 
3.5%
청 4
 
3.5%
Other values (49) 66
57.9%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114
82.0%
Common 25
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
문 8
 
7.0%
화 5
 
4.4%
예 5
 
4.4%
술 5
 
4.4%
업 5
 
4.4%
사 4
 
3.5%
작 4
 
3.5%
실 4
 
3.5%
도 4
 
3.5%
청 4
 
3.5%
Other values (49) 66
57.9%
Common
ValueCountFrequency (%)
. 7
28.0%
( 6
24.0%
) 6
24.0%
6
24.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114
82.0%
ASCII 25
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
문 8
 
7.0%
화 5
 
4.4%
예 5
 
4.4%
술 5
 
4.4%
업 5
 
4.4%
사 4
 
3.5%
작 4
 
3.5%
실 4
 
3.5%
도 4
 
3.5%
청 4
 
3.5%
Other values (49) 66
57.9%
ASCII
ValueCountFrequency (%)
. 7
28.0%
( 6
24.0%
) 6
24.0%
6
24.0%

Interactions

2023-12-13T04:26:16.178182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:15.440399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:15.765637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:16.286026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:15.522166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:15.885028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:16.392562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:15.651083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:26:16.072847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:26:20.396551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호구분폐지학교명폐교연도소재지토지면적(㎡)건물면적(㎡)관리현황활용/사용 현황
번호1.0000.7831.0000.8811.0000.3190.4640.8110.522
구분0.7831.0001.0000.0001.0000.4890.0000.9021.000
폐지학교명1.0001.0001.0001.0001.0001.0001.0001.0001.000
폐교연도0.8810.0001.0001.0001.0000.8570.8630.7230.000
소재지1.0001.0001.0001.0001.0001.0001.0001.0001.000
토지면적(㎡)0.3190.4891.0000.8571.0001.0000.5980.7190.832
건물면적(㎡)0.4640.0001.0000.8631.0000.5981.0000.0000.775
관리현황0.8110.9021.0000.7231.0000.7190.0001.0000.926
활용/사용 현황0.5221.0001.0000.0001.0000.8320.7750.9261.000
2023-12-13T04:26:20.519692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분관리현황
구분1.0000.771
관리현황0.7711.000
2023-12-13T04:26:20.642106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호토지면적(㎡)건물면적(㎡)구분관리현황
번호1.000-0.128-0.0160.5340.514
토지면적(㎡)-0.1281.0000.4200.2430.321
건물면적(㎡)-0.0160.4201.0000.0000.000
구분0.5340.2430.0001.0000.771
관리현황0.5140.3210.0000.7711.000

Missing values

2023-12-13T04:26:16.539507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:26:16.736501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

번호구분폐지학교명폐교연도소재지토지면적(㎡)건물면적(㎡)관리현황활용/사용 현황
01활용중인 폐교매전초등학교2012-03-01경상북도 청도군 매전면 온막리 42-4157471893.0유상대부소득증대
12활용중인 폐교풍각초서부분교2000-03-01경상북도 청도군 풍각면 안산리 58510004962.42유상대부문화예술(작업실)
23활용중인 폐교동곡초김전분교1999-09-01경상북도 청도군 금천면 김전리 5210581868.48유상대부문화예술(작업실)
34활용중인 폐교대산초등학교1999-03-01경상북도 청도군 각남면 옥산리 1594881025.98유상대부문화예술(작업실)
45활용중인 폐교청도동부초등학교1995-03-01경상북도 청도군 청도읍 원리 41289871522.6유상대부사회복지(청소년복지)
56활용중인 폐교유등초등학교1994-03-01경상북도 청도군 화양읍 유등리 187660101072.16유상대부문화예술(국악)
67활용중인 폐교풍각남부초등학교1994-03-01경상북도 청도군 풍각면 차산리 184-14149721.45유상대부문화예술(작업실)
78활용중인 폐교금천초문명분교2018-03-01경상북도 청도군 운문면 신원리 230-193451248.93유상대부공익사업 현장사무소
89활용중인 폐교방지초등학교2015-03-01경상북도 청도군 금천면 방지리 120366801534.31자체활용도서관 서고
910미활용 폐교동곡초등학교2015-03-01경상북도 청도군 금천면 동곡리 90596491715.1자체활용활용계획 수립중
번호구분폐지학교명폐교연도소재지토지면적(㎡)건물면적(㎡)관리현황활용/사용 현황
1415매각된 폐교대전초1993-03-01경상북도 청도군 이서면 대전리 5397388927.1농업생산.
1516매각된 폐교금천초임호분교1995-03-01경상북도 청도군 금천면 임당리 1026-15205811.55농업생산.
1617매각된 폐교동곡초소천분교1997-03-01경상북도 청도군 금천면 소천리 13444433470.61농업생산.
1718매각된 폐교방지초봉하분교1999-08-31경상북도 청도군 운문면 봉하리 78799301055.25교육시설.
1819매각된 폐교풍각초성곡분교1995-03-01경상북도 청도군 풍각면 성곡리 4975119878.82수몰운문댐
1920매각된 폐교각북초1998-03-01경상북도 청도군 각북면 남산리 118-289261375.73문화예술.
2021매각된 폐교유천초대현분교2000-03-01경상북도 청도군 청도읍 평양리 700-388171000.01교육시설.
2122매각된 폐교중남초1999-08-31경상북도 청도군 매전면 지전리 10162111432.67체험시설청도군 농촌체험관광센터
2223매각된 폐교관하초2007-03-01경상북도 청도군 매전면 관하리 1226-1154311501.49문화예술청도군 감물염색전시판매장
2324매각된 폐교칠곡초2008-03-01경상북도 청도군 이서면 양원리 129-5115181658.96문화예술청도군 역사박물관