Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells10144
Missing cells (%)6.3%
Duplicate rows350
Duplicate rows (%)3.5%
Total size in memory1.4 MiB
Average record size in memory142.0 B

Variable types

Numeric6
Categorical7
Text2
Boolean1

Alerts

Dataset has 350 (3.5%) duplicate rowsDuplicates
시군명 is highly overall correlated with 지역교육청명 and 1 other fieldsHigh correlation
지역명 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
제외여부 is highly overall correlated with 교사대지및기타면적(㎡) and 7 other fieldsHigh correlation
공동사용여부 is highly overall correlated with 기준년도 and 1 other fieldsHigh correlation
기준년도 is highly overall correlated with 공동사용여부High correlation
교사대지및기타면적(㎡) is highly overall correlated with 소계면적(㎡) and 2 other fieldsHigh correlation
체육장면적(㎡) is highly overall correlated with 제외여부High correlation
소계면적(㎡) is highly overall correlated with 교사대지및기타면적(㎡) and 2 other fieldsHigh correlation
부속토지면적(㎡) is highly overall correlated with 제외여부High correlation
합계면적(㎡) is highly overall correlated with 교사대지및기타면적(㎡) and 2 other fieldsHigh correlation
지역교육청명 is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
학교급명 is highly overall correlated with 제외여부High correlation
설립구분명 is highly overall correlated with 지역교육청명High correlation
설립유형명 is highly overall correlated with 제외여부High correlation
학교급명 is highly imbalanced (57.1%)Imbalance
설립구분명 is highly imbalanced (68.0%)Imbalance
제외여부 is highly imbalanced (97.1%)Imbalance
설립유형명 is highly imbalanced (79.0%)Imbalance
제외사유 has 9970 (99.7%) missing valuesMissing
교사대지및기타면적(㎡) is highly skewed (γ1 = 99.04926803)Skewed
체육장면적(㎡) is highly skewed (γ1 = 26.40712101)Skewed
소계면적(㎡) is highly skewed (γ1 = 98.7115061)Skewed
합계면적(㎡) is highly skewed (γ1 = 87.34089368)Skewed
교사대지및기타면적(㎡) has 211 (2.1%) zerosZeros
체육장면적(㎡) has 371 (3.7%) zerosZeros
소계면적(㎡) has 219 (2.2%) zerosZeros
부속토지면적(㎡) has 7790 (77.9%) zerosZeros
합계면적(㎡) has 216 (2.2%) zerosZeros

Reproduction

Analysis started2023-12-10 23:01:05.692929
Analysis finished2023-12-10 23:01:12.364173
Duration6.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.3049
Minimum2015
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:01:12.416955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016
median2017
Q32019
95-th percentile2020
Maximum2020
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6025582
Coefficient of variation (CV)0.00079440555
Kurtosis-1.1680388
Mean2017.3049
Median Absolute Deviation (MAD)1
Skewness0.064471465
Sum20173049
Variance2.5681928
MonotonicityNot monotonic
2023-12-11T08:01:12.529225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2019 1843
18.4%
2018 1823
18.2%
2017 1821
18.2%
2016 1801
18.0%
2015 1759
17.6%
2020 953
9.5%
ValueCountFrequency (%)
2015 1759
17.6%
2016 1801
18.0%
2017 1821
18.2%
2018 1823
18.2%
2019 1843
18.4%
2020 953
9.5%
ValueCountFrequency (%)
2020 953
9.5%
2019 1843
18.4%
2018 1823
18.2%
2017 1821
18.2%
2016 1801
18.0%
2015 1759
17.6%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
850 
용인시
742 
고양시
686 
화성시
 
641
성남시
 
628
Other values (26)
6453 

Length

Max length4
Median length3
Mean length3.0895
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row파주시
2nd row용인시
3rd row고양시
4th row안양시
5th row수원시

Common Values

ValueCountFrequency (%)
수원시 850
 
8.5%
용인시 742
 
7.4%
고양시 686
 
6.9%
화성시 641
 
6.4%
성남시 628
 
6.3%
부천시 537
 
5.4%
남양주시 486
 
4.9%
평택시 456
 
4.6%
안산시 449
 
4.5%
파주시 420
 
4.2%
Other values (21) 4105
41.0%

Length

2023-12-11T08:01:12.644878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 850
 
8.5%
용인시 742
 
7.4%
고양시 686
 
6.9%
화성시 641
 
6.4%
성남시 628
 
6.3%
부천시 537
 
5.4%
남양주시 486
 
4.9%
평택시 456
 
4.6%
안산시 449
 
4.5%
파주시 420
 
4.2%
Other values (21) 4105
41.0%

지역교육청명
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도교육청
2064 
경기도화성오산교육지원청
674 
경기도수원교육지원청
649 
경기도용인교육지원청
609 
경기도고양교육지원청
 
535
Other values (22)
5469 

Length

Max length13
Median length10
Mean length9.7115
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도파주교육지원청
2nd row경기도교육청
3rd row경기도고양교육지원청
4th row경기도교육청
5th row경기도수원교육지원청

Common Values

ValueCountFrequency (%)
경기도교육청 2064
20.6%
경기도화성오산교육지원청 674
 
6.7%
경기도수원교육지원청 649
 
6.5%
경기도용인교육지원청 609
 
6.1%
경기도고양교육지원청 535
 
5.3%
경기도구리남양주교육지원청 494
 
4.9%
경기도성남교육지원청 477
 
4.8%
경기도부천교육지원청 417
 
4.2%
경기도평택교육지원청 354
 
3.5%
경기도안산교육지원청 341
 
3.4%
Other values (17) 3386
33.9%

Length

2023-12-11T08:01:12.750335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도교육청 2064
20.6%
경기도화성오산교육지원청 674
 
6.7%
경기도수원교육지원청 649
 
6.5%
경기도용인교육지원청 609
 
6.1%
경기도고양교육지원청 535
 
5.3%
경기도구리남양주교육지원청 494
 
4.9%
경기도성남교육지원청 477
 
4.8%
경기도부천교육지원청 417
 
4.2%
경기도평택교육지원청 354
 
3.5%
경기도안산교육지원청 341
 
3.4%
Other values (17) 3386
33.9%

지역명
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도 화성시
 
641
경기도 부천시
 
537
경기도 남양주시
 
486
경기도 평택시
 
456
경기도 파주시
 
420
Other values (37)
7460 

Length

Max length12
Median length7
Mean length8.6178
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 파주시
2nd row경기도 용인시 기흥구
3rd row경기도 고양시 덕양구
4th row경기도 안양시 만안구
5th row경기도 수원시 영통구

Common Values

ValueCountFrequency (%)
경기도 화성시 641
 
6.4%
경기도 부천시 537
 
5.4%
경기도 남양주시 486
 
4.9%
경기도 평택시 456
 
4.6%
경기도 파주시 420
 
4.2%
경기도 성남시 분당구 352
 
3.5%
경기도 김포시 325
 
3.2%
경기도 의정부시 307
 
3.1%
경기도 시흥시 293
 
2.9%
경기도 용인시 기흥구 290
 
2.9%
Other values (32) 5893
58.9%

Length

2023-12-11T08:01:12.854999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 10000
42.2%
수원시 850
 
3.6%
용인시 742
 
3.1%
고양시 686
 
2.9%
화성시 641
 
2.7%
성남시 628
 
2.6%
부천시 537
 
2.3%
남양주시 486
 
2.0%
평택시 456
 
1.9%
안산시 449
 
1.9%
Other values (39) 8246
34.8%

학교명
Text

Distinct2483
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:01:13.082877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length6
Mean length6.2768
Min length4

Characters and Unicode

Total characters62768
Distinct characters346
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)1.5%

Sample

1st row신산초등학교
2nd row보라고등학교
3rd row서정초등학교
4th row성문고등학교
5th row광교중학교
ValueCountFrequency (%)
석천초등학교 10
 
0.1%
상원초등학교 10
 
0.1%
오산초등학교 10
 
0.1%
초당초등학교 10
 
0.1%
광남고등학교 9
 
0.1%
원동초등학교 9
 
0.1%
삼성초등학교 9
 
0.1%
신길초등학교 9
 
0.1%
내유초등학교 9
 
0.1%
과천고등학교 9
 
0.1%
Other values (2474) 9911
99.1%
2023-12-11T08:01:13.507164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 10239
16.3%
학 10148
16.2%
등 7213
 
11.5%
초 5325
 
8.5%
중 2867
 
4.6%
고 2135
 
3.4%
동 629
 
1.0%
양 620
 
1.0%
천 613
 
1.0%
원 612
 
1.0%
Other values (336) 22367
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62622
99.8%
Lowercase Letter 68
 
0.1%
Close Punctuation 29
 
< 0.1%
Open Punctuation 29
 
< 0.1%
Uppercase Letter 14
 
< 0.1%
Space Separator 5
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 10239
16.4%
학 10148
16.2%
등 7213
 
11.5%
초 5325
 
8.5%
중 2867
 
4.6%
고 2135
 
3.4%
동 629
 
1.0%
양 620
 
1.0%
천 613
 
1.0%
원 612
 
1.0%
Other values (320) 22221
35.5%
Lowercase Letter
ValueCountFrequency (%)
s 20
29.4%
i 10
14.7%
n 10
14.7%
e 8
 
11.8%
g 5
 
7.4%
l 5
 
7.4%
u 5
 
7.4%
h 5
 
7.4%
Uppercase Letter
ValueCountFrequency (%)
E 5
35.7%
B 5
35.7%
T 2
 
14.3%
I 2
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62622
99.8%
Latin 82
 
0.1%
Common 64
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 10239
16.4%
학 10148
16.2%
등 7213
 
11.5%
초 5325
 
8.5%
중 2867
 
4.6%
고 2135
 
3.4%
동 629
 
1.0%
양 620
 
1.0%
천 613
 
1.0%
원 612
 
1.0%
Other values (320) 22221
35.5%
Latin
ValueCountFrequency (%)
s 20
24.4%
i 10
12.2%
n 10
12.2%
e 8
 
9.8%
E 5
 
6.1%
g 5
 
6.1%
l 5
 
6.1%
B 5
 
6.1%
u 5
 
6.1%
h 5
 
6.1%
Other values (2) 4
 
4.9%
Common
ValueCountFrequency (%)
) 29
45.3%
( 29
45.3%
5
 
7.8%
1 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62622
99.8%
ASCII 146
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 10239
16.4%
학 10148
16.2%
등 7213
 
11.5%
초 5325
 
8.5%
중 2867
 
4.6%
고 2135
 
3.4%
동 629
 
1.0%
양 620
 
1.0%
천 613
 
1.0%
원 612
 
1.0%
Other values (320) 22221
35.5%
ASCII
ValueCountFrequency (%)
) 29
19.9%
( 29
19.9%
s 20
13.7%
i 10
 
6.8%
n 10
 
6.8%
e 8
 
5.5%
E 5
 
3.4%
g 5
 
3.4%
l 5
 
3.4%
5
 
3.4%
Other values (6) 20
13.7%

학교급명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6362 
초등학교
1923 
중학교
938 
고등학교
684 
특수학교
 
59
Other values (7)
 
34

Length

Max length7
Median length4
Mean length3.9105
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row초등학교
4th row고등학교
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6362
63.6%
초등학교 1923
 
19.2%
중학교 938
 
9.4%
고등학교 684
 
6.8%
특수학교 59
 
0.6%
방통고 8
 
0.1%
각종학교(중) 7
 
0.1%
방통중 6
 
0.1%
각종학교(고) 5
 
0.1%
각종학교(초) 5
 
0.1%
Other values (2) 3
 
< 0.1%

Length

2023-12-11T08:01:13.639732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6362
63.6%
초등학교 1923
 
19.2%
중학교 938
 
9.4%
고등학교 684
 
6.8%
특수학교 59
 
0.6%
방통고 8
 
0.1%
각종학교(중 7
 
0.1%
방통중 6
 
0.1%
각종학교(고 5
 
< 0.1%
각종학교(초 5
 
< 0.1%
Other values (2) 3
 
< 0.1%

설립구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공립
8913 
사립
1073 
국립
 
14

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공립
2nd row공립
3rd row공립
4th row사립
5th row공립

Common Values

ValueCountFrequency (%)
공립 8913
89.1%
사립 1073
 
10.7%
국립 14
 
0.1%

Length

2023-12-11T08:01:13.752005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:01:13.838006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 8913
89.1%
사립 1073
 
10.7%
국립 14
 
0.1%

제외여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9970 
True
 
30
ValueCountFrequency (%)
False 9970
99.7%
True 30
 
0.3%
2023-12-11T08:01:14.166882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

제외사유
Text

MISSING 

Distinct16
Distinct (%)53.3%
Missing9970
Missing (%)99.7%
Memory size156.2 KiB
2023-12-11T08:01:14.351821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length19
Mean length16.033333
Min length3

Characters and Unicode

Total characters481
Distinct characters73
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

Unique8 ?
Unique (%)26.7%

Sample

1st row본교인 삼평중학교에 따름
2nd row수원여자고등학교 부설교
3rd row하늘꿈학교(고) 해당항목 열람 바람
4th row서현고등학교(본교) 정보공시로 대체함.
5th row본교통합공시
ValueCountFrequency (%)
본교와 5
 
5.3%
본교통합공시 4
 
4.2%
삼평중학교에 4
 
4.2%
따름 4
 
4.2%
사용하므로 4
 
4.2%
부설교 4
 
4.2%
하늘꿈학교(고 4
 
4.2%
열람 3
 
3.2%
본교 3
 
3.2%
본교인 3
 
3.2%
Other values (33) 57
60.0%
2023-12-11T08:01:14.802778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
 
13.7%
교 46
 
9.6%
학 22
 
4.6%
본 20
 
4.2%
고 15
 
3.1%
공 14
 
2.9%
시 13
 
2.7%
등 10
 
2.1%
로 10
 
2.1%
하 10
 
2.1%
Other values (63) 255
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 394
81.9%
Space Separator 66
 
13.7%
Close Punctuation 7
 
1.5%
Other Punctuation 7
 
1.5%
Open Punctuation 7
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 46
 
11.7%
학 22
 
5.6%
본 20
 
5.1%
고 15
 
3.8%
공 14
 
3.6%
시 13
 
3.3%
등 10
 
2.5%
로 10
 
2.5%
하 10
 
2.5%
사 9
 
2.3%
Other values (59) 225
57.1%
Space Separator
ValueCountFrequency (%)
66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 394
81.9%
Common 87
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 46
 
11.7%
학 22
 
5.6%
본 20
 
5.1%
고 15
 
3.8%
공 14
 
3.6%
시 13
 
3.3%
등 10
 
2.5%
로 10
 
2.5%
하 10
 
2.5%
사 9
 
2.3%
Other values (59) 225
57.1%
Common
ValueCountFrequency (%)
66
75.9%
) 7
 
8.0%
. 7
 
8.0%
( 7
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 394
81.9%
ASCII 87
 
18.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
75.9%
) 7
 
8.0%
. 7
 
8.0%
( 7
 
8.0%
Hangul
ValueCountFrequency (%)
교 46
 
11.7%
학 22
 
5.6%
본 20
 
5.1%
고 15
 
3.8%
공 14
 
3.6%
시 13
 
3.3%
등 10
 
2.5%
로 10
 
2.5%
하 10
 
2.5%
사 9
 
2.3%
Other values (59) 225
57.1%

교사대지및기타면적(㎡)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2612
Distinct (%)26.2%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean9353.1569
Minimum0
Maximum8801919
Zeros211
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:01:14.992688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1519
Q15022
median7983
Q310208
95-th percentile17996
Maximum8801919
Range8801919
Interquartile range (IQR)5186

Descriptive statistics

Standard deviation88327.351
Coefficient of variation (CV)9.443587
Kurtosis9860.7113
Mean9353.1569
Median Absolute Deviation (MAD)2543
Skewness99.049268
Sum93176149
Variance7.8017209 × 109
MonotonicityNot monotonic
2023-12-11T08:01:15.176401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 211
 
2.1%
4000 23
 
0.2%
6979 16
 
0.2%
14435 15
 
0.1%
8933 15
 
0.1%
12000 14
 
0.1%
7602 14
 
0.1%
7736 14
 
0.1%
5487 14
 
0.1%
10277 14
 
0.1%
Other values (2602) 9612
96.1%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0 211
2.1%
272 4
 
< 0.1%
357 5
 
0.1%
364 1
 
< 0.1%
455 3
 
< 0.1%
599 1
 
< 0.1%
631 1
 
< 0.1%
714 4
 
< 0.1%
715 4
 
< 0.1%
777 4
 
< 0.1%
ValueCountFrequency (%)
8801919 1
 
< 0.1%
92166 3
< 0.1%
79336 4
< 0.1%
73855 1
 
< 0.1%
67617 6
0.1%
66114 4
< 0.1%
59365 3
< 0.1%
55247 3
< 0.1%
51868 4
< 0.1%
51617 3
< 0.1%

체육장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2266
Distinct (%)22.7%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean6184.8172
Minimum0
Maximum370981
Zeros371
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:01:15.337804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1275
Q13566
median5294.5
Q37622
95-th percentile13124.75
Maximum370981
Range370981
Interquartile range (IQR)4056

Descriptive statistics

Standard deviation6008.7036
Coefficient of variation (CV)0.97152485
Kurtosis1424.5915
Mean6184.8172
Median Absolute Deviation (MAD)1931
Skewness26.407121
Sum61613149
Variance36104519
MonotonicityNot monotonic
2023-12-11T08:01:15.527520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 371
 
3.7%
3000 40
 
0.4%
2800 34
 
0.3%
5500 32
 
0.3%
4800 28
 
0.3%
7500 27
 
0.3%
5000 26
 
0.3%
8000 23
 
0.2%
3150 23
 
0.2%
5300 21
 
0.2%
Other values (2256) 9337
93.4%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0 371
3.7%
42 2
 
< 0.1%
54 3
 
< 0.1%
100 2
 
< 0.1%
271 2
 
< 0.1%
330 2
 
< 0.1%
340 2
 
< 0.1%
360 2
 
< 0.1%
363 1
 
< 0.1%
375 2
 
< 0.1%
ValueCountFrequency (%)
370981 1
 
< 0.1%
120027 4
< 0.1%
93590 2
 
< 0.1%
35120 3
 
< 0.1%
34905 8
0.1%
29901 3
 
< 0.1%
29886 5
0.1%
29694 2
 
< 0.1%
29592 2
 
< 0.1%
29319 2
 
< 0.1%

소계면적(㎡)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2373
Distinct (%)23.8%
Missing30
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean15525.506
Minimum0
Maximum9172900
Zeros219
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:01:15.695266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6239
Q111501
median13023
Q315684
95-th percentile26946
Maximum9172900
Range9172900
Interquartile range (IQR)4183

Descriptive statistics

Standard deviation92072.713
Coefficient of variation (CV)5.9304161
Kurtosis9818.3231
Mean15525.506
Median Absolute Deviation (MAD)1931
Skewness98.711506
Sum1.547893 × 108
Variance8.4773845 × 109
MonotonicityNot monotonic
2023-12-11T08:01:15.831024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 219
 
2.2%
11500 109
 
1.1%
12000 82
 
0.8%
11000 77
 
0.8%
13000 37
 
0.4%
13500 32
 
0.3%
12500 30
 
0.3%
14000 29
 
0.3%
15000 20
 
0.2%
11501 19
 
0.2%
Other values (2363) 9316
93.2%
(Missing) 30
 
0.3%
ValueCountFrequency (%)
0 219
2.2%
357 5
 
0.1%
364 1
 
< 0.1%
455 3
 
< 0.1%
599 1
 
< 0.1%
1073 2
 
< 0.1%
1111 4
 
< 0.1%
1171 1
 
< 0.1%
1282 2
 
< 0.1%
1527 4
 
< 0.1%
ValueCountFrequency (%)
9172900 1
 
< 0.1%
135664 4
< 0.1%
106160 2
 
< 0.1%
101414 3
< 0.1%
89346 4
< 0.1%
80008 6
0.1%
79855 1
 
< 0.1%
75864 4
< 0.1%
73867 4
< 0.1%
73518 3
< 0.1%

부속토지면적(㎡)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct639
Distinct (%)6.4%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean3906.4515
Minimum0
Maximum913677
Zeros7790
Zeros (%)77.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:01:15.978854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile16482
Maximum913677
Range913677
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26238.576
Coefficient of variation (CV)6.716729
Kurtosis571.03636
Mean3906.4515
Median Absolute Deviation (MAD)0
Skewness19.924842
Sum38916070
Variance6.8846287 × 108
MonotonicityNot monotonic
2023-12-11T08:01:16.139759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7790
77.9%
272 15
 
0.1%
324 14
 
0.1%
337 10
 
0.1%
1186 10
 
0.1%
361 9
 
0.1%
364 9
 
0.1%
691 9
 
0.1%
10390 9
 
0.1%
47 9
 
0.1%
Other values (629) 2078
 
20.8%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0 7790
77.9%
11 6
 
0.1%
12 6
 
0.1%
16 1
 
< 0.1%
22 5
 
0.1%
29 4
 
< 0.1%
32 1
 
< 0.1%
33 2
 
< 0.1%
35 3
 
< 0.1%
38 6
 
0.1%
ValueCountFrequency (%)
913677 1
 
< 0.1%
893498 2
 
< 0.1%
869936 1
 
< 0.1%
413620 1
 
< 0.1%
413275 1
 
< 0.1%
305241 2
 
< 0.1%
300206 6
0.1%
297521 4
< 0.1%
255733 4
< 0.1%
232949 2
 
< 0.1%

합계면적(㎡)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2418
Distinct (%)24.3%
Missing30
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean19428.823
Minimum0
Maximum9172900
Zeros216
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:01:16.263576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7454
Q111816
median13411
Q317026.5
95-th percentile40274
Maximum9172900
Range9172900
Interquartile range (IQR)5210.5

Descriptive statistics

Standard deviation96036.772
Coefficient of variation (CV)4.9430051
Kurtosis8284.1998
Mean19428.823
Median Absolute Deviation (MAD)2037.5
Skewness87.340894
Sum1.9370537 × 108
Variance9.2230616 × 109
MonotonicityNot monotonic
2023-12-11T08:01:16.404193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 216
 
2.2%
11500 109
 
1.1%
12000 80
 
0.8%
11000 73
 
0.7%
13000 37
 
0.4%
14000 36
 
0.4%
13500 28
 
0.3%
12500 25
 
0.2%
15000 20
 
0.2%
11501 19
 
0.2%
Other values (2408) 9327
93.3%
(Missing) 30
 
0.3%
ValueCountFrequency (%)
0 216
2.2%
357 5
 
0.1%
364 1
 
< 0.1%
455 3
 
< 0.1%
599 1
 
< 0.1%
1073 2
 
< 0.1%
1111 4
 
< 0.1%
1171 1
 
< 0.1%
1360 2
 
< 0.1%
1527 4
 
< 0.1%
ValueCountFrequency (%)
9172900 1
 
< 0.1%
972584 1
 
< 0.1%
952405 2
 
< 0.1%
949791 1
 
< 0.1%
436196 1
 
< 0.1%
435851 1
 
< 0.1%
332681 4
< 0.1%
322074 2
 
< 0.1%
308336 6
0.1%
274975 4
< 0.1%

공동사용여부
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
5327 
Y
3466 
x
1109 
<NA>
 
98

Length

Max length4
Median length1
Mean length1.0294
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowN
4th rowY
5th rowN

Common Values

ValueCountFrequency (%)
N 5327
53.3%
Y 3466
34.7%
x 1109
 
11.1%
<NA> 98
 
1.0%

Length

2023-12-11T08:01:16.525788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:01:16.623290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 5327
53.3%
y 3466
34.7%
x 1109
 
11.1%
na 98
 
1.0%

설립유형명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단설
9072 
병설
 
866
부설
 
23
부속
 
20
<NA>
 
19

Length

Max length4
Median length2
Mean length2.0038
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단설 9072
90.7%
병설 866
 
8.7%
부설 23
 
0.2%
부속 20
 
0.2%
<NA> 19
 
0.2%

Length

2023-12-11T08:01:16.736661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:01:16.847000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단설 9072
90.7%
병설 866
 
8.7%
부설 23
 
0.2%
부속 20
 
0.2%
na 19
 
0.2%

Interactions

2023-12-11T08:01:11.143958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:07.753855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:08.456504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.176097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.835894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.534039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:11.233618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:07.838205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:08.588675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.317957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.937127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.639991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:11.331021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:07.988061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:08.706835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.428234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.083540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.728738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:11.448538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:08.104990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:08.834960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.542349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.230705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.852597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:11.551013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:08.204014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:08.953223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.648802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.342236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.960347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:11.641621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:08.322985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.068293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:09.741145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:10.435100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:01:11.060705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:01:16.935779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명지역교육청명지역명학교급명설립구분명제외여부제외사유교사대지및기타면적(㎡)체육장면적(㎡)소계면적(㎡)부속토지면적(㎡)합계면적(㎡)공동사용여부설립유형명
기준년도1.0000.0000.0000.0000.0180.0000.0000.7220.0000.0080.0000.0000.0000.5980.035
시군명0.0001.0000.9921.0000.2040.2850.1161.0000.0000.1820.0000.2620.1770.2530.222
지역교육청명0.0000.9921.0000.9940.7070.9380.0931.0000.0000.0000.0000.2110.0000.2840.298
지역명0.0001.0000.9941.0000.2510.4150.2241.0000.0000.1960.0000.2780.1790.3170.281
학교급명0.0180.2040.7070.2511.0000.5470.8001.0000.0000.0000.0000.5400.0000.2280.638
설립구분명0.0000.2850.9380.4150.5471.0000.0001.0000.0000.0400.0000.1330.0000.3040.181
제외여부0.0000.1160.0930.2240.8000.0001.000NaNNaNNaNNaNNaNNaNNaN0.706
제외사유0.7221.0001.0001.0001.0001.000NaN1.000NaNNaNNaNNaNNaNNaN1.000
교사대지및기타면적(㎡)0.0000.0000.0000.0000.0000.000NaNNaN1.0001.0000.7070.0001.0000.0000.000
체육장면적(㎡)0.0080.1820.0000.1960.0000.040NaNNaN1.0001.0001.0000.0000.6760.0170.052
소계면적(㎡)0.0000.0000.0000.0000.0000.000NaNNaN0.7071.0001.0000.0001.0000.0000.000
부속토지면적(㎡)0.0000.2620.2110.2780.5400.133NaNNaN0.0000.0000.0001.0000.9410.0440.010
합계면적(㎡)0.0000.1770.0000.1790.0000.000NaNNaN1.0000.6761.0000.9411.0000.0130.000
공동사용여부0.5980.2530.2840.3170.2280.304NaNNaN0.0000.0170.0000.0440.0131.0000.163
설립유형명0.0350.2220.2980.2810.6380.1810.7061.0000.0000.0520.0000.0100.0000.1631.000
2023-12-11T08:01:17.090064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립구분명지역교육청명시군명지역명학교급명제외여부설립유형명공동사용여부
설립구분명1.0000.7490.1490.2120.3810.0000.1720.103
지역교육청명0.7491.0000.8590.8600.3310.0790.1600.136
시군명0.1490.8591.0000.9990.0710.0990.1170.131
지역명0.2120.8600.9991.0000.0850.1780.1450.155
학교급명0.3810.3310.0710.0851.0000.7920.4440.218
제외여부0.0000.0790.0990.1780.7921.0000.5021.000
설립유형명0.1720.1600.1170.1450.4440.5021.0000.154
공동사용여부0.1030.1360.1310.1550.2181.0000.1541.000
2023-12-11T08:01:17.204295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도교사대지및기타면적(㎡)체육장면적(㎡)소계면적(㎡)부속토지면적(㎡)합계면적(㎡)시군명지역교육청명지역명학교급명설립구분명제외여부공동사용여부설립유형명
기준년도1.0000.033-0.049-0.002-0.023-0.0100.0000.0000.0000.0080.0000.0000.5690.030
교사대지및기타면적(㎡)0.0331.000-0.2120.667-0.0470.5300.0000.0000.0000.0000.0001.0000.0000.000
체육장면적(㎡)-0.049-0.2121.0000.4480.1880.4460.0950.0000.1000.0000.0371.0000.0160.021
소계면적(㎡)-0.0020.6670.4481.0000.0910.8600.0000.0000.0000.0000.0001.0000.0000.000
부속토지면적(㎡)-0.023-0.0470.1880.0911.0000.4340.1180.0940.1150.3130.0551.0000.0180.007
합계면적(㎡)-0.0100.5300.4460.8600.4341.0000.0890.0000.0830.0000.0001.0000.0040.000
시군명0.0000.0000.0950.0000.1180.0891.0000.8590.9990.0710.1490.0990.1310.117
지역교육청명0.0000.0000.0000.0000.0940.0000.8591.0000.8600.3310.7490.0790.1360.160
지역명0.0000.0000.1000.0000.1150.0830.9990.8601.0000.0850.2120.1780.1550.145
학교급명0.0080.0000.0000.0000.3130.0000.0710.3310.0851.0000.3810.7920.2180.444
설립구분명0.0000.0000.0370.0000.0550.0000.1490.7490.2120.3811.0000.0000.1030.172
제외여부0.0001.0001.0001.0001.0001.0000.0990.0790.1780.7920.0001.0001.0000.502
공동사용여부0.5690.0000.0160.0000.0180.0040.1310.1360.1550.2180.1031.0001.0000.154
설립유형명0.0300.0000.0210.0000.0070.0000.1170.1600.1450.4440.1720.5020.1541.000

Missing values

2023-12-11T08:01:11.809980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:01:12.044650image/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.
2023-12-11T08:01:12.228481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기준년도시군명지역교육청명지역명학교명학교급명설립구분명제외여부제외사유교사대지및기타면적(㎡)체육장면적(㎡)소계면적(㎡)부속토지면적(㎡)합계면적(㎡)공동사용여부설립유형명
114212018파주시경기도파주교육지원청경기도 파주시신산초등학교<NA>공립N<NA>12697188273152460832132Y단설
158132017용인시경기도교육청경기도 용인시 기흥구보라고등학교<NA>공립N<NA>10040424414284014284N단설
221872015고양시경기도고양교육지원청경기도 고양시 덕양구서정초등학교초등학교공립N<NA>8905309512000012000N단설
245962015안양시경기도교육청경기도 안양시 만안구성문고등학교고등학교사립N<NA>30148892539073039073Y단설
140942017수원시경기도수원교육지원청경기도 수원시 영통구광교중학교<NA>공립N<NA>10083434914432014432N단설
155142017오산시경기도화성오산교육지원청경기도 오산시금암초등학교<NA>공립N<NA>8724526513989013989N단설
110172018용인시경기도용인교육지원청경기도 용인시 기흥구용인백현초등학교초등학교공립N<NA>12483456917052017052N단설
204222016용인시경기도용인교육지원청경기도 용인시 처인구장평초등학교초등학교공립N<NA>94057817172222308540307<NA>병설
250452015오산시경기도화성오산교육지원청경기도 오산시오산대원초등학교<NA>공립N<NA>10495250513000013000N병설
67132019평택시경기도평택교육지원청경기도 평택시갈곶초등학교<NA>공립N<NA>17821023212014105913073Y단설
기준년도시군명지역교육청명지역명학교명학교급명설립구분명제외여부제외사유교사대지및기타면적(㎡)체육장면적(㎡)소계면적(㎡)부속토지면적(㎡)합계면적(㎡)공동사용여부설립유형명
41992019성남시경기도성남교육지원청경기도 성남시 분당구초림초등학교<NA>공립N<NA>5606589411500011500x단설
220342015고양시경기도고양교육지원청경기도 고양시 덕양구덕양중학교<NA>공립N<NA>23735081745407454N단설
59342019용인시경기도용인교육지원청경기도 용인시 기흥구동막초등학교<NA>공립N<NA>9767272512492012492Y단설
42492019성남시경기도성남교육지원청경기도 성남시 분당구돌마초등학교<NA>공립N<NA>65211000752107521x단설
219282015가평군경기도가평교육지원청경기도 가평군율길초등학교초등학교공립N<NA>50494177922609226N단설
257492015이천시경기도이천교육지원청경기도 이천시도지초등학교<NA>공립N<NA>15191128212801012801N단설
38632019부천시경기도교육청경기도 부천시소명여자고등학교<NA>사립N<NA>10718536416082016082Y단설
11542020시흥시경기도시흥교육지원청경기도 시흥시시흥장현초등학교<NA>공립N<NA>8772549614268014268Y단설
212452016파주시경기도교육청경기도 파주시파주여자고등학교고등학교사립N<NA>39662313127097027097N단설
226262015군포시경기도군포의왕교육지원청경기도 군포시수리초등학교<NA>공립N<NA>4663636511028011028N단설

Duplicate rows

Most frequently occurring

기준년도시군명지역교육청명지역명학교명학교급명설립구분명제외여부제외사유교사대지및기타면적(㎡)체육장면적(㎡)소계면적(㎡)부속토지면적(㎡)합계면적(㎡)공동사용여부설립유형명# duplicates
02019가평군경기도가평교육지원청경기도 가평군가평북중학교<NA>공립N<NA>322249350415744541619Y단설2
12019가평군경기도가평교육지원청경기도 가평군대성초등학교<NA>공립N<NA>20004747674706747Y단설2
22019가평군경기도가평교육지원청경기도 가평군미원초등학교<NA>공립N<NA>10965281613781743821219Y병설2
32019가평군경기도가평교육지원청경기도 가평군청평중학교<NA>공립N<NA>62881113817426017426x단설2
42019고양시경기도고양교육지원청경기도 고양시 덕양구고양중학교<NA>공립N<NA>6523496011483011483x단설2
52019고양시경기도고양교육지원청경기도 고양시 덕양구고양초등학교<NA>공립N<NA>9789420413993966623659Y단설2
62019고양시경기도고양교육지원청경기도 고양시 덕양구능곡중학교<NA>공립N<NA>1236053501771055418264x단설2
72019고양시경기도고양교육지원청경기도 고양시 덕양구무원초등학교<NA>공립N<NA>5918508211000011000x단설2
82019고양시경기도고양교육지원청경기도 고양시 덕양구백양중학교<NA>공립N<NA>7587391211499011499x단설2
92019고양시경기도고양교육지원청경기도 고양시 덕양구서정초등학교<NA>공립N<NA>8916309512011012011Y단설2