Overview

Dataset statistics

Number of variables19
Number of observations10000
Missing cells33946
Missing cells (%)17.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory171.0 B

Variable types

Numeric9
Categorical5
Text2
Unsupported2
Boolean1

Dataset

Description학교 현황(학생수)(초,중,고,그외)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=8GRSB88F2QW4RJ3MG95I23516519&infSeq=2

Alerts

제외여부 has constant value ""Constant
시군명 is highly overall correlated with 지역교육청명 and 1 other fieldsHigh correlation
지역명 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
1학년수(명) is highly overall correlated with 2학년수(명) and 4 other fieldsHigh correlation
2학년수(명) is highly overall correlated with 1학년수(명) and 4 other fieldsHigh correlation
3학년수(명) is highly overall correlated with 1학년수(명) and 4 other fieldsHigh correlation
4학년수(명) is highly overall correlated with 1학년수(명) and 5 other fieldsHigh correlation
5학년수(명) is highly overall correlated with 1학년수(명) and 5 other fieldsHigh correlation
6학년수(명) is highly overall correlated with 1학년수(명) and 5 other fieldsHigh correlation
지역교육청명 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
주야간명 is highly overall correlated with 4학년수(명) and 2 other fieldsHigh correlation
설립구분명 is highly imbalanced (53.2%)Imbalance
학교급명 has 10000 (100.0%) missing valuesMissing
제외사유 has 10000 (100.0%) missing valuesMissing
4학년수(명) has 3885 (38.9%) missing valuesMissing
5학년수(명) has 4644 (46.4%) missing valuesMissing
6학년수(명) has 4644 (46.4%) missing valuesMissing
특수학급학생수(명) has 759 (7.6%) missing valuesMissing
학교급명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제외사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
3학년수(명) has 111 (1.1%) zerosZeros
4학년수(명) has 320 (3.2%) zerosZeros
특수학급학생수(명) has 2641 (26.4%) zerosZeros
순회학급학생수(명) has 9344 (93.4%) zerosZeros

Reproduction

Analysis started2023-12-10 21:01:21.890130
Analysis finished2023-12-10 21:01:35.629548
Duration13.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5401
Minimum2015
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:35.682506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016
median2018
Q32019
95-th percentile2020
Maximum2020
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.709703
Coefficient of variation (CV)0.00084741958
Kurtosis-1.2734952
Mean2017.5401
Median Absolute Deviation (MAD)1
Skewness-0.025269948
Sum20175401
Variance2.9230843
MonotonicityNot monotonic
2023-12-11T06:01:35.792727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2020 1734
17.3%
2019 1712
17.1%
2017 1672
16.7%
2016 1649
16.5%
2018 1630
16.3%
2015 1603
16.0%
ValueCountFrequency (%)
2015 1603
16.0%
2016 1649
16.5%
2017 1672
16.7%
2018 1630
16.3%
2019 1712
17.1%
2020 1734
17.3%
ValueCountFrequency (%)
2020 1734
17.3%
2019 1712
17.1%
2018 1630
16.3%
2017 1672
16.7%
2016 1649
16.5%
2015 1603
16.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
840 
용인시
762 
고양시
674 
성남시
652 
화성시
 
630
Other values (26)
6442 

Length

Max length4
Median length3
Mean length3.0899
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광명시
2nd row김포시
3rd row광명시
4th row파주시
5th row평택시

Common Values

ValueCountFrequency (%)
수원시 840
 
8.4%
용인시 762
 
7.6%
고양시 674
 
6.7%
성남시 652
 
6.5%
화성시 630
 
6.3%
부천시 518
 
5.2%
남양주시 495
 
5.0%
안산시 454
 
4.5%
파주시 426
 
4.3%
평택시 421
 
4.2%
Other values (21) 4128
41.3%

Length

2023-12-11T06:01:35.933747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 840
 
8.4%
용인시 762
 
7.6%
고양시 674
 
6.7%
성남시 652
 
6.5%
화성시 630
 
6.3%
부천시 518
 
5.2%
남양주시 495
 
5.0%
안산시 454
 
4.5%
파주시 426
 
4.3%
평택시 421
 
4.2%
Other values (21) 4128
41.3%

지역교육청명
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도교육청
2026 
경기도화성오산교육지원청
669 
경기도수원교육지원청
650 
경기도용인교육지원청
634 
경기도고양교육지원청
 
526
Other values (21)
5495 

Length

Max length13
Median length10
Mean length9.7414
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도교육청
2nd row경기도김포교육지원청
3rd row경기도광명교육지원청
4th row경기도파주교육지원청
5th row경기도평택교육지원청

Common Values

ValueCountFrequency (%)
경기도교육청 2026
20.3%
경기도화성오산교육지원청 669
 
6.7%
경기도수원교육지원청 650
 
6.5%
경기도용인교육지원청 634
 
6.3%
경기도고양교육지원청 526
 
5.3%
경기도구리남양주교육지원청 505
 
5.1%
경기도성남교육지원청 482
 
4.8%
경기도부천교육지원청 404
 
4.0%
경기도파주교육지원청 348
 
3.5%
경기도안산교육지원청 346
 
3.5%
Other values (16) 3410
34.1%

Length

2023-12-11T06:01:36.083233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도교육청 2026
20.3%
경기도화성오산교육지원청 669
 
6.7%
경기도수원교육지원청 650
 
6.5%
경기도용인교육지원청 634
 
6.3%
경기도고양교육지원청 526
 
5.3%
경기도구리남양주교육지원청 505
 
5.1%
경기도성남교육지원청 482
 
4.8%
경기도부천교육지원청 404
 
4.0%
경기도파주교육지원청 348
 
3.5%
경기도안산교육지원청 346
 
3.5%
Other values (16) 3410
34.1%

지역명
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도 화성시
 
630
경기도 부천시
 
518
경기도 남양주시
 
495
경기도 파주시
 
426
경기도 평택시
 
421
Other values (37)
7510 

Length

Max length12
Median length7
Mean length8.6189
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 광명시
2nd row경기도 김포시
3rd row경기도 광명시
4th row경기도 파주시
5th row경기도 평택시

Common Values

ValueCountFrequency (%)
경기도 화성시 630
 
6.3%
경기도 부천시 518
 
5.2%
경기도 남양주시 495
 
5.0%
경기도 파주시 426
 
4.3%
경기도 평택시 421
 
4.2%
경기도 성남시 분당구 372
 
3.7%
경기도 시흥시 351
 
3.5%
경기도 김포시 339
 
3.4%
경기도 의정부시 304
 
3.0%
경기도 고양시 덕양구 280
 
2.8%
Other values (32) 5864
58.6%

Length

2023-12-11T06:01:36.261503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 10000
42.2%
수원시 840
 
3.5%
용인시 762
 
3.2%
고양시 674
 
2.8%
성남시 652
 
2.7%
화성시 630
 
2.7%
부천시 518
 
2.2%
남양주시 495
 
2.1%
안산시 454
 
1.9%
파주시 426
 
1.8%
Other values (39) 8273
34.9%
Distinct2475
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:01:36.563030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length6
Mean length6.2937
Min length5

Characters and Unicode

Total characters62937
Distinct characters341
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

Unique93 ?
Unique (%)0.9%

Sample

1st row광명고등학교
2nd row운양중학교
3rd row온신초등학교
4th row덕암초등학교
5th row안중중학교
ValueCountFrequency (%)
석천초등학교 11
 
0.1%
오산초등학교 9
 
0.1%
탑동초등학교 8
 
0.1%
초당초등학교 8
 
0.1%
삼성초등학교 8
 
0.1%
상원초등학교 8
 
0.1%
원일초등학교 8
 
0.1%
신곡중학교 7
 
0.1%
성일정보고등학교 6
 
0.1%
가평초등학교 6
 
0.1%
Other values (2466) 9926
99.2%
2023-12-11T06:01:37.049908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10228
16.3%
10145
16.1%
7376
 
11.7%
5406
 
8.6%
2818
 
4.5%
2234
 
3.5%
637
 
1.0%
629
 
1.0%
598
 
1.0%
594
 
0.9%
Other values (331) 22272
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62798
99.8%
Lowercase Letter 67
 
0.1%
Close Punctuation 25
 
< 0.1%
Open Punctuation 25
 
< 0.1%
Uppercase Letter 16
 
< 0.1%
Space Separator 5
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10228
16.3%
10145
16.2%
7376
 
11.7%
5406
 
8.6%
2818
 
4.5%
2234
 
3.6%
637
 
1.0%
629
 
1.0%
598
 
1.0%
594
 
0.9%
Other values (315) 22133
35.2%
Lowercase Letter
ValueCountFrequency (%)
s 20
29.9%
n 10
14.9%
i 10
14.9%
e 7
 
10.4%
g 5
 
7.5%
l 5
 
7.5%
h 5
 
7.5%
u 5
 
7.5%
Uppercase Letter
ValueCountFrequency (%)
E 5
31.2%
B 5
31.2%
T 3
18.8%
I 3
18.8%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62798
99.8%
Latin 83
 
0.1%
Common 56
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10228
16.3%
10145
16.2%
7376
 
11.7%
5406
 
8.6%
2818
 
4.5%
2234
 
3.6%
637
 
1.0%
629
 
1.0%
598
 
1.0%
594
 
0.9%
Other values (315) 22133
35.2%
Latin
ValueCountFrequency (%)
s 20
24.1%
n 10
12.0%
i 10
12.0%
e 7
 
8.4%
E 5
 
6.0%
g 5
 
6.0%
l 5
 
6.0%
h 5
 
6.0%
u 5
 
6.0%
B 5
 
6.0%
Other values (2) 6
 
7.2%
Common
ValueCountFrequency (%)
) 25
44.6%
( 25
44.6%
5
 
8.9%
1 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62798
99.8%
ASCII 139
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
10228
16.3%
10145
16.2%
7376
 
11.7%
5406
 
8.6%
2818
 
4.5%
2234
 
3.6%
637
 
1.0%
629
 
1.0%
598
 
1.0%
594
 
0.9%
Other values (315) 22133
35.2%
ASCII
ValueCountFrequency (%)
) 25
18.0%
( 25
18.0%
s 20
14.4%
n 10
 
7.2%
i 10
 
7.2%
e 7
 
5.0%
E 5
 
3.6%
g 5
 
3.6%
l 5
 
3.6%
h 5
 
3.6%
Other values (6) 22
15.8%

학교급명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

설립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공립
9004 
사립
996 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공립 9004
90.0%
사립 996
 
10.0%

Length

2023-12-11T06:01:37.230922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:37.324068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 9004
90.0%
사립 996
 
10.0%

주야간명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5375 
주간
4611 
N
 
14

Length

Max length4
Median length4
Mean length3.0736
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5375
53.8%
주간 4611
46.1%
N 14
 
0.1%

Length

2023-12-11T06:01:37.453815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:37.557597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5375
53.8%
주간 4611
46.1%
n 14
 
0.1%

제외여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing14
Missing (%)0.1%
Memory size97.7 KiB
False
9986 
(Missing)
 
14
ValueCountFrequency (%)
False 9986
99.9%
(Missing) 14
 
0.1%
2023-12-11T06:01:37.655089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

제외사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

1학년수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct505
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.6898
Minimum0
Maximum573
Zeros89
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:37.817673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q169
median135
Q3235
95-th percentile366
Maximum573
Range573
Interquartile range (IQR)166

Descriptive statistics

Standard deviation112.78335
Coefficient of variation (CV)0.71522285
Kurtosis-0.32603543
Mean157.6898
Median Absolute Deviation (MAD)79
Skewness0.64585838
Sum1576898
Variance12720.084
MonotonicityNot monotonic
2023-12-11T06:01:37.995206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 89
 
0.9%
10 82
 
0.8%
9 79
 
0.8%
6 78
 
0.8%
11 77
 
0.8%
8 69
 
0.7%
14 68
 
0.7%
13 61
 
0.6%
15 59
 
0.6%
12 57
 
0.6%
Other values (495) 9281
92.8%
ValueCountFrequency (%)
0 89
0.9%
1 2
 
< 0.1%
2 8
 
0.1%
3 13
 
0.1%
4 26
 
0.3%
5 48
0.5%
6 78
0.8%
7 53
0.5%
8 69
0.7%
9 79
0.8%
ValueCountFrequency (%)
573 1
 
< 0.1%
563 1
 
< 0.1%
556 1
 
< 0.1%
554 1
 
< 0.1%
549 1
 
< 0.1%
537 1
 
< 0.1%
533 1
 
< 0.1%
531 3
< 0.1%
529 1
 
< 0.1%
525 1
 
< 0.1%

2학년수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct523
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.3087
Minimum0
Maximum656
Zeros78
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:38.145614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q169
median136
Q3237
95-th percentile374
Maximum656
Range656
Interquartile range (IQR)168

Descriptive statistics

Standard deviation115.23673
Coefficient of variation (CV)0.72335489
Kurtosis-0.15629433
Mean159.3087
Median Absolute Deviation (MAD)80
Skewness0.70177741
Sum1593087
Variance13279.503
MonotonicityNot monotonic
2023-12-11T06:01:38.330664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 80
 
0.8%
0 78
 
0.8%
12 78
 
0.8%
9 76
 
0.8%
11 70
 
0.7%
7 69
 
0.7%
14 68
 
0.7%
10 65
 
0.7%
15 62
 
0.6%
6 57
 
0.6%
Other values (513) 9297
93.0%
ValueCountFrequency (%)
0 78
0.8%
1 1
 
< 0.1%
2 13
 
0.1%
3 16
 
0.2%
4 31
 
0.3%
5 46
0.5%
6 57
0.6%
7 69
0.7%
8 80
0.8%
9 76
0.8%
ValueCountFrequency (%)
656 1
< 0.1%
617 1
< 0.1%
613 1
< 0.1%
567 1
< 0.1%
565 1
< 0.1%
563 1
< 0.1%
560 1
< 0.1%
557 1
< 0.1%
556 1
< 0.1%
554 1
< 0.1%

3학년수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct540
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.3317
Minimum0
Maximum652
Zeros111
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:38.493437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.95
Q168.75
median136
Q3242
95-th percentile391
Maximum652
Range652
Interquartile range (IQR)173.25

Descriptive statistics

Standard deviation120.7243
Coefficient of variation (CV)0.74368901
Kurtosis-0.03972903
Mean162.3317
Median Absolute Deviation (MAD)81
Skewness0.76742545
Sum1623317
Variance14574.357
MonotonicityNot monotonic
2023-12-11T06:01:38.670791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 111
 
1.1%
9 77
 
0.8%
8 76
 
0.8%
13 74
 
0.7%
6 72
 
0.7%
11 68
 
0.7%
7 68
 
0.7%
17 66
 
0.7%
12 66
 
0.7%
14 65
 
0.7%
Other values (530) 9257
92.6%
ValueCountFrequency (%)
0 111
1.1%
1 3
 
< 0.1%
2 6
 
0.1%
3 13
 
0.1%
4 26
 
0.3%
5 48
0.5%
6 72
0.7%
7 68
0.7%
8 76
0.8%
9 77
0.8%
ValueCountFrequency (%)
652 3
< 0.1%
624 1
 
< 0.1%
612 1
 
< 0.1%
609 1
 
< 0.1%
598 1
 
< 0.1%
592 1
 
< 0.1%
587 1
 
< 0.1%
586 1
 
< 0.1%
583 1
 
< 0.1%
576 1
 
< 0.1%

4학년수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct303
Distinct (%)5.0%
Missing3885
Missing (%)38.9%
Infinite0
Infinite (%)0.0%
Mean83.826656
Minimum0
Maximum417
Zeros320
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:38.851676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116
median79
Q3129
95-th percentile207.3
Maximum417
Range417
Interquartile range (IQR)113

Descriptive statistics

Standard deviation68.056561
Coefficient of variation (CV)0.81187255
Kurtosis-0.086915429
Mean83.826656
Median Absolute Deviation (MAD)58
Skewness0.65933358
Sum512600
Variance4631.6955
MonotonicityNot monotonic
2023-12-11T06:01:39.022689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 320
 
3.2%
6 119
 
1.2%
7 112
 
1.1%
9 111
 
1.1%
8 108
 
1.1%
11 90
 
0.9%
10 89
 
0.9%
5 85
 
0.9%
13 78
 
0.8%
12 77
 
0.8%
Other values (293) 4926
49.3%
(Missing) 3885
38.9%
ValueCountFrequency (%)
0 320
3.2%
1 25
 
0.2%
2 49
 
0.5%
3 55
 
0.5%
4 63
 
0.6%
5 85
 
0.9%
6 119
 
1.2%
7 112
 
1.1%
8 108
 
1.1%
9 111
 
1.1%
ValueCountFrequency (%)
417 1
< 0.1%
349 1
< 0.1%
347 1
< 0.1%
341 1
< 0.1%
339 1
< 0.1%
323 1
< 0.1%
322 1
< 0.1%
317 1
< 0.1%
313 2
< 0.1%
307 1
< 0.1%

5학년수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct293
Distinct (%)5.5%
Missing4644
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean94.247199
Minimum0
Maximum377
Zeros64
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:39.182704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q141
median91
Q3136.25
95-th percentile209
Maximum377
Range377
Interquartile range (IQR)95.25

Descriptive statistics

Standard deviation64.446196
Coefficient of variation (CV)0.68379959
Kurtosis-0.10667146
Mean94.247199
Median Absolute Deviation (MAD)48
Skewness0.52793476
Sum504788
Variance4153.3122
MonotonicityNot monotonic
2023-12-11T06:01:39.347797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 79
 
0.8%
11 76
 
0.8%
9 75
 
0.8%
10 71
 
0.7%
7 67
 
0.7%
0 64
 
0.6%
5 58
 
0.6%
6 57
 
0.6%
12 57
 
0.6%
15 53
 
0.5%
Other values (283) 4699
47.0%
(Missing) 4644
46.4%
ValueCountFrequency (%)
0 64
0.6%
1 4
 
< 0.1%
2 8
 
0.1%
3 23
 
0.2%
4 24
 
0.2%
5 58
0.6%
6 57
0.6%
7 67
0.7%
8 79
0.8%
9 75
0.8%
ValueCountFrequency (%)
377 1
< 0.1%
355 1
< 0.1%
348 1
< 0.1%
346 1
< 0.1%
343 1
< 0.1%
318 1
< 0.1%
317 1
< 0.1%
311 1
< 0.1%
309 1
< 0.1%
307 1
< 0.1%

6학년수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct300
Distinct (%)5.6%
Missing4644
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean95.198096
Minimum0
Maximum382
Zeros31
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:39.540297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q141
median93
Q3138
95-th percentile207
Maximum382
Range382
Interquartile range (IQR)97

Descriptive statistics

Standard deviation64.743425
Coefficient of variation (CV)0.6800916
Kurtosis-0.12401941
Mean95.198096
Median Absolute Deviation (MAD)48
Skewness0.50432284
Sum509881
Variance4191.7111
MonotonicityNot monotonic
2023-12-11T06:01:39.691190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 83
 
0.8%
9 75
 
0.8%
11 72
 
0.7%
12 68
 
0.7%
7 68
 
0.7%
6 67
 
0.7%
10 62
 
0.6%
14 59
 
0.6%
5 54
 
0.5%
15 53
 
0.5%
Other values (290) 4695
46.9%
(Missing) 4644
46.4%
ValueCountFrequency (%)
0 31
 
0.3%
1 4
 
< 0.1%
2 9
 
0.1%
3 24
 
0.2%
4 37
0.4%
5 54
0.5%
6 67
0.7%
7 68
0.7%
8 83
0.8%
9 75
0.8%
ValueCountFrequency (%)
382 1
< 0.1%
363 2
< 0.1%
350 1
< 0.1%
343 1
< 0.1%
324 1
< 0.1%
320 1
< 0.1%
318 1
< 0.1%
317 1
< 0.1%
313 1
< 0.1%
309 1
< 0.1%

특수학급학생수(명)
Real number (ℝ)

MISSING  ZEROS 

Distinct34
Distinct (%)0.4%
Missing759
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean4.8813981
Minimum0
Maximum37
Zeros2641
Zeros (%)26.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:39.835788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q37
95-th percentile14
Maximum37
Range37
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.9044552
Coefficient of variation (CV)1.0047235
Kurtosis2.3335872
Mean4.8813981
Median Absolute Deviation (MAD)4
Skewness1.314186
Sum45109
Variance24.053681
MonotonicityNot monotonic
2023-12-11T06:01:39.951094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 2641
26.4%
6 791
 
7.9%
5 773
 
7.7%
3 714
 
7.1%
4 650
 
6.5%
7 643
 
6.4%
2 550
 
5.5%
9 392
 
3.9%
8 388
 
3.9%
1 303
 
3.0%
Other values (24) 1396
14.0%
(Missing) 759
 
7.6%
ValueCountFrequency (%)
0 2641
26.4%
1 303
 
3.0%
2 550
 
5.5%
3 714
 
7.1%
4 650
 
6.5%
5 773
 
7.7%
6 791
 
7.9%
7 643
 
6.4%
8 388
 
3.9%
9 392
 
3.9%
ValueCountFrequency (%)
37 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
30 2
 
< 0.1%
29 2
 
< 0.1%
28 4
 
< 0.1%
27 7
0.1%
26 10
0.1%
25 8
0.1%
24 16
0.2%

순회학급학생수(명)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3115
Minimum0
Maximum21
Zeros9344
Zeros (%)93.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:01:40.074169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum21
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4408592
Coefficient of variation (CV)4.6255513
Kurtosis52.60086
Mean0.3115
Median Absolute Deviation (MAD)0
Skewness6.4296251
Sum3115
Variance2.0760754
MonotonicityNot monotonic
2023-12-11T06:01:40.169697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 9344
93.4%
3 134
 
1.3%
4 127
 
1.3%
5 92
 
0.9%
2 85
 
0.9%
1 51
 
0.5%
6 36
 
0.4%
7 35
 
0.4%
8 26
 
0.3%
10 15
 
0.1%
Other values (11) 55
 
0.5%
ValueCountFrequency (%)
0 9344
93.4%
1 51
 
0.5%
2 85
 
0.9%
3 134
 
1.3%
4 127
 
1.3%
5 92
 
0.9%
6 36
 
0.4%
7 35
 
0.4%
8 26
 
0.3%
9 13
 
0.1%
ValueCountFrequency (%)
21 1
 
< 0.1%
20 3
 
< 0.1%
19 1
 
< 0.1%
17 3
 
< 0.1%
16 2
 
< 0.1%
15 5
0.1%
14 4
 
< 0.1%
13 8
0.1%
12 5
0.1%
11 10
0.1%
Distinct6852
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:01:40.505109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.6944
Min length1

Characters and Unicode

Total characters56944
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4895 ?
Unique (%)48.9%

Sample

1st row907
2nd row1036(3)
3rd row70(1)
4th row69(5)
5th row257(0)
ValueCountFrequency (%)
42(0 11
 
0.1%
61(0 11
 
0.1%
65(0 10
 
0.1%
48(0 10
 
0.1%
55(0 10
 
0.1%
58(0 9
 
0.1%
290(0 9
 
0.1%
59(0 9
 
0.1%
99(0 9
 
0.1%
67(0 9
 
0.1%
Other values (6842) 9903
99.0%
2023-12-11T06:01:41.214113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 8266
14.5%
) 8266
14.5%
1 6504
11.4%
0 5350
9.4%
6 3849
6.8%
2 3740
6.6%
5 3728
6.5%
3 3700
6.5%
4 3629
6.4%
7 3605
6.3%
Other values (2) 6307
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40412
71.0%
Open Punctuation 8266
 
14.5%
Close Punctuation 8266
 
14.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6504
16.1%
0 5350
13.2%
6 3849
9.5%
2 3740
9.3%
5 3728
9.2%
3 3700
9.2%
4 3629
9.0%
7 3605
8.9%
8 3261
8.1%
9 3046
7.5%
Open Punctuation
ValueCountFrequency (%)
( 8266
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56944
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
( 8266
14.5%
) 8266
14.5%
1 6504
11.4%
0 5350
9.4%
6 3849
6.8%
2 3740
6.6%
5 3728
6.5%
3 3700
6.5%
4 3629
6.4%
7 3605
6.3%
Other values (2) 6307
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 8266
14.5%
) 8266
14.5%
1 6504
11.4%
0 5350
9.4%
6 3849
6.8%
2 3740
6.6%
5 3728
6.5%
3 3700
6.5%
4 3629
6.4%
7 3605
6.3%
Other values (2) 6307
11.1%

Interactions

2023-12-11T06:01:33.575652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:24.828547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.881244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:27.007880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:28.425108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.393721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.303537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:31.224326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:32.246608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:33.679899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:24.924772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.996443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:27.126460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:28.517539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.497224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.397021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:31.342294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:32.370066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:33.813707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.044390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:26.106363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:27.257011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:28.609236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.579445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.503702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:31.452760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:32.496423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:33.913193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.167462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:26.249853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:27.371350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:28.711646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.663651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.605343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:31.559621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:32.657627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:34.022186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.295761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:26.370174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:27.508159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:28.828184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.757599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.716218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:31.655803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:32.791782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:34.176157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.410610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:26.462414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:27.635154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:28.919035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.867412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.804095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:31.786094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:32.936290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:34.320989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.522589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:26.578395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:27.782387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.013693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.964688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.895843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:31.900185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:33.135472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:34.458788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.653965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:26.753561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:27.927301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.128818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.072625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.990031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:32.012025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:33.310156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:34.881168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:25.782103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:26.889711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:28.317002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:29.282758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:30.187940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:31.113377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:32.140203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:33.435468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:01:41.337763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명지역교육청명지역명설립구분명주야간명1학년수(명)2학년수(명)3학년수(명)4학년수(명)5학년수(명)6학년수(명)특수학급학생수(명)순회학급학생수(명)
기준년도1.0000.0000.0000.0000.0000.0920.1650.1210.1620.3890.1080.0260.1280.000
시군명0.0001.0000.9931.0000.2190.1020.4240.4060.4070.4110.4970.4930.2420.186
지역교육청명0.0000.9931.0000.9940.4320.0440.5560.5500.5430.4750.4750.4700.3520.148
지역명0.0001.0000.9941.0000.3080.1530.4510.4360.4350.4450.5280.5270.2750.221
설립구분명0.0000.2190.4320.3081.0000.1450.1880.2110.2120.2850.0480.0620.3370.092
주야간명0.0920.1020.0440.1530.1451.0000.1920.1710.168NaNNaNNaN0.0420.000
1학년수(명)0.1650.4240.5560.4510.1880.1921.0000.9410.9220.6910.7620.7380.4080.088
2학년수(명)0.1210.4060.5500.4360.2110.1710.9411.0000.9500.6980.7820.7670.4340.083
3학년수(명)0.1620.4070.5430.4350.2120.1680.9220.9501.0000.7110.8210.8130.4860.108
4학년수(명)0.3890.4110.4750.4450.285NaN0.6910.6980.7111.0000.9480.9420.3110.000
5학년수(명)0.1080.4970.4750.5280.048NaN0.7620.7820.8210.9481.0000.9570.3240.021
6학년수(명)0.0260.4930.4700.5270.062NaN0.7380.7670.8130.9420.9571.0000.3320.000
특수학급학생수(명)0.1280.2420.3520.2750.3370.0420.4080.4340.4860.3110.3240.3321.0000.242
순회학급학생수(명)0.0000.1860.1480.2210.0920.0000.0880.0830.1080.0000.0210.0000.2421.000
2023-12-11T06:01:41.500390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주야간명설립구분명시군명지역명지역교육청명
주야간명1.0000.0930.0870.1210.035
설립구분명0.0931.0000.1860.2450.343
시군명0.0870.1861.0000.9990.879
지역명0.1210.2450.9991.0000.879
지역교육청명0.0350.3430.8790.8791.000
2023-12-11T06:01:41.628610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도1학년수(명)2학년수(명)3학년수(명)4학년수(명)5학년수(명)6학년수(명)특수학급학생수(명)순회학급학생수(명)시군명지역교육청명지역명설립구분명주야간명
기준년도1.000-0.044-0.060-0.069-0.051-0.017-0.0180.060-0.0120.0000.0000.0000.0000.115
1학년수(명)-0.0441.0000.9700.9470.5300.9350.9090.2340.0310.1630.2370.1720.1440.147
2학년수(명)-0.0600.9701.0000.9710.5260.9530.9340.2500.0370.1550.2330.1650.1620.131
3학년수(명)-0.0690.9470.9711.0000.5200.9600.9470.2520.0410.1550.2290.1650.1630.129
4학년수(명)-0.0510.5300.5260.5201.0000.9680.9570.352-0.0310.1570.1920.1690.2181.000
5학년수(명)-0.0170.9350.9530.9600.9681.0000.9670.356-0.0110.1980.1920.2100.0371.000
6학년수(명)-0.0180.9090.9340.9470.9570.9671.0000.359-0.0030.1960.1890.2100.0471.000
특수학급학생수(명)0.0600.2340.2500.2520.3520.3560.3591.0000.1910.0870.1350.0980.2580.042
순회학급학생수(명)-0.0120.0310.0370.041-0.031-0.011-0.0030.1911.0000.0660.0540.0780.0710.000
시군명0.0000.1630.1550.1550.1570.1980.1960.0870.0661.0000.8790.9990.1860.087
지역교육청명0.0000.2370.2330.2290.1920.1920.1890.1350.0540.8791.0000.8790.3430.035
지역명0.0000.1720.1650.1650.1690.2100.2100.0980.0780.9990.8791.0000.2450.121
설립구분명0.0000.1440.1620.1630.2180.0370.0470.2580.0710.1860.3430.2451.0000.093
주야간명0.1150.1470.1310.1291.0001.0001.0000.0420.0000.0870.0350.1210.0931.000

Missing values

2023-12-11T06:01:35.063541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:01:35.358780image/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.
2023-12-11T06:01:35.531000image/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

기준년도시군명지역교육청명지역명학교명학교급명설립구분명주야간명제외여부제외사유1학년수(명)2학년수(명)3학년수(명)4학년수(명)5학년수(명)6학년수(명)특수학급학생수(명)순회학급학생수(명)합계사항(명)
2102020광명시경기도교육청경기도 광명시광명고등학교<NA>공립주간N<NA>302307285<NA><NA><NA>130907
29132019김포시경기도김포교육지원청경기도 김포시운양중학교<NA>공립주간N<NA>357359317<NA><NA><NA>301036(3)
122492015광명시경기도광명교육지원청경기도 광명시온신초등학교<NA>공립<NA>N<NA>11917131271070(1)
69102018파주시경기도파주교육지원청경기도 파주시덕암초등학교<NA>공립<NA>N<NA>10161181185069(5)
46132019평택시경기도평택교육지원청경기도 평택시안중중학교<NA>사립주간N<NA>868487<NA><NA><NA>00257(0)
56322018성남시경기도교육청경기도 성남시 분당구송림고등학교<NA>사립주간N<NA>2603093570<NA><NA><NA>0926(0)
114292016용인시경기도교육청경기도 용인시 기흥구흥덕고등학교<NA>공립주간N<NA>271260266<NA><NA><NA>90806(9)
110082016안양시경기도안양과천교육지원청경기도 안양시 만안구안양서여자중학교<NA>공립주간N<NA>344763<NA><NA><NA>00144(0)
81592017수원시경기도수원교육지원청경기도 수원시 영통구원천중학교<NA>공립주간N<NA>149182185<NA><NA><NA>60522(6)
20312020파주시경기도파주교육지원청경기도 파주시한가람초등학교<NA>공립<NA>N<NA>208225224216238218601335
기준년도시군명지역교육청명지역명학교명학교급명설립구분명주야간명제외여부제외사유1학년수(명)2학년수(명)3학년수(명)4학년수(명)5학년수(명)6학년수(명)특수학급학생수(명)순회학급학생수(명)합계사항(명)
112202016오산시경기도화성오산교육지원청경기도 오산시대호초등학교<NA>공립<NA>N<NA>11911712711810411200697(0)
100682016김포시경기도김포교육지원청경기도 김포시김포한가람초등학교<NA>공립<NA>N<NA>62667045394100323(0)
106442016수원시경기도수원교육지원청경기도 수원시 권선구수원금호초등학교<NA>공립<NA>N<NA>56646238373300290(0)
13212020안성시경기도안성교육지원청경기도 안성시어울초등학교<NA>공립<NA>N<NA>10010910377565860509
59942018시흥시경기도시흥교육지원청경기도 시흥시시흥능곡중학교<NA>공립주간N<NA>2132332215<NA><NA><NA>0672(5)
65062018용인시경기도용인교육지원청경기도 용인시 수지구용인한빛중학교<NA>공립주간N<NA>124115852<NA><NA><NA>0326(2)
127922015성남시경기도성남교육지원청경기도 성남시 중원구성남동초등학교<NA>공립<NA>N<NA>10710210810011613380674(8)
84992017안산시경기도안산교육지원청경기도 안산시 상록구정재초등학교<NA>공립<NA>N<NA>51445853575190323(9)
44682019파주시경기도파주교육지원청경기도 파주시금신초등학교<NA>공립<NA>N<NA>9896979410195120593(12)
79542017부천시경기도부천교육지원청경기도 부천시수주중학교<NA>공립주간N<NA>237217276<NA><NA><NA>100740(10)