Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells16802
Missing cells (%)9.3%
Duplicate rows534
Duplicate rows (%)5.3%
Total size in memory1.6 MiB
Average record size in memory164.0 B

Variable types

Numeric12
Categorical5
Text1

Dataset

Description경기도_학년별_학급별 학생수(초,중,고,그외) 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=YGJ121JNAHEESZTGDF3Z23237547&infSeq=2

Alerts

Dataset has 534 (5.3%) 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
1학년학생수평균값(명) is highly overall correlated with 2학년학생수평균값(명) and 6 other fieldsHigh correlation
2학년학생수평균값(명) is highly overall correlated with 1학년학생수평균값(명) and 6 other fieldsHigh correlation
3학년학생수평균값(명) is highly overall correlated with 1학년학생수평균값(명) and 6 other fieldsHigh correlation
4학년학생수평균값(명) is highly overall correlated with 1학년학생수평균값(명) and 7 other fieldsHigh correlation
5학년학생수평균값(명) is highly overall correlated with 1학년학생수평균값(명) and 7 other fieldsHigh correlation
6학년학생수평균값(명) is highly overall correlated with 1학년학생수평균값(명) and 7 other fieldsHigh correlation
학급학생수평균값(명) is highly overall correlated with 1학년학생수평균값(명) and 7 other fieldsHigh correlation
교사수(명) is highly overall correlated with 1학년학생수평균값(명) and 6 other fieldsHigh correlation
교사1인당학생평균값(명) is highly overall correlated with 4학년학생수평균값(명) and 3 other fieldsHigh correlation
지역교육청명 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
설립구분명 is highly imbalanced (55.9%)Imbalance
4학년학생수평균값(명) has 4590 (45.9%) missing valuesMissing
5학년학생수평균값(명) has 4590 (45.9%) missing valuesMissing
6학년학생수평균값(명) has 4590 (45.9%) missing valuesMissing
교사수(명) has 1516 (15.2%) missing valuesMissing
교사1인당학생평균값(명) has 1516 (15.2%) missing valuesMissing
3학년학생수평균값(명) has 130 (1.3%) zerosZeros
특수학급학생평균값(명) has 2860 (28.6%) zerosZeros
순회학습학생평균값(명) has 9356 (93.6%) zerosZeros

Reproduction

Analysis started2024-03-12 23:59:51.997666
Analysis finished2024-03-13 00:00:08.871516
Duration16.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.9071
Minimum2015
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:08.910882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016
median2017
Q32020
95-th percentile2023
Maximum2023
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.6255207
Coefficient of variation (CV)0.0013011108
Kurtosis-0.96967285
Mean2017.9071
Median Absolute Deviation (MAD)2
Skewness0.61468795
Sum20179071
Variance6.8933589
MonotonicityNot monotonic
2024-03-13T09:00:08.994347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2015 2079
20.8%
2016 2072
20.7%
2017 1516
15.2%
2022 778
 
7.8%
2019 739
 
7.4%
2023 728
 
7.3%
2021 719
 
7.2%
2018 709
 
7.1%
2020 660
 
6.6%
ValueCountFrequency (%)
2015 2079
20.8%
2016 2072
20.7%
2017 1516
15.2%
2018 709
 
7.1%
2019 739
 
7.4%
2020 660
 
6.6%
2021 719
 
7.2%
2022 778
 
7.8%
2023 728
 
7.3%
ValueCountFrequency (%)
2023 728
 
7.3%
2022 778
 
7.8%
2021 719
 
7.2%
2020 660
 
6.6%
2019 739
 
7.4%
2018 709
 
7.1%
2017 1516
15.2%
2016 2072
20.7%
2015 2079
20.8%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
용인시
816 
수원시
758 
화성시
692 
고양시
 
614
성남시
 
593
Other values (26)
6527 

Length

Max length4
Median length3
Mean length3.0875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row안산시
2nd row시흥시
3rd row고양시
4th row안산시
5th row평택시

Common Values

ValueCountFrequency (%)
용인시 816
 
8.2%
수원시 758
 
7.6%
화성시 692
 
6.9%
고양시 614
 
6.1%
성남시 593
 
5.9%
부천시 488
 
4.9%
안산시 476
 
4.8%
평택시 472
 
4.7%
파주시 457
 
4.6%
남양주시 454
 
4.5%
Other values (21) 4180
41.8%

Length

2024-03-13T09:00:09.336118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 816
 
8.2%
수원시 758
 
7.6%
화성시 692
 
6.9%
고양시 614
 
6.1%
성남시 593
 
5.9%
부천시 488
 
4.9%
안산시 476
 
4.8%
평택시 472
 
4.7%
파주시 457
 
4.6%
남양주시 454
 
4.5%
Other values (21) 4180
41.8%

지역교육청명
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도교육청
1970 
경기도화성오산교육지원청
718 
경기도용인교육지원청
679 
경기도수원교육지원청
591 
경기도성남교육지원청
 
466
Other values (21)
5576 

Length

Max length13
Median length10
Mean length9.769
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도안산교육지원청
2nd row경기도시흥교육지원청
3rd row경기도교육청
4th row경기도안산교육지원청
5th row경기도평택교육지원청

Common Values

ValueCountFrequency (%)
경기도교육청 1970
19.7%
경기도화성오산교육지원청 718
 
7.2%
경기도용인교육지원청 679
 
6.8%
경기도수원교육지원청 591
 
5.9%
경기도성남교육지원청 466
 
4.7%
경기도고양교육지원청 465
 
4.7%
경기도구리남양주교육지원청 452
 
4.5%
경기도안산교육지원청 383
 
3.8%
경기도평택교육지원청 383
 
3.8%
경기도파주교육지원청 377
 
3.8%
Other values (16) 3516
35.2%

Length

2024-03-13T09:00:09.430159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도교육청 1970
19.7%
경기도화성오산교육지원청 718
 
7.2%
경기도용인교육지원청 679
 
6.8%
경기도수원교육지원청 591
 
5.9%
경기도성남교육지원청 466
 
4.7%
경기도고양교육지원청 465
 
4.7%
경기도구리남양주교육지원청 452
 
4.5%
경기도안산교육지원청 383
 
3.8%
경기도평택교육지원청 383
 
3.8%
경기도파주교육지원청 377
 
3.8%
Other values (16) 3516
35.2%

지역명
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도 화성시
 
692
경기도 평택시
 
472
경기도 파주시
 
457
경기도 남양주시
 
454
경기도 부천시
 
370
Other values (40)
7555 

Length

Max length12
Median length7
Mean length8.6354
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 안산시 상록구
2nd row경기도 시흥시
3rd row경기도 고양시 덕양구
4th row경기도 안산시 상록구
5th row경기도 평택시

Common Values

ValueCountFrequency (%)
경기도 화성시 692
 
6.9%
경기도 평택시 472
 
4.7%
경기도 파주시 457
 
4.6%
경기도 남양주시 454
 
4.5%
경기도 부천시 370
 
3.7%
경기도 용인시 기흥구 346
 
3.5%
경기도 김포시 341
 
3.4%
경기도 시흥시 335
 
3.4%
경기도 의정부시 332
 
3.3%
경기도 성남시 분당구 328
 
3.3%
Other values (35) 5873
58.7%

Length

2024-03-13T09:00:09.534405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 10000
42.1%
용인시 816
 
3.4%
수원시 758
 
3.2%
화성시 692
 
2.9%
고양시 614
 
2.6%
성남시 593
 
2.5%
부천시 488
 
2.1%
안산시 476
 
2.0%
평택시 472
 
2.0%
파주시 457
 
1.9%
Other values (42) 8413
35.4%
Distinct2488
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T09:00:09.736953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length6
Mean length6.3045
Min length5

Characters and Unicode

Total characters63045
Distinct characters337
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

Unique183 ?
Unique (%)1.8%

Sample

1st row광덕중학교
2nd row월곶중학교
3rd row능곡고등학교
4th row광덕중학교
5th row평택중앙초등학교
ValueCountFrequency (%)
삼성초등학교 12
 
0.1%
탑동초등학교 12
 
0.1%
숭신여자고등학교 10
 
0.1%
초당초등학교 10
 
0.1%
구갈중학교 10
 
0.1%
의왕초등학교 10
 
0.1%
반월중학교 10
 
0.1%
마지초등학교 10
 
0.1%
의왕고등학교 9
 
0.1%
대안중학교 9
 
0.1%
Other values (2479) 9903
99.0%
2024-03-13T09:00:10.026686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10254
16.3%
10166
16.1%
7403
 
11.7%
5468
 
8.7%
2845
 
4.5%
2193
 
3.5%
664
 
1.1%
614
 
1.0%
599
 
1.0%
597
 
0.9%
Other values (327) 22242
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62951
99.9%
Lowercase Letter 68
 
0.1%
Uppercase Letter 16
 
< 0.1%
Space Separator 5
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10254
16.3%
10166
16.1%
7403
 
11.8%
5468
 
8.7%
2845
 
4.5%
2193
 
3.5%
664
 
1.1%
614
 
1.0%
599
 
1.0%
597
 
0.9%
Other values (311) 22148
35.2%
Lowercase Letter
ValueCountFrequency (%)
s 20
29.4%
n 10
14.7%
i 10
14.7%
e 8
 
11.8%
h 5
 
7.4%
u 5
 
7.4%
g 5
 
7.4%
l 5
 
7.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
31.2%
E 5
31.2%
T 3
18.8%
I 3
18.8%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62951
99.9%
Latin 84
 
0.1%
Common 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10254
16.3%
10166
16.1%
7403
 
11.8%
5468
 
8.7%
2845
 
4.5%
2193
 
3.5%
664
 
1.1%
614
 
1.0%
599
 
1.0%
597
 
0.9%
Other values (311) 22148
35.2%
Latin
ValueCountFrequency (%)
s 20
23.8%
n 10
11.9%
i 10
11.9%
e 8
 
9.5%
h 5
 
6.0%
u 5
 
6.0%
B 5
 
6.0%
E 5
 
6.0%
g 5
 
6.0%
l 5
 
6.0%
Other values (2) 6
 
7.1%
Common
ValueCountFrequency (%)
5
50.0%
) 2
 
20.0%
( 2
 
20.0%
1 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62951
99.9%
ASCII 94
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
10254
16.3%
10166
16.1%
7403
 
11.8%
5468
 
8.7%
2845
 
4.5%
2193
 
3.5%
664
 
1.1%
614
 
1.0%
599
 
1.0%
597
 
0.9%
Other values (311) 22148
35.2%
ASCII
ValueCountFrequency (%)
s 20
21.3%
n 10
10.6%
i 10
10.6%
e 8
 
8.5%
h 5
 
5.3%
5
 
5.3%
u 5
 
5.3%
B 5
 
5.3%
E 5
 
5.3%
g 5
 
5.3%
Other values (6) 16
17.0%

학교급명
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
초등학교
4451 
중학교
2136 
<NA>
1785 
고등학교
1603 
방통중
 
12
Other values (2)
 
13

Length

Max length4
Median length4
Mean length3.784
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
초등학교 4451
44.5%
중학교 2136
21.4%
<NA> 1785
17.8%
고등학교 1603
 
16.0%
방통중 12
 
0.1%
방통고 12
 
0.1%
공민학교 1
 
< 0.1%

Length

2024-03-13T09:00:10.131461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:00:10.212765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 4451
44.5%
중학교 2136
21.4%
na 1785
17.8%
고등학교 1603
 
16.0%
방통중 12
 
0.1%
방통고 12
 
0.1%
공민학교 1
 
< 0.1%

설립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공립
9086 
사립
914 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공립 9086
90.9%
사립 914
 
9.1%

Length

2024-03-13T09:00:10.308187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:00:10.378278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 9086
90.9%
사립 914
 
9.1%

1학년학생수평균값(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct292
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.35716
Minimum0
Maximum77
Zeros91
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:10.460614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q123
median26.6
Q329.8
95-th percentile34
Maximum77
Range77
Interquartile range (IQR)6.8

Descriptive statistics

Standard deviation7.0288815
Coefficient of variation (CV)0.27719514
Kurtosis2.4612708
Mean25.35716
Median Absolute Deviation (MAD)3.4
Skewness-1.1405179
Sum253571.6
Variance49.405175
MonotonicityNot monotonic
2024-03-13T09:00:10.573756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.0 217
 
2.2%
27.0 208
 
2.1%
26.0 188
 
1.9%
28.0 174
 
1.7%
24.0 157
 
1.6%
30.0 140
 
1.4%
26.3 131
 
1.3%
29.0 129
 
1.3%
22.0 129
 
1.3%
26.5 118
 
1.2%
Other values (282) 8409
84.1%
ValueCountFrequency (%)
0.0 91
0.9%
1.0 3
 
< 0.1%
2.0 6
 
0.1%
3.0 15
 
0.1%
4.0 29
 
0.3%
5.0 49
0.5%
6.0 75
0.8%
7.0 67
0.7%
8.0 58
0.6%
8.1 1
 
< 0.1%
ValueCountFrequency (%)
77.0 1
 
< 0.1%
72.0 2
 
< 0.1%
42.3 1
 
< 0.1%
41.5 1
 
< 0.1%
41.4 1
 
< 0.1%
41.3 1
 
< 0.1%
41.2 2
 
< 0.1%
41.0 5
0.1%
40.9 1
 
< 0.1%
40.8 1
 
< 0.1%

2학년학생수평균값(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct287
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.44133
Minimum0
Maximum72
Zeros90
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:10.686216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q123
median26.7
Q329.8
95-th percentile34.8
Maximum72
Range72
Interquartile range (IQR)6.8

Descriptive statistics

Standard deviation7.0956188
Coefficient of variation (CV)0.27890125
Kurtosis2.0955283
Mean25.44133
Median Absolute Deviation (MAD)3.3
Skewness-1.1321621
Sum254413.3
Variance50.347806
MonotonicityNot monotonic
2024-03-13T09:00:10.792039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.0 201
 
2.0%
25.0 195
 
1.9%
26.0 193
 
1.9%
28.0 186
 
1.9%
24.0 159
 
1.6%
29.0 140
 
1.4%
30.0 128
 
1.3%
27.3 127
 
1.3%
23.0 126
 
1.3%
27.5 111
 
1.1%
Other values (277) 8434
84.3%
ValueCountFrequency (%)
0.0 90
0.9%
1.0 1
 
< 0.1%
2.0 11
 
0.1%
3.0 23
 
0.2%
4.0 19
 
0.2%
5.0 54
0.5%
6.0 64
0.6%
7.0 69
0.7%
8.0 67
0.7%
8.3 1
 
< 0.1%
ValueCountFrequency (%)
72.0 2
 
< 0.1%
41.7 1
 
< 0.1%
41.6 1
 
< 0.1%
41.4 1
 
< 0.1%
41.2 1
 
< 0.1%
41.1 2
 
< 0.1%
41.0 5
0.1%
40.9 1
 
< 0.1%
40.8 3
< 0.1%
40.6 1
 
< 0.1%

3학년학생수평균값(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct285
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5109
Minimum0
Maximum46.6
Zeros130
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:10.898034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q123
median26.7
Q329.9
95-th percentile35.3
Maximum46.6
Range46.6
Interquartile range (IQR)6.9

Descriptive statistics

Standard deviation7.3902352
Coefficient of variation (CV)0.28968932
Kurtosis1.7274304
Mean25.5109
Median Absolute Deviation (MAD)3.4
Skewness-1.183765
Sum255109
Variance54.615577
MonotonicityNot monotonic
2024-03-13T09:00:11.001799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.0 205
 
2.1%
26.0 182
 
1.8%
28.0 181
 
1.8%
27.0 174
 
1.7%
23.0 166
 
1.7%
27.3 154
 
1.5%
24.0 148
 
1.5%
29.0 135
 
1.4%
0.0 130
 
1.3%
22.0 118
 
1.2%
Other values (275) 8407
84.1%
ValueCountFrequency (%)
0.0 130
1.3%
1.0 1
 
< 0.1%
2.0 9
 
0.1%
3.0 13
 
0.1%
4.0 26
 
0.3%
5.0 55
0.5%
6.0 75
0.8%
7.0 56
0.6%
7.1 1
 
< 0.1%
8.0 84
0.8%
ValueCountFrequency (%)
46.6 1
 
< 0.1%
42.0 2
< 0.1%
41.4 1
 
< 0.1%
41.3 1
 
< 0.1%
41.2 2
< 0.1%
40.8 3
< 0.1%
40.6 1
 
< 0.1%
40.5 2
< 0.1%
40.4 3
< 0.1%
40.3 2
< 0.1%

4학년학생수평균값(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct178
Distinct (%)3.3%
Missing4590
Missing (%)45.9%
Infinite0
Infinite (%)0.0%
Mean22.75756
Minimum0
Maximum38.3
Zeros49
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:11.104069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q120.3
median25
Q327.5
95-th percentile30
Maximum38.3
Range38.3
Interquartile range (IQR)7.2

Descriptive statistics

Standard deviation7.0586204
Coefficient of variation (CV)0.31016596
Kurtosis0.94597884
Mean22.75756
Median Absolute Deviation (MAD)3
Skewness-1.2711119
Sum123118.4
Variance49.824122
MonotonicityNot monotonic
2024-03-13T09:00:11.214380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.0 162
 
1.6%
27.0 154
 
1.5%
28.0 138
 
1.4%
25.0 129
 
1.3%
24.0 123
 
1.2%
23.0 113
 
1.1%
27.3 102
 
1.0%
25.3 87
 
0.9%
26.3 87
 
0.9%
9.0 85
 
0.9%
Other values (168) 4230
42.3%
(Missing) 4590
45.9%
ValueCountFrequency (%)
0.0 49
0.5%
1.0 2
 
< 0.1%
2.0 7
 
0.1%
3.0 18
 
0.2%
4.0 30
 
0.3%
5.0 60
0.6%
6.0 71
0.7%
7.0 73
0.7%
8.0 75
0.8%
9.0 85
0.9%
ValueCountFrequency (%)
38.3 1
< 0.1%
37.9 1
< 0.1%
37.3 2
< 0.1%
37.0 1
< 0.1%
36.7 2
< 0.1%
36.3 1
< 0.1%
35.7 2
< 0.1%
35.3 1
< 0.1%
34.9 1
< 0.1%
34.8 2
< 0.1%

5학년학생수평균값(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct177
Distinct (%)3.3%
Missing4590
Missing (%)45.9%
Infinite0
Infinite (%)0.0%
Mean22.700573
Minimum0
Maximum39
Zeros57
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:11.363559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q120.5
median25
Q327.4
95-th percentile30
Maximum39
Range39
Interquartile range (IQR)6.9

Descriptive statistics

Standard deviation7.1313953
Coefficient of variation (CV)0.31415045
Kurtosis1.0355684
Mean22.700573
Median Absolute Deviation (MAD)3
Skewness-1.3082059
Sum122810.1
Variance50.856799
MonotonicityNot monotonic
2024-03-13T09:00:11.493354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.0 174
 
1.7%
27.0 142
 
1.4%
28.0 133
 
1.3%
25.0 131
 
1.3%
24.0 126
 
1.3%
26.3 108
 
1.1%
23.0 105
 
1.1%
21.0 97
 
1.0%
22.0 87
 
0.9%
29.0 86
 
0.9%
Other values (167) 4221
42.2%
(Missing) 4590
45.9%
ValueCountFrequency (%)
0.0 57
0.6%
1.0 5
 
0.1%
2.0 4
 
< 0.1%
3.0 24
 
0.2%
4.0 41
0.4%
5.0 66
0.7%
6.0 59
0.6%
7.0 76
0.8%
8.0 70
0.7%
9.0 84
0.8%
ValueCountFrequency (%)
39.0 2
< 0.1%
37.9 1
< 0.1%
37.7 1
< 0.1%
37.4 1
< 0.1%
37.2 1
< 0.1%
37.0 1
< 0.1%
36.9 2
< 0.1%
35.9 2
< 0.1%
35.3 2
< 0.1%
35.2 1
< 0.1%

6학년학생수평균값(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct183
Distinct (%)3.4%
Missing4590
Missing (%)45.9%
Infinite0
Infinite (%)0.0%
Mean22.748688
Minimum0
Maximum38.3
Zeros29
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:11.630709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q120.7
median25.2
Q327.4
95-th percentile29.9
Maximum38.3
Range38.3
Interquartile range (IQR)6.7

Descriptive statistics

Standard deviation7.0767945
Coefficient of variation (CV)0.31108583
Kurtosis0.94837002
Mean22.748688
Median Absolute Deviation (MAD)2.8
Skewness-1.3192458
Sum123070.4
Variance50.08102
MonotonicityNot monotonic
2024-03-13T09:00:11.761992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.0 166
 
1.7%
27.0 151
 
1.5%
24.0 130
 
1.3%
25.0 127
 
1.3%
28.0 124
 
1.2%
27.3 110
 
1.1%
6.0 98
 
1.0%
26.5 94
 
0.9%
23.0 93
 
0.9%
22.0 92
 
0.9%
Other values (173) 4225
42.2%
(Missing) 4590
45.9%
ValueCountFrequency (%)
0.0 29
 
0.3%
1.0 5
 
0.1%
2.0 16
 
0.2%
3.0 23
 
0.2%
4.0 38
 
0.4%
5.0 67
0.7%
6.0 98
1.0%
7.0 82
0.8%
8.0 61
0.6%
8.8 1
 
< 0.1%
ValueCountFrequency (%)
38.3 1
 
< 0.1%
37.2 1
 
< 0.1%
36.4 2
< 0.1%
36.3 1
 
< 0.1%
36.0 3
< 0.1%
35.9 2
< 0.1%
35.1 1
 
< 0.1%
35.0 2
< 0.1%
34.7 1
 
< 0.1%
34.5 2
< 0.1%

특수학급학생평균값(명)
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.305
Minimum0
Maximum20
Zeros2860
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:11.871046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q36
95-th percentile8
Maximum20
Range20
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.7916222
Coefficient of variation (CV)0.84466631
Kurtosis-0.74113124
Mean3.305
Median Absolute Deviation (MAD)3
Skewness0.32025376
Sum33050
Variance7.7931543
MonotonicityNot monotonic
2024-03-13T09:00:11.961839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 2860
28.6%
5 1282
12.8%
6 1219
12.2%
4 1159
11.6%
3 771
 
7.7%
7 735
 
7.3%
1 696
 
7.0%
2 694
 
6.9%
8 296
 
3.0%
9 187
 
1.9%
Other values (7) 101
 
1.0%
ValueCountFrequency (%)
0 2860
28.6%
1 696
 
7.0%
2 694
 
6.9%
3 771
 
7.7%
4 1159
11.6%
5 1282
12.8%
6 1219
12.2%
7 735
 
7.3%
8 296
 
3.0%
9 187
 
1.9%
ValueCountFrequency (%)
20 1
 
< 0.1%
16 2
 
< 0.1%
14 3
 
< 0.1%
13 2
 
< 0.1%
12 17
 
0.2%
11 13
 
0.1%
10 63
 
0.6%
9 187
 
1.9%
8 296
3.0%
7 735
7.3%

순회학습학생평균값(명)
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2118
Minimum0
Maximum10
Zeros9356
Zeros (%)93.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:12.050595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.88035122
Coefficient of variation (CV)4.1565213
Kurtosis19.308206
Mean0.2118
Median Absolute Deviation (MAD)0
Skewness4.3978502
Sum2118
Variance0.77501826
MonotonicityNot monotonic
2024-03-13T09:00:12.130919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 9356
93.6%
4 195
 
1.9%
3 133
 
1.3%
5 112
 
1.1%
2 99
 
1.0%
1 91
 
0.9%
6 11
 
0.1%
7 2
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
0 9356
93.6%
1 91
 
0.9%
2 99
 
1.0%
3 133
 
1.3%
4 195
 
1.9%
5 112
 
1.1%
6 11
 
0.1%
7 2
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
7 2
 
< 0.1%
6 11
 
0.1%
5 112
 
1.1%
4 195
 
1.9%
3 133
 
1.3%
2 99
 
1.0%
1 91
 
0.9%
0 9356
93.6%

학급학생수평균값(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct370
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.48647
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:12.225456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.6
Q122.1
median25.6
Q328.5
95-th percentile33.4
Maximum77
Range76
Interquartile range (IQR)6.4

Descriptive statistics

Standard deviation6.6651785
Coefficient of variation (CV)0.27219842
Kurtosis1.8377505
Mean24.48647
Median Absolute Deviation (MAD)3.2
Skewness-0.86638351
Sum244864.7
Variance44.424604
MonotonicityNot monotonic
2024-03-13T09:00:12.357241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.2 111
 
1.1%
26.3 110
 
1.1%
27.2 106
 
1.1%
26.1 106
 
1.1%
26.5 103
 
1.0%
26.0 103
 
1.0%
26.2 103
 
1.0%
25.6 102
 
1.0%
25.3 101
 
1.0%
26.8 96
 
1.0%
Other values (360) 8959
89.6%
ValueCountFrequency (%)
1.0 1
 
< 0.1%
1.5 1
 
< 0.1%
2.0 3
< 0.1%
2.3 4
< 0.1%
2.5 6
0.1%
2.6 1
 
< 0.1%
3.0 6
0.1%
3.2 1
 
< 0.1%
3.3 5
0.1%
3.4 2
 
< 0.1%
ValueCountFrequency (%)
77.0 1
 
< 0.1%
72.0 2
< 0.1%
41.3 1
 
< 0.1%
41.1 2
< 0.1%
40.8 2
< 0.1%
40.7 1
 
< 0.1%
40.6 1
 
< 0.1%
40.4 3
< 0.1%
40.3 1
 
< 0.1%
39.9 3
< 0.1%

교사수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct110
Distinct (%)1.3%
Missing1516
Missing (%)15.2%
Infinite0
Infinite (%)0.0%
Mean35.929279
Minimum1
Maximum156
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:12.476321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q121
median34
Q349
95-th percentile72
Maximum156
Range155
Interquartile range (IQR)28

Descriptive statistics

Standard deviation19.74207
Coefficient of variation (CV)0.54947026
Kurtosis-0.022662999
Mean35.929279
Median Absolute Deviation (MAD)14
Skewness0.55662883
Sum304824
Variance389.74933
MonotonicityNot monotonic
2024-03-13T09:00:12.585196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 343
 
3.4%
7 319
 
3.2%
24 207
 
2.1%
34 203
 
2.0%
26 200
 
2.0%
33 195
 
1.9%
25 187
 
1.9%
32 175
 
1.8%
27 171
 
1.7%
29 170
 
1.7%
Other values (100) 6314
63.1%
(Missing) 1516
 
15.2%
ValueCountFrequency (%)
1 4
 
< 0.1%
2 13
 
0.1%
3 16
 
0.2%
4 20
 
0.2%
5 24
 
0.2%
6 19
 
0.2%
7 319
3.2%
8 343
3.4%
9 89
 
0.9%
10 74
 
0.7%
ValueCountFrequency (%)
156 1
< 0.1%
120 1
< 0.1%
116 1
< 0.1%
111 1
< 0.1%
110 1
< 0.1%
108 2
< 0.1%
107 1
< 0.1%
104 1
< 0.1%
103 2
< 0.1%
102 1
< 0.1%

교사1인당학생평균값(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct271
Distinct (%)3.2%
Missing1516
Missing (%)15.2%
Infinite0
Infinite (%)0.0%
Mean16.974741
Minimum1
Maximum31.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T09:00:12.697155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.9
Q114
median17.8
Q320.8
95-th percentile23.6
Maximum31.4
Range30.4
Interquartile range (IQR)6.8

Descriptive statistics

Standard deviation5.0353022
Coefficient of variation (CV)0.296635
Kurtosis-0.034704829
Mean16.974741
Median Absolute Deviation (MAD)3.3
Skewness-0.65837677
Sum144013.7
Variance25.354268
MonotonicityNot monotonic
2024-03-13T09:00:13.004066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.1 92
 
0.9%
20.6 88
 
0.9%
20.2 86
 
0.9%
21.4 85
 
0.9%
20.3 83
 
0.8%
19.5 83
 
0.8%
19.6 81
 
0.8%
19.3 80
 
0.8%
21.3 80
 
0.8%
21.6 78
 
0.8%
Other values (261) 7648
76.5%
(Missing) 1516
 
15.2%
ValueCountFrequency (%)
1.0 1
 
< 0.1%
1.5 2
 
< 0.1%
1.7 1
 
< 0.1%
1.8 2
 
< 0.1%
2.0 1
 
< 0.1%
2.1 1
 
< 0.1%
2.2 1
 
< 0.1%
2.3 3
< 0.1%
2.4 1
 
< 0.1%
2.5 7
0.1%
ValueCountFrequency (%)
31.4 2
< 0.1%
30.8 1
 
< 0.1%
29.8 1
 
< 0.1%
29.6 2
< 0.1%
29.4 1
 
< 0.1%
29.3 3
< 0.1%
29.2 1
 
< 0.1%
28.8 1
 
< 0.1%
28.5 1
 
< 0.1%
28.4 1
 
< 0.1%

Interactions

2024-03-13T09:00:07.481296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:55.197196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.658011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.742484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.842140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.837316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.056379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.041173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.120646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.171020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.378792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.400676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.567499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:55.282177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.748204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.837565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.924587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.919431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.139100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.141825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.211100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.255135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.484951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.485180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.651901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:55.375032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.830828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.922090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.008089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.998886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.220035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.250357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.291657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.332644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.567387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.565796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.721954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:55.481828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.918279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.007443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.084487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.086556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.307214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.336020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.371382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.412894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.652035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.645217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.790737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:55.844194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.001274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.117206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.160347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.183949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.394239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.419932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.443550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.479613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.745365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.716554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.885123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:55.999954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.084671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.229239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.256916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.506457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.489970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.526098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.549801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.559231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.829778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.797758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.970609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.109174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.169265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.320276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.355097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.585535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.574183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.629489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.651354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.904629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.908475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.918415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:08.054038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.210916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.270526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.406850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.443379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.666663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.656894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.711648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.733727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.983549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.993398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.019601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:08.135588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.309896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.385771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.496268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.523498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.751046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.738209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.792668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.821114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.063088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.080648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.104493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:08.213771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.398635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.471602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.570024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.602067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.831033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.812569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.871871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.895600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.132766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.158097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.201741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:08.290612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.488325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.569668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.674683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.683993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.908562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.894082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:02.952140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.980081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.214065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.238231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.291008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:08.369130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:56.577183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:57.650716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:58.762842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:59:59.764703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:00.978038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:01.963948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:03.023033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:04.071151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:05.296738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:06.322807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:00:07.372317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T09:00:13.087983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명지역교육청명지역명학교급명설립구분명1학년학생수평균값(명)2학년학생수평균값(명)3학년학생수평균값(명)4학년학생수평균값(명)5학년학생수평균값(명)6학년학생수평균값(명)특수학급학생평균값(명)순회학습학생평균값(명)학급학생수평균값(명)교사수(명)교사1인당학생평균값(명)
기준년도1.0000.1670.1460.2700.0000.0180.1240.1540.2170.1350.1280.1180.2680.1120.1510.0790.151
시군명0.1671.0000.9931.0000.1370.2290.4370.4140.3960.4880.4650.4920.1970.1750.4510.4300.422
지역교육청명0.1460.9931.0000.9950.7430.4180.4590.4410.4240.4800.4600.4820.3170.1360.4780.6060.542
지역명0.2701.0000.9951.0000.1960.3010.4610.4360.4270.5100.4890.5160.2400.2140.4800.5060.451
학교급명0.0000.1370.7430.1961.0000.5240.4330.3760.4190.2320.2090.2340.2400.0470.3910.5270.475
설립구분명0.0180.2290.4180.3010.5241.0000.0970.1080.1660.0700.0610.0900.4210.0770.1300.1490.309
1학년학생수평균값(명)0.1240.4370.4590.4610.4330.0971.0000.9280.7710.7250.7220.7140.2010.0000.9670.5400.618
2학년학생수평균값(명)0.1540.4140.4410.4360.3760.1080.9281.0000.7710.7670.7700.7290.2320.0000.9350.5920.639
3학년학생수평균값(명)0.2170.3960.4240.4270.4190.1660.7710.7711.0000.7430.7600.7280.2990.0360.8100.5450.767
4학년학생수평균값(명)0.1350.4880.4800.5100.2320.0700.7250.7670.7431.0000.8570.8500.3240.0580.9420.6430.906
5학년학생수평균값(명)0.1280.4650.4600.4890.2090.0610.7220.7700.7600.8571.0000.8510.2860.1000.9510.6390.917
6학년학생수평균값(명)0.1180.4920.4820.5160.2340.0900.7140.7290.7280.8500.8511.0000.3020.0660.9380.6350.901
특수학급학생평균값(명)0.2680.1970.3170.2400.2400.4210.2010.2320.2990.3240.2860.3021.0000.1670.2370.2850.300
순회학습학생평균값(명)0.1120.1750.1360.2140.0470.0770.0000.0000.0360.0580.1000.0660.1671.0000.0530.0890.065
학급학생수평균값(명)0.1510.4510.4780.4800.3910.1300.9670.9350.8100.9420.9510.9380.2370.0531.0000.5640.676
교사수(명)0.0790.4300.6060.5060.5270.1490.5400.5920.5450.6430.6390.6350.2850.0890.5641.0000.517
교사1인당학생평균값(명)0.1510.4220.5420.4510.4750.3090.6180.6390.7670.9060.9170.9010.3000.0650.6760.5171.000
2024-03-13T09:00:13.214605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명설립구분명학교급명지역교육청명지역명
시군명1.0000.1950.0600.8800.999
설립구분명0.1951.0000.3790.3320.251
학교급명0.0600.3791.0000.4490.084
지역교육청명0.8800.3320.4491.0000.880
지역명0.9990.2510.0840.8801.000
2024-03-13T09:00:13.299667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도1학년학생수평균값(명)2학년학생수평균값(명)3학년학생수평균값(명)4학년학생수평균값(명)5학년학생수평균값(명)6학년학생수평균값(명)특수학급학생평균값(명)순회학습학생평균값(명)학급학생수평균값(명)교사수(명)교사1인당학생평균값(명)시군명지역교육청명지역명학교급명설립구분명
기준년도1.000-0.183-0.198-0.201-0.086-0.085-0.1070.000-0.029-0.1980.026-0.2040.0550.0480.0960.0000.006
1학년학생수평균값(명)-0.1831.0000.8150.7810.7150.7070.6780.1290.0090.8970.5900.4420.1980.2130.2050.2730.104
2학년학생수평균값(명)-0.1980.8151.0000.8360.7300.7270.7070.1560.0120.9080.5910.5000.1850.2040.1910.2360.118
3학년학생수평균값(명)-0.2010.7810.8361.0000.7320.7330.7220.1500.0290.8910.5980.4650.1500.1670.1570.2360.127
4학년학생수평균값(명)-0.0860.7150.7300.7321.0000.7350.7150.254-0.0320.8560.7450.8330.1930.1900.1970.1770.054
5학년학생수평균값(명)-0.0850.7070.7270.7330.7351.0000.7270.257-0.0200.8550.7420.8260.1820.1800.1860.1600.049
6학년학생수평균값(명)-0.1070.6780.7070.7220.7150.7271.0000.235-0.0130.8360.7330.8090.1950.1910.2000.1790.069
특수학급학생평균값(명)0.0000.1290.1560.1500.2540.2570.2351.0000.1480.0770.2450.2050.0730.1210.0830.1240.276
순회학습학생평균값(명)-0.0290.0090.0120.029-0.032-0.020-0.0130.1481.000-0.0610.046-0.0750.0610.0490.0700.0190.070
학급학생수평균값(명)-0.1980.8970.9080.8910.8560.8550.8360.077-0.0611.0000.6660.5180.2050.2240.2150.2430.139
교사수(명)0.0260.5900.5910.5980.7450.7420.7330.2450.0460.6661.0000.3040.1750.2750.1950.2920.148
교사1인당학생평균값(명)-0.2040.4420.5000.4650.8330.8260.8090.205-0.0750.5180.3041.0000.1620.2290.1690.2730.238
시군명0.0550.1980.1850.1500.1930.1820.1950.0730.0610.2050.1750.1621.0000.8800.9990.0600.195
지역교육청명0.0480.2130.2040.1670.1900.1800.1910.1210.0490.2240.2750.2290.8801.0000.8800.4490.332
지역명0.0960.2050.1910.1570.1970.1860.2000.0830.0700.2150.1950.1690.9990.8801.0000.0840.251
학교급명0.0000.2730.2360.2360.1770.1600.1790.1240.0190.2430.2920.2730.0600.4490.0841.0000.379
설립구분명0.0060.1040.1180.1270.0540.0490.0690.2760.0700.1390.1480.2380.1950.3320.2510.3791.000

Missing values

2024-03-13T09:00:08.491342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T09:00:08.672590image/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.
2024-03-13T09:00:08.803897image/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

기준년도시군명지역교육청명지역명학교명학교급명설립구분명1학년학생수평균값(명)2학년학생수평균값(명)3학년학생수평균값(명)4학년학생수평균값(명)5학년학생수평균값(명)6학년학생수평균값(명)특수학급학생평균값(명)순회학습학생평균값(명)학급학생수평균값(명)교사수(명)교사1인당학생평균값(명)
227562016안산시경기도안산교육지원청경기도 안산시 상록구광덕중학교<NA>공립28.729.536.7<NA><NA><NA>0031.62919.6
225732016시흥시경기도시흥교육지원청경기도 시흥시월곶중학교<NA>공립28.429.432.5<NA><NA><NA>6028.32219.3
26812022고양시경기도교육청경기도 고양시 덕양구능곡고등학교고등학교공립24.121.522.9<NA><NA><NA>0022.86611.8
157702017안산시경기도안산교육지원청경기도 안산시 상록구광덕중학교<NA>공립32.028.328.8<NA><NA><NA>0029.6<NA><NA>
326232015평택시경기도평택교육지원청경기도 평택시평택중앙초등학교초등학교공립24.021.031.027.526.025.74023.12218.9
89702020용인시경기도용인교육지원청경기도 용인시 기흥구상갈중학교중학교공립29.527.728.0<NA><NA><NA>4027.13215.2
211732016부천시경기도교육청경기도 부천시수주고등학교고등학교공립23.119.722.2<NA><NA><NA>8020.35511.4
92852020평택시경기도평택교육지원청경기도 평택시태광중학교중학교사립30.030.431.1<NA><NA><NA>0030.53918.0
193052017화성시경기도화성오산교육지원청경기도 화성시고정초등학교초등학교공립7.07.06.05.05.07.0205.6<NA><NA>
51552021고양시경기도교육청경기도 고양시 일산서구일산국제컨벤션고등학교고등학교공립21.921.720.7<NA><NA><NA>3019.8719.8
기준년도시군명지역교육청명지역명학교명학교급명설립구분명1학년학생수평균값(명)2학년학생수평균값(명)3학년학생수평균값(명)4학년학생수평균값(명)5학년학생수평균값(명)6학년학생수평균값(명)특수학급학생평균값(명)순회학습학생평균값(명)학급학생수평균값(명)교사수(명)교사1인당학생평균값(명)
165722017양평군경기도양평교육지원청경기도 양평군강하초등학교초등학교공립16.014.024.019.024.021.00019.7<NA><NA>
322512015파주시경기도파주교육지원청경기도 파주시선유중학교중학교공립26.520.022.3<NA><NA><NA>5021.72314.1
259002016하남시경기도교육청경기도 하남시미사강변고등학교고등학교공립13.90.00.0<NA><NA><NA>1012.4148.0
34222022수원시경기도수원교육지원청경기도 수원시 장안구수원북중학교중학교공립23.727.329.3<NA><NA><NA>4023.32113.3
298012015안산시경기도안산교육지원청경기도 안산시 상록구반월초등학교초등학교공립20.321.723.325.523.028.55022.22118.0
162442017안양시경기도교육청경기도 안양시 만안구근명여자정보고등학교고등학교사립24.624.326.4<NA><NA><NA>0025.1<NA><NA>
280432015동두천시경기도동두천양주교육지원청경기도 동두천시탑동초등학교초등학교공립17.019.517.514.015.514.00016.51313.9
107212019시흥시경기도시흥교육지원청경기도 시흥시은계초등학교초등학교공립26.323.327.724.326.824.81123.83318.8
20442023파주시경기도파주교육지원청경기도 파주시적암초등학교초등학교공립0.05.00.05.00.07.0104.563.0
52352021광명시경기도광명교육지원청경기도 광명시광명초등학교초등학교공립22.720.324.019.821.023.26020.52917.0

Duplicate rows

Most frequently occurring

기준년도시군명지역교육청명지역명학교명학교급명설립구분명1학년학생수평균값(명)2학년학생수평균값(명)3학년학생수평균값(명)4학년학생수평균값(명)5학년학생수평균값(명)6학년학생수평균값(명)특수학급학생평균값(명)순회학습학생평균값(명)학급학생수평균값(명)교사수(명)교사1인당학생평균값(명)# duplicates
02015가평군경기도가평교육지원청경기도 가평군상면초등학교초등학교공립12.017.010.015.013.017.02012.3712.32
12015가평군경기도가평교육지원청경기도 가평군청심국제중학교중학교사립25.525.024.8<NA><NA><NA>0025.12313.12
22015가평군경기도가평교육지원청경기도 가평군청평중학교중학교공립26.325.823.7<NA><NA><NA>3023.72515.22
32015고양시경기도고양교육지원청경기도 고양시 덕양구도래울중학교중학교공립31.336.530.0<NA><NA><NA>2028.91517.32
42015고양시경기도고양교육지원청경기도 고양시 덕양구흥도초등학교초등학교공립30.723.523.326.327.024.70025.72421.42
52015고양시경기도고양교육지원청경기도 고양시 일산동구하늘초등학교초등학교공립26.024.328.526.826.325.33025.22921.82
62015고양시경기도고양교육지원청경기도 고양시 일산동구호수초등학교초등학교공립29.025.628.023.530.326.05025.33022.82
72015고양시경기도고양교육지원청경기도 고양시 일산서구신일중학교중학교공립33.335.235.3<NA><NA><NA>5033.16220.32
82015고양시경기도고양교육지원청경기도 고양시 일산서구장성초등학교초등학교공립21.324.023.320.029.328.05023.32319.32
92015고양시경기도교육청경기도 고양시 덕양구행신고등학교고등학교공립31.333.335.3<NA><NA><NA>7031.97316.62