Overview

Dataset statistics

Number of variables11
Number of observations122
Missing cells118
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.7 KiB
Average record size in memory90.1 B

Variable types

Numeric1
Categorical3
Text6
DateTime1

Dataset

Description경기도 화성시 2013년 관내 학교 현황에 대한 정보(급별, 공사립, 학교명, 주소, 전화번호 등)를 제공합니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15052020/fileData.do

Alerts

No. is highly overall correlated with 급별High correlation
급별 is highly overall correlated with No. and 1 other fieldsHigh correlation
공사립 is highly overall correlated with 급별High correlation
비고 has 118 (96.7%) missing valuesMissing
No. has unique valuesUnique
학교명 has unique valuesUnique
교무실 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:46:46.400836
Analysis finished2023-12-12 22:46:47.136528
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

No.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.5
Minimum1
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T07:46:47.201090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.05
Q131.25
median61.5
Q391.75
95-th percentile115.95
Maximum122
Range121
Interquartile range (IQR)60.5

Descriptive statistics

Standard deviation35.362409
Coefficient of variation (CV)0.57499853
Kurtosis-1.2
Mean61.5
Median Absolute Deviation (MAD)30.5
Skewness0
Sum7503
Variance1250.5
MonotonicityStrictly increasing
2023-12-13T07:46:47.330907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
93 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
Other values (112) 112
91.8%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%

급별
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
초
72 
중
29 
고
19 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
초 72
59.0%
중 29
23.8%
고 19
 
15.6%
4 2
 
1.6%

Length

2023-12-13T07:46:47.506596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:46:47.601583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초 72
59.0%
중 29
23.8%
고 19
 
15.6%
4 2
 
1.6%

공사립
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
공립
105 
사립
17 

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 105
86.1%
사립 17
 
13.9%

Length

2023-12-13T07:46:47.733700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:46:47.853302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 105
86.1%
사립 17
 
13.9%

학교명
Text

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T07:46:48.222346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.3032787
Min length3

Characters and Unicode

Total characters403
Distinct characters106
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)100.0%

Sample

1st row갈담초
2nd row갈천초
3rd row고정초
4th row구봉초
5th row기산초
ValueCountFrequency (%)
갈담초 1
 
0.8%
안화중 1
 
0.8%
송산중 1
 
0.8%
솔빛중 1
 
0.8%
석우중 1
 
0.8%
서신중 1
 
0.8%
삼괴중 1
 
0.8%
비봉중 1
 
0.8%
봉담중 1
 
0.8%
병점중 1
 
0.8%
Other values (112) 112
91.8%
2023-12-13T07:46:48.783087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 69
 
17.1%
중 29
 
7.2%
고 20
 
5.0%
화 18
 
4.5%
안 15
 
3.7%
동 12
 
3.0%
성 9
 
2.2%
송 9
 
2.2%
남 8
 
2.0%
봉 8
 
2.0%
Other values (96) 206
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 403
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 69
 
17.1%
중 29
 
7.2%
고 20
 
5.0%
화 18
 
4.5%
안 15
 
3.7%
동 12
 
3.0%
성 9
 
2.2%
송 9
 
2.2%
남 8
 
2.0%
봉 8
 
2.0%
Other values (96) 206
51.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 403
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 69
 
17.1%
중 29
 
7.2%
고 20
 
5.0%
화 18
 
4.5%
안 15
 
3.7%
동 12
 
3.0%
성 9
 
2.2%
송 9
 
2.2%
남 8
 
2.0%
봉 8
 
2.0%
Other values (96) 206
51.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 403
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 69
 
17.1%
중 29
 
7.2%
고 20
 
5.0%
화 18
 
4.5%
안 15
 
3.7%
동 12
 
3.0%
성 9
 
2.2%
송 9
 
2.2%
남 8
 
2.0%
봉 8
 
2.0%
Other values (96) 206
51.1%

주소
Text

Distinct121
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T07:46:49.103871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.672131
Min length4

Characters and Unicode

Total characters1302
Distinct characters137
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)98.4%

Sample

1st row봉담읍 갈담초교길 24
2nd row향남읍 갈천리 156-1
3rd row송산면 공룡로 326
4th row병점2동 862
5th row동탄지성로 344
ValueCountFrequency (%)
향남읍 15
 
4.7%
봉담읍 10
 
3.2%
장안면 7
 
2.2%
우정읍 6
 
1.9%
송산면 5
 
1.6%
정남면 4
 
1.3%
비봉면 4
 
1.3%
서신면 4
 
1.3%
마도면 3
 
0.9%
42 3
 
0.9%
Other values (218) 256
80.8%
2023-12-13T07:46:49.546966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
197
 
15.1%
1 73
 
5.6%
로 67
 
5.1%
2 55
 
4.2%
길 43
 
3.3%
4 41
 
3.1%
5 36
 
2.8%
3 36
 
2.8%
면 36
 
2.8%
동 34
 
2.6%
Other values (127) 684
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 705
54.1%
Decimal Number 371
28.5%
Space Separator 197
 
15.1%
Dash Punctuation 29
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 67
 
9.5%
길 43
 
6.1%
면 36
 
5.1%
동 34
 
4.8%
읍 32
 
4.5%
남 20
 
2.8%
번 19
 
2.7%
정 18
 
2.6%
안 18
 
2.6%
리 17
 
2.4%
Other values (115) 401
56.9%
Decimal Number
ValueCountFrequency (%)
1 73
19.7%
2 55
14.8%
4 41
11.1%
5 36
9.7%
3 36
9.7%
6 33
8.9%
7 32
8.6%
8 24
 
6.5%
9 22
 
5.9%
0 19
 
5.1%
Space Separator
ValueCountFrequency (%)
197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 705
54.1%
Common 597
45.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 67
 
9.5%
길 43
 
6.1%
면 36
 
5.1%
동 34
 
4.8%
읍 32
 
4.5%
남 20
 
2.8%
번 19
 
2.7%
정 18
 
2.6%
안 18
 
2.6%
리 17
 
2.4%
Other values (115) 401
56.9%
Common
ValueCountFrequency (%)
197
33.0%
1 73
 
12.2%
2 55
 
9.2%
4 41
 
6.9%
5 36
 
6.0%
3 36
 
6.0%
6 33
 
5.5%
7 32
 
5.4%
- 29
 
4.9%
8 24
 
4.0%
Other values (2) 41
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 705
54.1%
ASCII 597
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
197
33.0%
1 73
 
12.2%
2 55
 
9.2%
4 41
 
6.9%
5 36
 
6.0%
3 36
 
6.0%
6 33
 
5.5%
7 32
 
5.4%
- 29
 
4.9%
8 24
 
4.0%
Other values (2) 41
 
6.9%
Hangul
ValueCountFrequency (%)
로 67
 
9.5%
길 43
 
6.1%
면 36
 
5.1%
동 34
 
4.8%
읍 32
 
4.5%
남 20
 
2.8%
번 19
 
2.7%
정 18
 
2.6%
안 18
 
2.6%
리 17
 
2.4%
Other values (115) 401
56.9%

교무실
Text

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T07:46:49.862157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length12.204918
Min length12

Characters and Unicode

Total characters1489
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

Unique122 ?
Unique (%)100.0%

Sample

1st row031-227-1546
2nd row031-352-0510
3rd row031-357-1308
4th row031-225-8328
5th row031-224-9013
ValueCountFrequency (%)
031-227-1546 1
 
0.8%
031-221-4732 1
 
0.8%
031-357-1021 1
 
0.8%
031-613-1864 1
 
0.8%
031-613-1102 1
 
0.8%
031-355-0783 1
 
0.8%
031-351-1091 1
 
0.8%
031-356-0795 1
 
0.8%
031-298-5816 1
 
0.8%
031-224-0417 1
 
0.8%
Other values (112) 112
91.8%
2023-12-13T07:46:50.355415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 250
16.8%
3 248
16.7%
- 244
16.4%
1 237
15.9%
5 123
8.3%
2 116
7.8%
8 81
 
5.4%
6 57
 
3.8%
7 47
 
3.2%
4 45
 
3.0%
Other values (2) 41
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1244
83.5%
Dash Punctuation 244
 
16.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 250
20.1%
3 248
19.9%
1 237
19.1%
5 123
9.9%
2 116
9.3%
8 81
 
6.5%
6 57
 
4.6%
7 47
 
3.8%
4 45
 
3.6%
9 40
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 244
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1489
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 250
16.8%
3 248
16.7%
- 244
16.4%
1 237
15.9%
5 123
8.3%
2 116
7.8%
8 81
 
5.4%
6 57
 
3.8%
7 47
 
3.2%
4 45
 
3.0%
Other values (2) 41
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 250
16.8%
3 248
16.7%
- 244
16.4%
1 237
15.9%
5 123
8.3%
2 116
7.8%
8 81
 
5.4%
6 57
 
3.8%
7 47
 
3.2%
4 45
 
3.0%
Other values (2) 41
 
2.8%

행정실
Text

Distinct116
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T07:46:50.637740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.172131
Min length12

Characters and Unicode

Total characters1485
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)90.2%

Sample

1st row031-227-9144
2nd row031-352-0516
3rd row031-357-1309
4th row031-225-8329
5th row031-224-9014
ValueCountFrequency (%)
031-351-3638 2
 
1.6%
031-350-8303 2
 
1.6%
031-352-8429 2
 
1.6%
031-358-1155 2
 
1.6%
031-352-8496 2
 
1.6%
031-357-5083 2
 
1.6%
031-613-1862 1
 
0.8%
031-221-6329 1
 
0.8%
031-351-3102 1
 
0.8%
031-355-0784 1
 
0.8%
Other values (106) 106
86.9%
2023-12-13T07:46:51.039690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 261
17.6%
- 244
16.4%
0 220
14.8%
1 213
14.3%
5 126
8.5%
2 114
7.7%
8 87
 
5.9%
9 60
 
4.0%
6 54
 
3.6%
7 53
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1241
83.6%
Dash Punctuation 244
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 261
21.0%
0 220
17.7%
1 213
17.2%
5 126
10.2%
2 114
9.2%
8 87
 
7.0%
9 60
 
4.8%
6 54
 
4.4%
7 53
 
4.3%
4 53
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 244
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1485
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 261
17.6%
- 244
16.4%
0 220
14.8%
1 213
14.3%
5 126
8.5%
2 114
7.7%
8 87
 
5.9%
9 60
 
4.0%
6 54
 
3.6%
7 53
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 261
17.6%
- 244
16.4%
0 220
14.8%
1 213
14.3%
5 126
8.5%
2 114
7.7%
8 87
 
5.9%
9 60
 
4.0%
6 54
 
3.6%
7 53
 
3.6%

FAX
Text

Distinct119
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T07:46:51.329724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.172131
Min length12

Characters and Unicode

Total characters1485
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)95.1%

Sample

1st row031-297-9143
2nd row031-352-4940
3rd row031-357-6135
4th row031-225-8544
5th row031-224-9024
ValueCountFrequency (%)
031-356-0792 2
 
1.6%
031-352-6913 2
 
1.6%
031-352-7811 2
 
1.6%
031-352-3091 1
 
0.8%
031-297-9143 1
 
0.8%
031-613-1132 1
 
0.8%
031-355-0786 1
 
0.8%
031-358-4313 1
 
0.8%
031-298-5818 1
 
0.8%
031-224-0458 1
 
0.8%
Other values (109) 109
89.3%
2023-12-13T07:46:51.941785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 249
16.8%
- 244
16.4%
0 206
13.9%
1 203
13.7%
5 133
9.0%
2 108
7.3%
8 91
 
6.1%
6 65
 
4.4%
9 63
 
4.2%
4 63
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1241
83.6%
Dash Punctuation 244
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 249
20.1%
0 206
16.6%
1 203
16.4%
5 133
10.7%
2 108
8.7%
8 91
 
7.3%
6 65
 
5.2%
9 63
 
5.1%
4 63
 
5.1%
7 60
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 244
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1485
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 249
16.8%
- 244
16.4%
0 206
13.9%
1 203
13.7%
5 133
9.0%
2 108
7.3%
8 91
 
6.1%
6 65
 
4.4%
9 63
 
4.2%
4 63
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 249
16.8%
- 244
16.4%
0 206
13.9%
1 203
13.7%
5 133
9.0%
2 108
7.3%
8 91
 
6.1%
6 65
 
4.4%
9 63
 
4.2%
4 63
 
4.2%

행정동
Categorical

Distinct27
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
향남읍
15 
봉담읍
11 
동탄1동
8 
동탄2동
8 
병점2동
 
7
Other values (22)
73 

Length

Max length4
Median length3
Mean length3.2540984
Min length3

Unique

Unique5 ?
Unique (%)4.1%

Sample

1st row봉담읍
2nd row향남읍
3rd row송산면
4th row병점2동
5th row반월동

Common Values

ValueCountFrequency (%)
향남읍 15
 
12.3%
봉담읍 11
 
9.0%
동탄1동 8
 
6.6%
동탄2동 8
 
6.6%
병점2동 7
 
5.7%
장안면 7
 
5.7%
우정읍 7
 
5.7%
동탄3동 6
 
4.9%
송산면 5
 
4.1%
남양동 4
 
3.3%
Other values (17) 44
36.1%

Length

2023-12-13T07:46:52.072536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
향남읍 15
 
12.3%
봉담읍 11
 
9.0%
동탄1동 8
 
6.6%
동탄2동 8
 
6.6%
병점2동 7
 
5.7%
장안면 7
 
5.7%
우정읍 7
 
5.7%
동탄3동 6
 
4.9%
송산면 5
 
4.1%
정남면 4
 
3.3%
Other values (17) 44
36.1%

개교년월일
Date

Distinct82
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1898-10-01 00:00:00
Maximum2012-11-01 00:00:00
2023-12-13T07:46:52.203548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:46:52.357506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

비고
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing118
Missing (%)96.7%
Memory size1.1 KiB
2023-12-13T07:46:52.474521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3.5
Mean length3.5
Min length3

Characters and Unicode

Total characters14
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row기배동
2nd row동탄1동
3rd row동탄1동
4th row남양동
ValueCountFrequency (%)
동탄1동 2
50.0%
기배동 1
25.0%
남양동 1
25.0%
2023-12-13T07:46:52.667806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 6
42.9%
탄 2
 
14.3%
1 2
 
14.3%
기 1
 
7.1%
배 1
 
7.1%
남 1
 
7.1%
양 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12
85.7%
Decimal Number 2
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6
50.0%
탄 2
 
16.7%
기 1
 
8.3%
배 1
 
8.3%
남 1
 
8.3%
양 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12
85.7%
Common 2
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6
50.0%
탄 2
 
16.7%
기 1
 
8.3%
배 1
 
8.3%
남 1
 
8.3%
양 1
 
8.3%
Common
ValueCountFrequency (%)
1 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12
85.7%
ASCII 2
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 6
50.0%
탄 2
 
16.7%
기 1
 
8.3%
배 1
 
8.3%
남 1
 
8.3%
양 1
 
8.3%
ASCII
ValueCountFrequency (%)
1 2
100.0%

Interactions

2023-12-13T07:46:46.842833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:46:52.741094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No.급별공사립행정동개교년월일비고
No.1.0000.8830.6230.0000.5840.827
급별0.8831.0000.7330.0000.616NaN
공사립0.6230.7331.0000.3320.975NaN
행정동0.0000.0000.3321.0000.9621.000
개교년월일0.5840.6160.9750.9621.0001.000
비고0.827NaNNaN1.0001.0001.000
2023-12-13T07:46:52.837673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사립행정동급별
공사립1.0000.2510.522
행정동0.2511.0000.000
급별0.5220.0001.000
2023-12-13T07:46:52.909948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No.급별공사립행정동
No.1.0000.7310.4660.000
급별0.7311.0000.5220.000
공사립0.4660.5221.0000.251
행정동0.0000.0000.2511.000

Missing values

2023-12-13T07:46:46.942977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:46:47.085783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

No.급별공사립학교명주소교무실행정실FAX행정동개교년월일비고
01초공립갈담초봉담읍 갈담초교길 24031-227-1546031-227-9144031-297-9143봉담읍1949-12-02<NA>
12초공립갈천초향남읍 갈천리 156-1031-352-0510031-352-0516031-352-4940향남읍1961-03-10<NA>
23초공립고정초송산면 공룡로 326031-357-1308031-357-1309031-357-6135송산면1964-10-25<NA>
34초공립구봉초병점2동 862031-225-8328031-225-8329031-225-8544병점2동2004-09-01<NA>
45초공립기산초동탄지성로 344031-224-9013031-224-9014031-224-9024반월동2004-09-15<NA>
56초공립기안초기안길 18031-222-0046031-222-0781031-222-9859기안동1968-03-04기배동
67초공립남양초남양시장로 55번길 7031-356-2014031-356-3576031-356-7289남양동1898-10-01<NA>
78초공립노진초장안면 화곡로 166031-351-2192031-351-2193031-351-7341장안면1971-03-01<NA>
89초공립능동초능동 1085031-613-4205031-613-4206031-613-4221동탄3동2008-03-01<NA>
910초공립대방분교팔탄면 노하리 173-1031-354-8581031-352-8496031-354-5580팔탄면1966-09-02<NA>
No.급별공사립학교명주소교무실행정실FAX행정동개교년월일비고
112113고사립삼괴고우정읍 장안로 35031-831-0600031-831-0700031-358-3809우정읍1960-05-10<NA>
113114고사립송산고송산면 송산포도로 102-21031-357-1116031-357-1117031-355-2558송산면1961-04-08<NA>
114115고사립홍익디자인고기안동 460-97031-8055-3011031-8055-3004031-222-3900기배동1973-03-05<NA>
115116고공립안화고병점동 852031-220-0300031-220-0390031-220-0305병점2동2007-03-01<NA>
116117고공립예당고삼성1로 47031-8055-6300031-8055-6200031-8055-6220동탄3동2008-03-01<NA>
117118고공립향남고향남읍 행정리 행정동로49031-8059-9202031-8059-9301031-8059-1091향남읍2009-03-01<NA>
118119고공립향일고향남읍 행정중앙2로 28031-8077-8600031-8077-8500031-8077-8510향남읍2012-03-01<NA>
119120고사립화성고향남읍 장짐길 4031-350-8311031-350-8303031-352-7811향남읍1979-05-18<NA>
1201214사립한우리학교정남면 관항리 338-6031-354-3089031-352-3090031-352-3091정남면2001-03-01<NA>
1211224사립해원학교장안면 은골길 30번길 43031-351-0806031-351-0805031-351-0807장안면2000-03-01<NA>