Overview

Dataset statistics

Number of variables5
Number of observations106
Missing cells12
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory42.2 B

Variable types

Numeric1
Text4

Dataset

Description경상북도상주교육지원청 관할 학원 및 교습소 현황 정보를 제공하는 서비스로서 학원명, 설립자, 전화번호, 주소를 제공
Author경상북도교육청 경상북도상주교육지원청
URLhttps://www.data.go.kr/data/15053523/fileData.do

Alerts

전화번호 has 11 (10.4%) missing valuesMissing
연번 has unique valuesUnique
학원명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:41:54.818472
Analysis finished2023-12-12 03:41:55.689673
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct106
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.5
Minimum1
Maximum106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T12:41:56.203924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.25
Q127.25
median53.5
Q379.75
95-th percentile100.75
Maximum106
Range105
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation30.743563
Coefficient of variation (CV)0.57464604
Kurtosis-1.2
Mean53.5
Median Absolute Deviation (MAD)26.5
Skewness0
Sum5671
Variance945.16667
MonotonicityStrictly increasing
2023-12-12T12:41:56.399358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
81 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
72 1
 
0.9%
Other values (96) 96
90.6%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%
97 1
0.9%

학원명
Text

UNIQUE 

Distinct106
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T12:41:56.732123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length7.8679245
Min length4

Characters and Unicode

Total characters834
Distinct characters209
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)100.0%

Sample

1st row미술놀이터학원
2nd row원리입시학원
3rd row이창선무용학원
4th row상주자동차중장비학원
5th row엠베스트SE상주학원
ValueCountFrequency (%)
미술놀이터학원 1
 
0.9%
유앤아이영어학원 1
 
0.9%
더쎈수학학원 1
 
0.9%
베스트푸르넷학원 1
 
0.9%
청암학원 1
 
0.9%
앤(n)수학과학학원 1
 
0.9%
본수학학원 1
 
0.9%
독한논술강한수학영어학원 1
 
0.9%
삼성영어중앙학원 1
 
0.9%
힘수학전문학원 1
 
0.9%
Other values (98) 98
90.7%
2023-12-12T12:41:57.235610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 111
 
13.3%
원 104
 
12.5%
스 28
 
3.4%
영 27
 
3.2%
어 23
 
2.8%
상 21
 
2.5%
주 20
 
2.4%
이 17
 
2.0%
리 17
 
2.0%
서 13
 
1.6%
Other values (199) 453
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 811
97.2%
Uppercase Letter 14
 
1.7%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%
Space Separator 2
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 111
 
13.7%
원 104
 
12.8%
스 28
 
3.5%
영 27
 
3.3%
어 23
 
2.8%
상 21
 
2.6%
주 20
 
2.5%
이 17
 
2.1%
리 17
 
2.1%
서 13
 
1.6%
Other values (185) 430
53.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
21.4%
U 2
14.3%
N 2
14.3%
E 1
 
7.1%
Y 1
 
7.1%
D 1
 
7.1%
T 1
 
7.1%
I 1
 
7.1%
O 1
 
7.1%
R 1
 
7.1%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 811
97.2%
Latin 14
 
1.7%
Common 9
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 111
 
13.7%
원 104
 
12.8%
스 28
 
3.5%
영 27
 
3.3%
어 23
 
2.8%
상 21
 
2.6%
주 20
 
2.5%
이 17
 
2.1%
리 17
 
2.1%
서 13
 
1.6%
Other values (185) 430
53.0%
Latin
ValueCountFrequency (%)
S 3
21.4%
U 2
14.3%
N 2
14.3%
E 1
 
7.1%
Y 1
 
7.1%
D 1
 
7.1%
T 1
 
7.1%
I 1
 
7.1%
O 1
 
7.1%
R 1
 
7.1%
Common
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
2
22.2%
2 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 811
97.2%
ASCII 23
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 111
 
13.7%
원 104
 
12.8%
스 28
 
3.5%
영 27
 
3.3%
어 23
 
2.8%
상 21
 
2.6%
주 20
 
2.5%
이 17
 
2.1%
리 17
 
2.1%
서 13
 
1.6%
Other values (185) 430
53.0%
ASCII
ValueCountFrequency (%)
) 3
13.0%
( 3
13.0%
S 3
13.0%
2
8.7%
U 2
8.7%
N 2
8.7%
E 1
 
4.3%
Y 1
 
4.3%
D 1
 
4.3%
T 1
 
4.3%
Other values (4) 4
17.4%

설립자
Text

Distinct102
Distinct (%)97.1%
Missing1
Missing (%)0.9%
Memory size980.0 B
2023-12-12T12:41:57.518590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length3.1619048
Min length2

Characters and Unicode

Total characters332
Distinct characters108
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

Unique99 ?
Unique (%)94.3%

Sample

1st row박은경
2nd row황삼석
3rd row이창선
4th row백길용
5th row정공주
ValueCountFrequency (%)
김경숙 2
 
1.9%
안선희 2
 
1.9%
구미란 2
 
1.9%
강민경 1
 
1.0%
강수민 1
 
1.0%
김민석 1
 
1.0%
김기현 1
 
1.0%
박인숙 1
 
1.0%
남현우 1
 
1.0%
구흥본 1
 
1.0%
Other values (92) 92
87.6%
2023-12-12T12:41:57.995981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 24
 
7.2%
정 20
 
6.0%
영 14
 
4.2%
박 13
 
3.9%
경 9
 
2.7%
미 9
 
2.7%
민 9
 
2.7%
이 8
 
2.4%
주 8
 
2.4%
진 8
 
2.4%
Other values (98) 210
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 323
97.3%
Close Punctuation 4
 
1.2%
Open Punctuation 4
 
1.2%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 24
 
7.4%
정 20
 
6.2%
영 14
 
4.3%
박 13
 
4.0%
경 9
 
2.8%
미 9
 
2.8%
민 9
 
2.8%
이 8
 
2.5%
주 8
 
2.5%
진 8
 
2.5%
Other values (95) 201
62.2%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 323
97.3%
Common 9
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 24
 
7.4%
정 20
 
6.2%
영 14
 
4.3%
박 13
 
4.0%
경 9
 
2.8%
미 9
 
2.8%
민 9
 
2.8%
이 8
 
2.5%
주 8
 
2.5%
진 8
 
2.5%
Other values (95) 201
62.2%
Common
ValueCountFrequency (%)
) 4
44.4%
( 4
44.4%
: 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 323
97.3%
ASCII 9
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 24
 
7.4%
정 20
 
6.2%
영 14
 
4.3%
박 13
 
4.0%
경 9
 
2.8%
미 9
 
2.8%
민 9
 
2.8%
이 8
 
2.5%
주 8
 
2.5%
진 8
 
2.5%
Other values (95) 201
62.2%
ASCII
ValueCountFrequency (%)
) 4
44.4%
( 4
44.4%
: 1
 
11.1%

전화번호
Text

MISSING 

Distinct95
Distinct (%)100.0%
Missing11
Missing (%)10.4%
Memory size980.0 B
2023-12-12T12:41:58.308966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010526
Min length12

Characters and Unicode

Total characters1141
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

Unique95 ?
Unique (%)100.0%

Sample

1st row054-536-1050
2nd row054-541-4706
3rd row054-536-8401
4th row054-536-1191
5th row054-532-0278
ValueCountFrequency (%)
054-536-1050 1
 
1.1%
054-532-3342 1
 
1.1%
054-536-2253 1
 
1.1%
054-536-7756 1
 
1.1%
054-535-7580 1
 
1.1%
070-8102-7931 1
 
1.1%
054-532-4341 1
 
1.1%
054-533-6565 1
 
1.1%
054-534-5815 1
 
1.1%
054-536-0517 1
 
1.1%
Other values (85) 85
89.5%
2023-12-12T12:41:58.707961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 250
21.9%
- 190
16.7%
0 152
13.3%
4 137
12.0%
3 136
11.9%
6 51
 
4.5%
1 51
 
4.5%
2 50
 
4.4%
9 47
 
4.1%
7 47
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 951
83.3%
Dash Punctuation 190
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 250
26.3%
0 152
16.0%
4 137
14.4%
3 136
14.3%
6 51
 
5.4%
1 51
 
5.4%
2 50
 
5.3%
9 47
 
4.9%
7 47
 
4.9%
8 30
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1141
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 250
21.9%
- 190
16.7%
0 152
13.3%
4 137
12.0%
3 136
11.9%
6 51
 
4.5%
1 51
 
4.5%
2 50
 
4.4%
9 47
 
4.1%
7 47
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1141
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 250
21.9%
- 190
16.7%
0 152
13.3%
4 137
12.0%
3 136
11.9%
6 51
 
4.5%
1 51
 
4.5%
2 50
 
4.4%
9 47
 
4.1%
7 47
 
4.1%

주소
Text

Distinct104
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T12:41:59.296724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length42
Mean length27.811321
Min length21

Characters and Unicode

Total characters2948
Distinct characters81
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)96.2%

Sample

1st row경상북도 상주시 동수로 155 (무양동)
2nd row경상북도 상주시 함창읍 함창중앙로 116-1 , 2층 (함창읍)
3rd row경상북도 상주시 동수1길 3, 3층 (무양동)
4th row경상북도 상주시 경상대로 2963 (낙양동)
5th row경상북도 상주시 중앙로 178-28 , 1층 (남성동)
ValueCountFrequency (%)
경상북도 106
15.5%
상주시 106
15.5%
59
 
8.6%
2층 45
 
6.6%
남성동 42
 
6.1%
상산로 28
 
4.1%
3층 13
 
1.9%
무양동 13
 
1.9%
서문동 11
 
1.6%
냉림동 11
 
1.6%
Other values (148) 252
36.7%
2023-12-12T12:41:59.951741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
580
19.7%
상 268
 
9.1%
동 126
 
4.3%
1 109
 
3.7%
경 109
 
3.7%
시 108
 
3.7%
북 108
 
3.7%
( 107
 
3.6%
) 107
 
3.6%
주 106
 
3.6%
Other values (71) 1220
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1564
53.1%
Space Separator 580
 
19.7%
Decimal Number 464
 
15.7%
Open Punctuation 107
 
3.6%
Close Punctuation 107
 
3.6%
Other Punctuation 87
 
3.0%
Dash Punctuation 32
 
1.1%
Math Symbol 5
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 268
17.1%
동 126
 
8.1%
경 109
 
7.0%
시 108
 
6.9%
북 108
 
6.9%
주 106
 
6.8%
도 106
 
6.8%
층 77
 
4.9%
로 58
 
3.7%
성 55
 
3.5%
Other values (53) 443
28.3%
Decimal Number
ValueCountFrequency (%)
1 109
23.5%
2 102
22.0%
3 72
15.5%
5 40
 
8.6%
9 33
 
7.1%
0 28
 
6.0%
4 21
 
4.5%
6 20
 
4.3%
7 20
 
4.3%
8 19
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
580
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Other Punctuation
ValueCountFrequency (%)
, 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1564
53.1%
Common 1382
46.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 268
17.1%
동 126
 
8.1%
경 109
 
7.0%
시 108
 
6.9%
북 108
 
6.9%
주 106
 
6.8%
도 106
 
6.8%
층 77
 
4.9%
로 58
 
3.7%
성 55
 
3.5%
Other values (53) 443
28.3%
Common
ValueCountFrequency (%)
580
42.0%
1 109
 
7.9%
( 107
 
7.7%
) 107
 
7.7%
2 102
 
7.4%
, 87
 
6.3%
3 72
 
5.2%
5 40
 
2.9%
9 33
 
2.4%
- 32
 
2.3%
Other values (6) 113
 
8.2%
Latin
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1564
53.1%
ASCII 1384
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
580
41.9%
1 109
 
7.9%
( 107
 
7.7%
) 107
 
7.7%
2 102
 
7.4%
, 87
 
6.3%
3 72
 
5.2%
5 40
 
2.9%
9 33
 
2.4%
- 32
 
2.3%
Other values (8) 115
 
8.3%
Hangul
ValueCountFrequency (%)
상 268
17.1%
동 126
 
8.1%
경 109
 
7.0%
시 108
 
6.9%
북 108
 
6.9%
주 106
 
6.8%
도 106
 
6.8%
층 77
 
4.9%
로 58
 
3.7%
성 55
 
3.5%
Other values (53) 443
28.3%

Interactions

2023-12-12T12:41:55.204608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:42:00.077745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전화번호
연번1.0001.000
전화번호1.0001.000

Missing values

2023-12-12T12:41:55.372612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:41:55.506973image/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.
2023-12-12T12:41:55.626045image/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

연번학원명설립자전화번호주소
01미술놀이터학원박은경054-536-1050경상북도 상주시 동수로 155 (무양동)
12원리입시학원황삼석054-541-4706경상북도 상주시 함창읍 함창중앙로 116-1 , 2층 (함창읍)
23이창선무용학원이창선054-536-8401경상북도 상주시 동수1길 3, 3층 (무양동)
34상주자동차중장비학원백길용054-536-1191경상북도 상주시 경상대로 2963 (낙양동)
45엠베스트SE상주학원정공주054-532-0278경상북도 상주시 중앙로 178-28 , 1층 (남성동)
56이기업피아노학원이기업054-536-4339경상북도 상주시 상산새싹길 53 , 2층 (냉림동)
67대신학원김미순054-534-4273경상북도 상주시 상서문로 54, 2층 (남성동)
78상주제과제빵학원안선희054-534-2501경상북도 상주시 중앙로 177-9 (서문동)
89부일미용전문학원조기현054-536-5045경상북도 상주시 문무1길 33 , 1층 (무양동)
910상주간호전문학원김택선054-536-3346경상북도 상주시 상산로 351-1 , 3층 (무양동)
연번학원명설립자전화번호주소
9697참영재학원최인희054-534-6805경상북도 상주시 상서문1길 63, 2층 (낙양동)
9798박진영피아노학원박진영054-535-2007경상북도 상주시 왕산로 389 , 2층 (냉림동)
9899남미진음악학원남미진054-531-2431경상북도 상주시 남성2길 3, 2층 (남성동)
99100샬롬피아노학원김경애054-535-6236경상북도 상주시 성동2길 33, 1~2층 (성동동)
100101상주요리학원안선희054-536-1142경상북도 상주시 중앙로 177-9 (서문동)
101102룸비니피아노학원김정순054-535-3977경상북도 상주시 동수1길 72-5, 2층 (무양동)
102103공간미술학원박현숙054-532-2992경상북도 상주시 서문길 131 , 2층 (서문동)
103104효성학원강혜진054-532-0615경상북도 상주시 상서문로 23 (남성동)
104105예인미용학원박명희054-535-1585경상북도 상주시 중앙로 157 , 3층 (남성동)
105106소파서예학원윤대영054-533-5783경상북도 상주시 상산로 145 , 상가204호,208호 (신봉동,동아아파트)