Overview

Dataset statistics

Number of variables3
Number of observations43
Missing cells7
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory27.1 B

Variable types

Text3

Dataset

Description서울특별시 관악구 치과기공소 현황(서울특별시 관악구 치과 기공소명, 치과기공소 소재지도로명 주소, 치과기공소 전화번호 등)
URLhttps://www.data.go.kr/data/15048012/fileData.do

Alerts

전화번호 has 7 (16.3%) missing valuesMissing
치과기공소명 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:15:05.310153
Analysis finished2023-12-12 12:15:05.650735
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

치과기공소명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T21:15:05.860856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length8.4651163
Min length6

Characters and Unicode

Total characters364
Distinct characters100
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

Unique43 ?
Unique (%)100.0%

Sample

1st rowD2(디투)치과기공소
2nd rowE&E치과기공소
3rd rowE-plus 치과기공소
4th row고은치과기공소
5th row구구치과기공소
ValueCountFrequency (%)
d2(디투)치과기공소 1
 
2.3%
란치과기공소 1
 
2.3%
지엘치과기공소 1
 
2.3%
엠앤에프밀링센타(주)치과기공소 1
 
2.3%
열린치과기공소 1
 
2.3%
웰덴치과기공소 1
 
2.3%
유노이아치과기공소 1
 
2.3%
유앤아이치과기공소 1
 
2.3%
정성치과기공소 1
 
2.3%
제이디치과기공소 1
 
2.3%
Other values (34) 34
77.3%
2023-12-12T21:15:06.323853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
 
11.8%
43
 
11.8%
43
 
11.8%
43
 
11.8%
43
 
11.8%
10
 
2.7%
8
 
2.2%
5
 
1.4%
5
 
1.4%
( 4
 
1.1%
Other values (90) 117
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 339
93.1%
Uppercase Letter 8
 
2.2%
Open Punctuation 4
 
1.1%
Close Punctuation 4
 
1.1%
Lowercase Letter 4
 
1.1%
Other Punctuation 2
 
0.5%
Space Separator 1
 
0.3%
Dash Punctuation 1
 
0.3%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
43
12.7%
43
12.7%
43
12.7%
43
12.7%
43
12.7%
10
 
2.9%
8
 
2.4%
5
 
1.5%
5
 
1.5%
4
 
1.2%
Other values (74) 92
27.1%
Uppercase Letter
ValueCountFrequency (%)
E 3
37.5%
C 1
 
12.5%
D 1
 
12.5%
L 1
 
12.5%
A 1
 
12.5%
V 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
s 1
25.0%
u 1
25.0%
l 1
25.0%
p 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 339
93.1%
Common 13
 
3.6%
Latin 12
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
43
12.7%
43
12.7%
43
12.7%
43
12.7%
43
12.7%
10
 
2.9%
8
 
2.4%
5
 
1.5%
5
 
1.5%
4
 
1.2%
Other values (74) 92
27.1%
Latin
ValueCountFrequency (%)
E 3
25.0%
C 1
 
8.3%
D 1
 
8.3%
L 1
 
8.3%
s 1
 
8.3%
u 1
 
8.3%
l 1
 
8.3%
p 1
 
8.3%
A 1
 
8.3%
V 1
 
8.3%
Common
ValueCountFrequency (%)
( 4
30.8%
) 4
30.8%
& 2
15.4%
1
 
7.7%
- 1
 
7.7%
2 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 339
93.1%
ASCII 25
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
43
12.7%
43
12.7%
43
12.7%
43
12.7%
43
12.7%
10
 
2.9%
8
 
2.4%
5
 
1.5%
5
 
1.5%
4
 
1.2%
Other values (74) 92
27.1%
ASCII
ValueCountFrequency (%)
( 4
16.0%
) 4
16.0%
E 3
12.0%
& 2
 
8.0%
C 1
 
4.0%
D 1
 
4.0%
L 1
 
4.0%
1
 
4.0%
s 1
 
4.0%
u 1
 
4.0%
Other values (6) 6
24.0%

도로명주소
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T21:15:06.660521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length34
Mean length28.27907
Min length22

Characters and Unicode

Total characters1216
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row서울특별시 관악구 조원로16길 33, 중앙빌딩 3층 (신림동)
2nd row서울특별시 관악구 문성로 214 (신림동, 성부빌딩)
3rd row서울특별시 관악구 봉천로 408, 동광빌딩 2층 (봉천동)
4th row서울특별시 관악구 봉천로 325, 3층 (봉천동)
5th row서울특별시 관악구 남부순환로172길 120 (신림동)
ValueCountFrequency (%)
서울특별시 43
17.1%
관악구 43
17.1%
봉천동 25
 
9.9%
봉천로 14
 
5.6%
신림동 13
 
5.2%
2층 8
 
3.2%
3층 8
 
3.2%
4층 7
 
2.8%
남부순환로 6
 
2.4%
관악로 3
 
1.2%
Other values (72) 82
32.5%
2023-12-12T21:15:07.103970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
211
 
17.4%
48
 
3.9%
47
 
3.9%
46
 
3.8%
44
 
3.6%
44
 
3.6%
43
 
3.5%
) 43
 
3.5%
43
 
3.5%
43
 
3.5%
Other values (58) 604
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 698
57.4%
Space Separator 211
 
17.4%
Decimal Number 186
 
15.3%
Close Punctuation 43
 
3.5%
Open Punctuation 43
 
3.5%
Other Punctuation 31
 
2.5%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
48
 
6.9%
47
 
6.7%
46
 
6.6%
44
 
6.3%
44
 
6.3%
43
 
6.2%
43
 
6.2%
43
 
6.2%
43
 
6.2%
43
 
6.2%
Other values (43) 254
36.4%
Decimal Number
ValueCountFrequency (%)
2 38
20.4%
3 34
18.3%
1 29
15.6%
4 23
12.4%
0 19
10.2%
5 15
 
8.1%
9 8
 
4.3%
7 8
 
4.3%
8 8
 
4.3%
6 4
 
2.2%
Space Separator
ValueCountFrequency (%)
211
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 698
57.4%
Common 518
42.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
48
 
6.9%
47
 
6.7%
46
 
6.6%
44
 
6.3%
44
 
6.3%
43
 
6.2%
43
 
6.2%
43
 
6.2%
43
 
6.2%
43
 
6.2%
Other values (43) 254
36.4%
Common
ValueCountFrequency (%)
211
40.7%
) 43
 
8.3%
( 43
 
8.3%
2 38
 
7.3%
3 34
 
6.6%
, 31
 
6.0%
1 29
 
5.6%
4 23
 
4.4%
0 19
 
3.7%
5 15
 
2.9%
Other values (5) 32
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 698
57.4%
ASCII 518
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
40.7%
) 43
 
8.3%
( 43
 
8.3%
2 38
 
7.3%
3 34
 
6.6%
, 31
 
6.0%
1 29
 
5.6%
4 23
 
4.4%
0 19
 
3.7%
5 15
 
2.9%
Other values (5) 32
 
6.2%
Hangul
ValueCountFrequency (%)
48
 
6.9%
47
 
6.7%
46
 
6.6%
44
 
6.3%
44
 
6.3%
43
 
6.2%
43
 
6.2%
43
 
6.2%
43
 
6.2%
43
 
6.2%
Other values (43) 254
36.4%

전화번호
Text

MISSING 

Distinct36
Distinct (%)100.0%
Missing7
Missing (%)16.3%
Memory size476.0 B
2023-12-12T21:15:07.360454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12.5
Mean length9.5
Min length8

Characters and Unicode

Total characters342
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

Unique36 ?
Unique (%)100.0%

Sample

1st row02-884-2281
2nd row02-3281-7218
3rd row879-1792
4th row874-4785
5th row879-2288
ValueCountFrequency (%)
02-884-2281 1
 
2.8%
02-3281-7218 1
 
2.8%
02-326-2833 1
 
2.8%
857-2804 1
 
2.8%
577-5667 1
 
2.8%
856-2804 1
 
2.8%
822-2848 1
 
2.8%
425-2804 1
 
2.8%
02-888-2804 1
 
2.8%
859-1822 1
 
2.8%
Other values (26) 26
72.2%
2023-12-12T21:15:07.929232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 70
20.5%
2 68
19.9%
- 52
15.2%
0 40
11.7%
7 27
 
7.9%
4 23
 
6.7%
5 14
 
4.1%
6 14
 
4.1%
3 13
 
3.8%
9 12
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
84.8%
Dash Punctuation 52
 
15.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 70
24.1%
2 68
23.4%
0 40
13.8%
7 27
 
9.3%
4 23
 
7.9%
5 14
 
4.8%
6 14
 
4.8%
3 13
 
4.5%
9 12
 
4.1%
1 9
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 342
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 70
20.5%
2 68
19.9%
- 52
15.2%
0 40
11.7%
7 27
 
7.9%
4 23
 
6.7%
5 14
 
4.1%
6 14
 
4.1%
3 13
 
3.8%
9 12
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 342
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 70
20.5%
2 68
19.9%
- 52
15.2%
0 40
11.7%
7 27
 
7.9%
4 23
 
6.7%
5 14
 
4.1%
6 14
 
4.1%
3 13
 
3.8%
9 12
 
3.5%

Correlations

2023-12-12T21:15:08.064795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
치과기공소명도로명주소전화번호
치과기공소명1.0001.0001.000
도로명주소1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2023-12-12T21:15:05.529080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:15:05.616439image/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

치과기공소명도로명주소전화번호
0D2(디투)치과기공소서울특별시 관악구 조원로16길 33, 중앙빌딩 3층 (신림동)<NA>
1E&E치과기공소서울특별시 관악구 문성로 214 (신림동, 성부빌딩)<NA>
2E-plus 치과기공소서울특별시 관악구 봉천로 408, 동광빌딩 2층 (봉천동)02-884-2281
3고은치과기공소서울특별시 관악구 봉천로 325, 3층 (봉천동)<NA>
4구구치과기공소서울특별시 관악구 남부순환로172길 120 (신림동)02-3281-7218
5굿스마일치과기공소서울특별시 관악구 솔밭로 1 (봉천동,5층)879-1792
6나남치과기공소서울특별시 관악구 봉천로 449-1 (봉천동)874-4785
7뉴베스트치과기공소서울특별시 관악구 봉천로 522 (봉천동,3층)879-2288
8동아치과기공소서울특별시 관악구 관악로 237, 4층 (봉천동)887-7204
9동원치과기공소서울특별시 관악구 보라매로 43, 4층 우측호 (봉천동)825-2808
치과기공소명도로명주소전화번호
33지엘치과기공소서울특별시 관악구 은천로 170(봉천동)<NA>
34초이스교정치과기공소서울특별시 관악구 봉천로 449, 2층 (봉천동)887-7220
35초이스치과기공소서울특별시 관악구 봉천로 523 (봉천동, 궁안빌딩)02-872-2204
36최강치과기공소서울특별시 관악구 은천로 146 (봉천동)6404-2803
37티엠제이치과기공소서울특별시 관악구 남부순환로 1710, 3층 (봉천동)884-5892
38퍼스트치과기공소서울특별시 관악구 은천로6길 8, 2층 (봉천동)02-753-0602
39한국치과기공소서울특별시 관악구 봉천로 408 (봉천동)<NA>
40한플러스치과기공소서울특별시 관악구 문성로 246 (신림동, 4층)3281-2804
41행복치과기공소서울특별시 관악구 봉천로 309 (봉천동, 4층)876-2804
42현치과기공소서울특별시 관악구 관천로 37 (신림동)02-867-0428