Overview

Dataset statistics

Number of variables4
Number of observations100
Missing cells360
Missing cells (%)90.0%
Duplicate rows1
Duplicate rows (%)1.0%
Total size in memory3.3 KiB
Average record size in memory33.3 B

Variable types

Text3
DateTime1

Dataset

Description인천광역시 서구 피부과의원의 현황에 대한 데이터입니다. 이 데이터는 의원명, 소재지, 전화번호 등에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15086619/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (1.0%) duplicate rowsDuplicates
의원명 has 90 (90.0%) missing valuesMissing
소재지 has 90 (90.0%) missing valuesMissing
전화번호 has 90 (90.0%) missing valuesMissing
데이터기준일자 has 90 (90.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:26:29.979725
Analysis finished2023-12-12 09:26:30.543483
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

의원명
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing90
Missing (%)90.0%
Memory size932.0 B
2023-12-12T18:26:30.683533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length8
Mean length8.9
Min length7

Characters and Unicode

Total characters89
Distinct characters35
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

Unique10 ?
Unique (%)100.0%

Sample

1st row닥터스피부과의원
2nd row오라클피부과의원 인천아라점
3rd row리멤버피부과의원
4th row연세뉴피부과의원
5th row오라클피부과의원
ValueCountFrequency (%)
오라클피부과의원 2
16.7%
닥터스피부과의원 1
8.3%
인천아라점 1
8.3%
리멤버피부과의원 1
8.3%
연세뉴피부과의원 1
8.3%
미엘피부과의원 1
8.3%
서울더본피부과의원 1
8.3%
클린업피부과의원 1
8.3%
이너스피부과의원 1
8.3%
휴먼피부과의원 1
8.3%
2023-12-12T18:26:31.085132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
피 10
 
11.2%
부 10
 
11.2%
과 10
 
11.2%
의 10
 
11.2%
원 10
 
11.2%
라 4
 
4.5%
클 3
 
3.4%
2
 
2.2%
스 2
 
2.2%
오 2
 
2.2%
Other values (25) 26
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87
97.8%
Space Separator 2
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
피 10
11.5%
부 10
11.5%
과 10
11.5%
의 10
11.5%
원 10
11.5%
라 4
 
4.6%
클 3
 
3.4%
스 2
 
2.3%
오 2
 
2.3%
점 2
 
2.3%
Other values (24) 24
27.6%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87
97.8%
Common 2
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
피 10
11.5%
부 10
11.5%
과 10
11.5%
의 10
11.5%
원 10
11.5%
라 4
 
4.6%
클 3
 
3.4%
스 2
 
2.3%
오 2
 
2.3%
점 2
 
2.3%
Other values (24) 24
27.6%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87
97.8%
ASCII 2
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
피 10
11.5%
부 10
11.5%
과 10
11.5%
의 10
11.5%
원 10
11.5%
라 4
 
4.6%
클 3
 
3.4%
스 2
 
2.3%
오 2
 
2.3%
점 2
 
2.3%
Other values (24) 24
27.6%
ASCII
ValueCountFrequency (%)
2
100.0%

소재지
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing90
Missing (%)90.0%
Memory size932.0 B
2023-12-12T18:26:31.383492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40.5
Mean length38.9
Min length26

Characters and Unicode

Total characters389
Distinct characters78
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 이음대로 384, 서영아너시티플러스 604~610호 (원당동)
2nd row인천광역시 서구 이음대로 392, 메트로시티 5층 505~507호 (원당동)
3rd row인천광역시 서구 이음대로 378, 로뎀타워 803~806호 (원당동)
4th row인천광역시 서구 청라커낼로288번길 10, 더스페이스타워 4층 405호 (청라동)
5th row인천광역시 서구 완정로 153, 이레메디칼센타 5층 (왕길동)
ValueCountFrequency (%)
인천광역시 10
 
14.3%
서구 10
 
14.3%
청라동 4
 
5.7%
이음대로 3
 
4.3%
원당동 3
 
4.3%
5층 2
 
2.9%
중봉대로 2
 
2.9%
405,406호 1
 
1.4%
403,404호 1
 
1.4%
신현동 1
 
1.4%
Other values (33) 33
47.1%
2023-12-12T18:26:31.842857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60
 
15.4%
0 18
 
4.6%
4 15
 
3.9%
, 14
 
3.6%
5 13
 
3.3%
시 12
 
3.1%
서 12
 
3.1%
로 12
 
3.1%
3 11
 
2.8%
인 10
 
2.6%
Other values (68) 212
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
52.2%
Decimal Number 86
22.1%
Space Separator 60
 
15.4%
Other Punctuation 14
 
3.6%
Open Punctuation 10
 
2.6%
Close Punctuation 10
 
2.6%
Math Symbol 5
 
1.3%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 12
 
5.9%
서 12
 
5.9%
로 12
 
5.9%
인 10
 
4.9%
동 10
 
4.9%
천 10
 
4.9%
광 10
 
4.9%
역 10
 
4.9%
구 10
 
4.9%
호 8
 
3.9%
Other values (52) 99
48.8%
Decimal Number
ValueCountFrequency (%)
0 18
20.9%
4 15
17.4%
5 13
15.1%
3 11
12.8%
8 8
9.3%
1 6
 
7.0%
6 6
 
7.0%
2 3
 
3.5%
7 3
 
3.5%
9 3
 
3.5%
Space Separator
ValueCountFrequency (%)
60
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 203
52.2%
Common 186
47.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 12
 
5.9%
서 12
 
5.9%
로 12
 
5.9%
인 10
 
4.9%
동 10
 
4.9%
천 10
 
4.9%
광 10
 
4.9%
역 10
 
4.9%
구 10
 
4.9%
호 8
 
3.9%
Other values (52) 99
48.8%
Common
ValueCountFrequency (%)
60
32.3%
0 18
 
9.7%
4 15
 
8.1%
, 14
 
7.5%
5 13
 
7.0%
3 11
 
5.9%
( 10
 
5.4%
) 10
 
5.4%
8 8
 
4.3%
1 6
 
3.2%
Other values (6) 21
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
52.2%
ASCII 186
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60
32.3%
0 18
 
9.7%
4 15
 
8.1%
, 14
 
7.5%
5 13
 
7.0%
3 11
 
5.9%
( 10
 
5.4%
) 10
 
5.4%
8 8
 
4.3%
1 6
 
3.2%
Other values (6) 21
 
11.3%
Hangul
ValueCountFrequency (%)
시 12
 
5.9%
서 12
 
5.9%
로 12
 
5.9%
인 10
 
4.9%
동 10
 
4.9%
천 10
 
4.9%
광 10
 
4.9%
역 10
 
4.9%
구 10
 
4.9%
호 8
 
3.9%
Other values (52) 99
48.8%

전화번호
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing90
Missing (%)90.0%
Memory size932.0 B
2023-12-12T18:26:32.055314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters120
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

Unique10 ?
Unique (%)100.0%

Sample

1st row032-279-1004
2nd row032-566-5595
3rd row032-710-7574
4th row032-562-0712
5th row032-566-4114
ValueCountFrequency (%)
032-279-1004 1
10.0%
032-566-5595 1
10.0%
032-710-7574 1
10.0%
032-562-0712 1
10.0%
032-566-4114 1
10.0%
032-572-7111 1
10.0%
032-710-0075 1
10.0%
032-569-7590 1
10.0%
032-262-1777 1
10.0%
032-283-3335 1
10.0%
2023-12-12T18:26:32.433673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 20
16.7%
0 18
15.0%
2 17
14.2%
3 14
11.7%
7 13
10.8%
5 12
10.0%
1 10
8.3%
6 7
 
5.8%
9 4
 
3.3%
4 4
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100
83.3%
Dash Punctuation 20
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
18.0%
2 17
17.0%
3 14
14.0%
7 13
13.0%
5 12
12.0%
1 10
10.0%
6 7
 
7.0%
9 4
 
4.0%
4 4
 
4.0%
8 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 20
16.7%
0 18
15.0%
2 17
14.2%
3 14
11.7%
7 13
10.8%
5 12
10.0%
1 10
8.3%
6 7
 
5.8%
9 4
 
3.3%
4 4
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 20
16.7%
0 18
15.0%
2 17
14.2%
3 14
11.7%
7 13
10.8%
5 12
10.0%
1 10
8.3%
6 7
 
5.8%
9 4
 
3.3%
4 4
 
3.3%

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)10.0%
Missing90
Missing (%)90.0%
Memory size932.0 B
Minimum2023-08-01 00:00:00
Maximum2023-08-01 00:00:00
2023-12-12T18:26:32.575391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:32.676253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T18:26:33.066471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의원명소재지전화번호
의원명1.0001.0001.000
소재지1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2023-12-12T18:26:30.224470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:26:30.334563image/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.
2023-12-12T18:26:30.453001image/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

의원명소재지전화번호데이터기준일자
0닥터스피부과의원인천광역시 서구 이음대로 384, 서영아너시티플러스 604~610호 (원당동)032-279-10042023-08-01
1오라클피부과의원 인천아라점인천광역시 서구 이음대로 392, 메트로시티 5층 505~507호 (원당동)032-566-55952023-08-01
2리멤버피부과의원인천광역시 서구 이음대로 378, 로뎀타워 803~806호 (원당동)032-710-75742023-08-01
3연세뉴피부과의원인천광역시 서구 청라커낼로288번길 10, 더스페이스타워 4층 405호 (청라동)032-562-07122023-08-01
4오라클피부과의원인천광역시 서구 완정로 153, 이레메디칼센타 5층 (왕길동)032-566-41142023-08-01
5미엘피부과의원인천광역시 서구 가정로 375, 403,404호 (신현동, 금강아미움)032-572-71112023-08-01
6서울더본피부과의원인천광역시 서구 중봉대로586번길 9-4, 쓰리엠타워 405,406호 (청라동)032-710-00752023-08-01
7클린업피부과의원인천광역시 서구 중봉대로 610, 403~405호 (청라동)032-569-75902023-08-01
8이너스피부과의원인천광역시 서구 서곶로 281, 3층 (심곡동)032-262-17772023-08-01
9휴먼피부과의원 청라점인천광역시 서구 중봉대로 594, 청라비전프라자 303,401~405호 (청라동)032-283-33352023-08-01
의원명소재지전화번호데이터기준일자
90<NA><NA><NA><NA>
91<NA><NA><NA><NA>
92<NA><NA><NA><NA>
93<NA><NA><NA><NA>
94<NA><NA><NA><NA>
95<NA><NA><NA><NA>
96<NA><NA><NA><NA>
97<NA><NA><NA><NA>
98<NA><NA><NA><NA>
99<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

의원명소재지전화번호데이터기준일자# duplicates
0<NA><NA><NA><NA>90