Overview

Dataset statistics

Number of variables14
Number of observations31
Missing cells12
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory116.3 B

Variable types

Text8
Categorical2
Boolean2
DateTime2

Dataset

Description이 데이터는 서울특별시 동작구에 있는 사회적 기업에 관한 것입니다. 이 데이터에는 기관명, 서비스 분야, 사업 내용이 포함되어 있습니다.
Author서울특별시 동작구
URLhttps://www.data.go.kr/data/15008837/fileData.do

Alerts

인증지정여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
전화번호 has 8 (25.8%) missing valuesMissing
홈페이지주소 has 4 (12.9%) missing valuesMissing
기관명 has unique valuesUnique
사업내용 has unique valuesUnique
인증지정번호 has unique valuesUnique
대표자명 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:00:21.836893
Analysis finished2024-04-21 01:00:24.229853
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-21T10:00:24.359089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.7419355
Min length4

Characters and Unicode

Total characters271
Distinct characters124
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row(사)한국시니어협회
2nd row삼성떡프린스
3rd row㈜희망하우징
4th row㈜정인애드
5th row㈜케이앤아츠
ValueCountFrequency (%)
주식회사 4
 
9.3%
협동조합 3
 
7.0%
사회적협동조합 2
 
4.7%
사)한국시니어협회 1
 
2.3%
㈜로열코칭 1
 
2.3%
성문화연구소 1
 
2.3%
라라 1
 
2.3%
원케어휴㈜ 1
 
2.3%
꿈꾸는도토리 1
 
2.3%
사단법인 1
 
2.3%
Other values (27) 27
62.8%
2024-04-21T10:00:24.677548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 16
 
5.9%
13
 
4.8%
사 12
 
4.4%
협 9
 
3.3%
회 9
 
3.3%
동 8
 
3.0%
스 8
 
3.0%
합 7
 
2.6%
조 7
 
2.6%
아 6
 
2.2%
Other values (114) 176
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
87.8%
Other Symbol 16
 
5.9%
Space Separator 13
 
4.8%
Open Punctuation 2
 
0.7%
Close Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 12
 
5.0%
협 9
 
3.8%
회 9
 
3.8%
동 8
 
3.4%
스 8
 
3.4%
합 7
 
2.9%
조 7
 
2.9%
아 6
 
2.5%
식 5
 
2.1%
주 5
 
2.1%
Other values (110) 162
68.1%
Other Symbol
ValueCountFrequency (%)
㈜ 16
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
93.7%
Common 17
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 16
 
6.3%
사 12
 
4.7%
협 9
 
3.5%
회 9
 
3.5%
동 8
 
3.1%
스 8
 
3.1%
합 7
 
2.8%
조 7
 
2.8%
아 6
 
2.4%
식 5
 
2.0%
Other values (111) 167
65.7%
Common
ValueCountFrequency (%)
13
76.5%
( 2
 
11.8%
) 2
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
87.8%
ASCII 17
 
6.3%
None 16
 
5.9%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 16
100.0%
ASCII
ValueCountFrequency (%)
13
76.5%
( 2
 
11.8%
) 2
 
11.8%
Hangul
ValueCountFrequency (%)
사 12
 
5.0%
협 9
 
3.8%
회 9
 
3.8%
동 8
 
3.4%
스 8
 
3.4%
합 7
 
2.9%
조 7
 
2.9%
아 6
 
2.5%
식 5
 
2.1%
주 5
 
2.1%
Other values (110) 162
68.1%

사회서비스분야
Text

Distinct16
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-21T10:00:24.841619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length12
Min length2

Characters and Unicode

Total characters372
Distinct characters60
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

Unique9 ?
Unique (%)29.0%

Sample

1st row보건업 및 사회복지서비스업
2nd row숙박 및 음식점업
3rd row건설업
4th row인쇄업
5th row예술, 스포츠 및 여가관련 서비스업
ValueCountFrequency (%)
및 20
20.0%
서비스업 12
 
12.0%
교육서비스업 6
 
6.0%
예술 6
 
6.0%
스포츠 6
 
6.0%
여가관련 6
 
6.0%
출판 3
 
3.0%
영상 3
 
3.0%
방송통신 3
 
3.0%
정보 3
 
3.0%
Other values (21) 32
32.0%
2024-04-21T10:00:25.108914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
18.8%
업 33
 
8.9%
스 28
 
7.5%
서 22
 
5.9%
비 22
 
5.9%
및 20
 
5.4%
, 14
 
3.8%
술 8
 
2.2%
육 7
 
1.9%
교 7
 
1.9%
Other values (50) 141
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 285
76.6%
Space Separator 70
 
18.8%
Other Punctuation 14
 
3.8%
Open Punctuation 1
 
0.3%
Uppercase Letter 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 33
 
11.6%
스 28
 
9.8%
서 22
 
7.7%
비 22
 
7.7%
및 20
 
7.0%
술 8
 
2.8%
육 7
 
2.5%
교 7
 
2.5%
포 6
 
2.1%
츠 6
 
2.1%
Other values (45) 126
44.2%
Space Separator
ValueCountFrequency (%)
70
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 285
76.6%
Common 86
 
23.1%
Latin 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 33
 
11.6%
스 28
 
9.8%
서 22
 
7.7%
비 22
 
7.7%
및 20
 
7.0%
술 8
 
2.8%
육 7
 
2.5%
교 7
 
2.5%
포 6
 
2.1%
츠 6
 
2.1%
Other values (45) 126
44.2%
Common
ValueCountFrequency (%)
70
81.4%
, 14
 
16.3%
( 1
 
1.2%
) 1
 
1.2%
Latin
ValueCountFrequency (%)
R 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 285
76.6%
ASCII 87
 
23.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
80.5%
, 14
 
16.1%
( 1
 
1.1%
R 1
 
1.1%
) 1
 
1.1%
Hangul
ValueCountFrequency (%)
업 33
 
11.6%
스 28
 
9.8%
서 22
 
7.7%
비 22
 
7.7%
및 20
 
7.0%
술 8
 
2.8%
육 7
 
2.5%
교 7
 
2.5%
포 6
 
2.1%
츠 6
 
2.1%
Other values (45) 126
44.2%

주된목적
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
창의혁신형
10 
일자리제공형
9 
사회서비스제공형
8 
혼합형
4 

Length

Max length8
Median length6
Mean length5.8064516
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row혼합형
2nd row일자리제공형
3rd row사회서비스제공형
4th row일자리제공형
5th row일자리제공형

Common Values

ValueCountFrequency (%)
창의혁신형 10
32.3%
일자리제공형 9
29.0%
사회서비스제공형 8
25.8%
혼합형 4
 
12.9%

Length

2024-04-21T10:00:25.233362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:00:25.341925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창의혁신형 10
32.3%
일자리제공형 9
29.0%
사회서비스제공형 8
25.8%
혼합형 4
 
12.9%

사업내용
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-21T10:00:25.565541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length19
Mean length15.451613
Min length5

Characters and Unicode

Total characters479
Distinct characters155
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row노인돌봄서비스,재가방문요양
2nd row전통, 퓨전떡 제작 및 판매
3rd row집수리,리모델링,인테리어
4th row기획디자인, 옵셋, 마스타인쇄, 임대
5th row예술, 교육
ValueCountFrequency (%)
및 10
 
8.8%
제작 5
 
4.4%
교육 5
 
4.4%
사업 3
 
2.6%
예술 3
 
2.6%
서비스 3
 
2.6%
환경 2
 
1.8%
콘텐츠 2
 
1.8%
개발 2
 
1.8%
노인돌봄서비스,재가방문요양 1
 
0.9%
Other values (78) 78
68.4%
2024-04-21T10:00:25.906129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
17.5%
, 21
 
4.4%
교 15
 
3.1%
육 14
 
2.9%
인 13
 
2.7%
스 11
 
2.3%
및 10
 
2.1%
비 10
 
2.1%
예 9
 
1.9%
술 9
 
1.9%
Other values (145) 283
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 371
77.5%
Space Separator 84
 
17.5%
Other Punctuation 22
 
4.6%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 15
 
4.0%
육 14
 
3.8%
인 13
 
3.5%
스 11
 
3.0%
및 10
 
2.7%
비 10
 
2.7%
예 9
 
2.4%
술 9
 
2.4%
서 9
 
2.4%
사 9
 
2.4%
Other values (140) 262
70.6%
Other Punctuation
ValueCountFrequency (%)
, 21
95.5%
· 1
 
4.5%
Space Separator
ValueCountFrequency (%)
84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 371
77.5%
Common 108
 
22.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 15
 
4.0%
육 14
 
3.8%
인 13
 
3.5%
스 11
 
3.0%
및 10
 
2.7%
비 10
 
2.7%
예 9
 
2.4%
술 9
 
2.4%
서 9
 
2.4%
사 9
 
2.4%
Other values (140) 262
70.6%
Common
ValueCountFrequency (%)
84
77.8%
, 21
 
19.4%
( 1
 
0.9%
· 1
 
0.9%
) 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 371
77.5%
ASCII 107
 
22.3%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
78.5%
, 21
 
19.6%
( 1
 
0.9%
) 1
 
0.9%
Hangul
ValueCountFrequency (%)
교 15
 
4.0%
육 14
 
3.8%
인 13
 
3.5%
스 11
 
3.0%
및 10
 
2.7%
비 10
 
2.7%
예 9
 
2.4%
술 9
 
2.4%
서 9
 
2.4%
사 9
 
2.4%
Other values (140) 262
70.6%
None
ValueCountFrequency (%)
· 1
100.0%

인증지정여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size163.0 B
True
31 
ValueCountFrequency (%)
True 31
100.0%
2024-04-21T10:00:26.031284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

예비형태
Boolean

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size163.0 B
True
16 
False
15 
ValueCountFrequency (%)
True 16
51.6%
False 15
48.4%
2024-04-21T10:00:26.116607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

부처형태
Categorical

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
N
22 
8
3 
0
3 
9
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)9.7%

Sample

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

Common Values

ValueCountFrequency (%)
N 22
71.0%
8 3
 
9.7%
0 3
 
9.7%
9 1
 
3.2%
3 1
 
3.2%
5 1
 
3.2%

Length

2024-04-21T10:00:26.221997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:00:26.314432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 22
71.0%
8 3
 
9.7%
0 3
 
9.7%
9 1
 
3.2%
3 1
 
3.2%
5 1
 
3.2%

인증지정일자
Date

Distinct25
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2008-12-30 00:00:00
Maximum2023-11-04 00:00:00
2024-04-21T10:00:26.407014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:00:26.510276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

인증지정번호
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-21T10:00:26.688323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.1935484
Min length9

Characters and Unicode

Total characters285
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row제2008-113호
2nd row제2011-123호
3rd row제2012-44호
4th row제2016-131호
5th row제2018-22호
ValueCountFrequency (%)
제2008-113호 1
 
3.2%
제2021-13호 1
 
3.2%
제2023-25호 1
 
3.2%
제2023-09호 1
 
3.2%
제2023-08호 1
 
3.2%
제2022-87호 1
 
3.2%
제2022-22호 1
 
3.2%
제2022-33호 1
 
3.2%
제2022-15호 1
 
3.2%
제2022-03호 1
 
3.2%
Other values (21) 21
67.7%
2024-04-21T10:00:26.990123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 74
26.0%
0 42
14.7%
제 31
10.9%
- 31
10.9%
호 31
10.9%
1 28
 
9.8%
3 14
 
4.9%
8 9
 
3.2%
9 7
 
2.5%
5 6
 
2.1%
Other values (3) 12
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 192
67.4%
Other Letter 62
 
21.8%
Dash Punctuation 31
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 74
38.5%
0 42
21.9%
1 28
 
14.6%
3 14
 
7.3%
8 9
 
4.7%
9 7
 
3.6%
5 6
 
3.1%
6 5
 
2.6%
4 4
 
2.1%
7 3
 
1.6%
Other Letter
ValueCountFrequency (%)
제 31
50.0%
호 31
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 223
78.2%
Hangul 62
 
21.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 74
33.2%
0 42
18.8%
- 31
13.9%
1 28
 
12.6%
3 14
 
6.3%
8 9
 
4.0%
9 7
 
3.1%
5 6
 
2.7%
6 5
 
2.2%
4 4
 
1.8%
Hangul
ValueCountFrequency (%)
제 31
50.0%
호 31
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 223
78.2%
Hangul 62
 
21.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 74
33.2%
0 42
18.8%
- 31
13.9%
1 28
 
12.6%
3 14
 
6.3%
8 9
 
4.0%
9 7
 
3.1%
5 6
 
2.7%
6 5
 
2.2%
4 4
 
1.8%
Hangul
ValueCountFrequency (%)
제 31
50.0%
호 31
50.0%

대표자명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-21T10:00:27.182332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0967742
Min length3

Characters and Unicode

Total characters96
Distinct characters42
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

Unique31 ?
Unique (%)100.0%

Sample

1st row신*희
2nd row최*태
3rd row강*경
4th row조*현
5th row김*범
ValueCountFrequency (%)
신*희 1
 
3.2%
김*영 1
 
3.2%
채*훈 1
 
3.2%
안*영 1
 
3.2%
박*미 1
 
3.2%
김*솜 1
 
3.2%
서*라 1
 
3.2%
김*형 1
 
3.2%
조*민 1
 
3.2%
구*영 1
 
3.2%
Other values (21) 21
67.7%
2024-04-21T10:00:27.476866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 32
33.3%
김 9
 
9.4%
영 4
 
4.2%
이 4
 
4.2%
훈 2
 
2.1%
석 2
 
2.1%
형 2
 
2.1%
민 2
 
2.1%
범 2
 
2.1%
송 2
 
2.1%
Other values (32) 35
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
65.6%
Other Punctuation 33
34.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 9
 
14.3%
영 4
 
6.3%
이 4
 
6.3%
훈 2
 
3.2%
석 2
 
3.2%
형 2
 
3.2%
민 2
 
3.2%
범 2
 
3.2%
송 2
 
3.2%
조 2
 
3.2%
Other values (30) 32
50.8%
Other Punctuation
ValueCountFrequency (%)
* 32
97.0%
, 1
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63
65.6%
Common 33
34.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 9
 
14.3%
영 4
 
6.3%
이 4
 
6.3%
훈 2
 
3.2%
석 2
 
3.2%
형 2
 
3.2%
민 2
 
3.2%
범 2
 
3.2%
송 2
 
3.2%
조 2
 
3.2%
Other values (30) 32
50.8%
Common
ValueCountFrequency (%)
* 32
97.0%
, 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
65.6%
ASCII 33
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 32
97.0%
, 1
 
3.0%
Hangul
ValueCountFrequency (%)
김 9
 
14.3%
영 4
 
6.3%
이 4
 
6.3%
훈 2
 
3.2%
석 2
 
3.2%
형 2
 
3.2%
민 2
 
3.2%
범 2
 
3.2%
송 2
 
3.2%
조 2
 
3.2%
Other values (30) 32
50.8%

전화번호
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing8
Missing (%)25.8%
Memory size380.0 B
2024-04-21T10:00:27.653702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length12
Min length11

Characters and Unicode

Total characters276
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

Unique23 ?
Unique (%)100.0%

Sample

1st row02-815-1922
2nd row02-823-2230
3rd row02-2069-3636
4th row02-3486-6791
5th row070-8278-6984
ValueCountFrequency (%)
02-815-1922 1
 
4.3%
070-4035-3318 1
 
4.3%
02-814-3900 1
 
4.3%
070-8648-1616 1
 
4.3%
02-533-4863 1
 
4.3%
0507-1312-9324 1
 
4.3%
02-815-7803 1
 
4.3%
070-4842-2514 1
 
4.3%
02-3442-6800 1
 
4.3%
02-717-4336 1
 
4.3%
Other values (13) 13
56.5%
2024-04-21T10:00:27.944118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 46
16.7%
0 45
16.3%
2 35
12.7%
3 24
8.7%
7 24
8.7%
8 22
8.0%
4 22
8.0%
6 19
6.9%
1 17
 
6.2%
9 12
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
83.3%
Dash Punctuation 46
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
19.6%
2 35
15.2%
3 24
10.4%
7 24
10.4%
8 22
9.6%
4 22
9.6%
6 19
8.3%
1 17
 
7.4%
9 12
 
5.2%
5 10
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 46
16.7%
0 45
16.3%
2 35
12.7%
3 24
8.7%
7 24
8.7%
8 22
8.0%
4 22
8.0%
6 19
6.9%
1 17
 
6.2%
9 12
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 46
16.7%
0 45
16.3%
2 35
12.7%
3 24
8.7%
7 24
8.7%
8 22
8.0%
4 22
8.0%
6 19
6.9%
1 17
 
6.2%
9 12
 
4.3%

소재지도로명주소
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-21T10:00:28.170828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length29
Mean length25.903226
Min length18

Characters and Unicode

Total characters803
Distinct characters89
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

Unique28 ?
Unique (%)90.3%

Sample

1st row서울특별시 동작구 상도로30길 8 (상도동)
2nd row서울특별시 동작구 양녕로30길 19-4 (상도동)
3rd row서울특별시 동작구 여의대방로 44길 47 (대방동, 주공아파트)
4th row서울특별시 동작구 동작대로33길 28(사당동)
5th row서울특별시 동작구 장승배기로10길49, 401호
ValueCountFrequency (%)
서울특별시 31
19.1%
동작구 31
19.1%
상도로 7
 
4.3%
노량진로 6
 
3.7%
190 3
 
1.9%
1층 3
 
1.9%
35 3
 
1.9%
208호 2
 
1.2%
상도동 2
 
1.2%
369 2
 
1.2%
Other values (71) 72
44.4%
2024-04-21T10:00:28.494883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
 
16.4%
동 41
 
5.1%
서 34
 
4.2%
작 33
 
4.1%
울 33
 
4.1%
시 32
 
4.0%
별 31
 
3.9%
특 31
 
3.9%
구 31
 
3.9%
로 30
 
3.7%
Other values (79) 375
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 483
60.1%
Decimal Number 151
 
18.8%
Space Separator 132
 
16.4%
Other Punctuation 21
 
2.6%
Open Punctuation 7
 
0.9%
Close Punctuation 7
 
0.9%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 41
 
8.5%
서 34
 
7.0%
작 33
 
6.8%
울 33
 
6.8%
시 32
 
6.6%
별 31
 
6.4%
특 31
 
6.4%
구 31
 
6.4%
로 30
 
6.2%
호 15
 
3.1%
Other values (63) 172
35.6%
Decimal Number
ValueCountFrequency (%)
0 28
18.5%
1 25
16.6%
3 20
13.2%
4 19
12.6%
2 15
9.9%
8 11
 
7.3%
6 10
 
6.6%
5 10
 
6.6%
9 9
 
6.0%
7 4
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 20
95.2%
. 1
 
4.8%
Space Separator
ValueCountFrequency (%)
132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
60.1%
Common 320
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 41
 
8.5%
서 34
 
7.0%
작 33
 
6.8%
울 33
 
6.8%
시 32
 
6.6%
별 31
 
6.4%
특 31
 
6.4%
구 31
 
6.4%
로 30
 
6.2%
호 15
 
3.1%
Other values (63) 172
35.6%
Common
ValueCountFrequency (%)
132
41.2%
0 28
 
8.8%
1 25
 
7.8%
3 20
 
6.2%
, 20
 
6.2%
4 19
 
5.9%
2 15
 
4.7%
8 11
 
3.4%
6 10
 
3.1%
5 10
 
3.1%
Other values (6) 30
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 483
60.1%
ASCII 320
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
41.2%
0 28
 
8.8%
1 25
 
7.8%
3 20
 
6.2%
, 20
 
6.2%
4 19
 
5.9%
2 15
 
4.7%
8 11
 
3.4%
6 10
 
3.1%
5 10
 
3.1%
Other values (6) 30
 
9.4%
Hangul
ValueCountFrequency (%)
동 41
 
8.5%
서 34
 
7.0%
작 33
 
6.8%
울 33
 
6.8%
시 32
 
6.6%
별 31
 
6.4%
특 31
 
6.4%
구 31
 
6.4%
로 30
 
6.2%
호 15
 
3.1%
Other values (63) 172
35.6%

홈페이지주소
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing4
Missing (%)12.9%
Memory size380.0 B
2024-04-21T10:00:28.674304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length130
Median length27
Mean length28.444444
Min length8

Characters and Unicode

Total characters768
Distinct characters46
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st rowhttp://www.seniorleague.or.kr
2nd rowwww.ddprince.com
3rd rowwww.heemanghousing.co.kr
4th rowhttp://www.knarts.com/
5th rowhttp://h2edu.co.kr/
ValueCountFrequency (%)
http://www.seniorleague.or.kr 1
 
3.7%
http://e-super.co.kr 1
 
3.7%
https://www.digiwill.ai 1
 
3.7%
www.iiaki.com 1
 
3.7%
https://sarana.modoo.at 1
 
3.7%
http://luxbitart.co.kr 1
 
3.7%
https://gamtanstore.kr 1
 
3.7%
http://www.onecarehu.co.kr 1
 
3.7%
https://lalaschool.modoo.at/?napm=ct%3dlgvwqp1z%7cci%3dcheckout%7ctr%3dds%7ctrx%3d%7chk%3d7cc3f940babdcf6218005ab26082628941b15395 1
 
3.7%
http://www.royalcoaching.co.kr 1
 
3.7%
Other values (17) 17
63.0%
2024-04-21T10:00:28.955882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 70
 
9.1%
t 62
 
8.1%
. 59
 
7.7%
o 49
 
6.4%
w 43
 
5.6%
r 40
 
5.2%
c 37
 
4.8%
a 35
 
4.6%
h 33
 
4.3%
e 33
 
4.3%
Other values (36) 307
40.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 553
72.0%
Other Punctuation 162
 
21.1%
Decimal Number 40
 
5.2%
Uppercase Letter 11
 
1.4%
Math Symbol 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 62
 
11.2%
o 49
 
8.9%
w 43
 
7.8%
r 40
 
7.2%
c 37
 
6.7%
a 35
 
6.3%
h 33
 
6.0%
e 33
 
6.0%
p 32
 
5.8%
s 31
 
5.6%
Other values (15) 158
28.6%
Decimal Number
ValueCountFrequency (%)
3 7
17.5%
2 5
12.5%
7 5
12.5%
1 5
12.5%
0 4
10.0%
9 3
7.5%
6 3
7.5%
8 3
7.5%
5 3
7.5%
4 2
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/ 70
43.2%
. 59
36.4%
: 23
 
14.2%
% 9
 
5.6%
? 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
D 5
45.5%
C 4
36.4%
P 1
 
9.1%
N 1
 
9.1%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 564
73.4%
Common 204
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 62
 
11.0%
o 49
 
8.7%
w 43
 
7.6%
r 40
 
7.1%
c 37
 
6.6%
a 35
 
6.2%
h 33
 
5.9%
e 33
 
5.9%
p 32
 
5.7%
s 31
 
5.5%
Other values (19) 169
30.0%
Common
ValueCountFrequency (%)
/ 70
34.3%
. 59
28.9%
: 23
 
11.3%
% 9
 
4.4%
3 7
 
3.4%
2 5
 
2.5%
7 5
 
2.5%
1 5
 
2.5%
0 4
 
2.0%
9 3
 
1.5%
Other values (7) 14
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 768
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 70
 
9.1%
t 62
 
8.1%
. 59
 
7.7%
o 49
 
6.4%
w 43
 
5.6%
r 40
 
5.2%
c 37
 
4.8%
a 35
 
4.6%
h 33
 
4.3%
e 33
 
4.3%
Other values (36) 307
40.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2024-04-05 00:00:00
Maximum2024-04-05 00:00:00
2024-04-21T10:00:29.053732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:00:29.134323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-04-21T10:00:29.214254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명사회서비스분야주된목적사업내용예비형태부처형태인증지정일자인증지정번호대표자명전화번호소재지도로명주소홈페이지주소
기관명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사회서비스분야1.0001.0000.3821.0000.1090.4710.0001.0001.0001.0000.0001.000
주된목적1.0000.3821.0001.0000.2940.4830.8911.0001.0001.0000.6191.000
사업내용1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
예비형태1.0000.1090.2941.0001.0000.6991.0001.0001.0001.0000.3881.000
부처형태1.0000.4710.4831.0000.6991.0001.0001.0001.0001.0000.9091.000
인증지정일자1.0000.0000.8911.0001.0001.0001.0001.0001.0001.0000.9941.000
인증지정번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0000.0000.6191.0000.3880.9090.9941.0001.0001.0001.0001.000
홈페이지주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-04-21T10:00:29.343110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주된목적예비형태부처형태
주된목적1.0000.1800.310
예비형태0.1801.0000.474
부처형태0.3100.4741.000
2024-04-21T10:00:29.416956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주된목적예비형태부처형태
주된목적1.0000.1800.310
예비형태0.1801.0000.474
부처형태0.3100.4741.000

Missing values

2024-04-21T10:00:23.843513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:00:24.048247image/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.
2024-04-21T10:00:24.177638image/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

기관명사회서비스분야주된목적사업내용인증지정여부예비형태부처형태인증지정일자인증지정번호대표자명전화번호소재지도로명주소홈페이지주소데이터기준일자
0(사)한국시니어협회보건업 및 사회복지서비스업혼합형노인돌봄서비스,재가방문요양YNN2008-12-30제2008-113호신*희02-815-1922서울특별시 동작구 상도로30길 8 (상도동)http://www.seniorleague.or.kr2024-04-05
1삼성떡프린스숙박 및 음식점업일자리제공형전통, 퓨전떡 제작 및 판매YNN2011-12-19제2011-123호최*태02-823-2230서울특별시 동작구 양녕로30길 19-4 (상도동)www.ddprince.com2024-04-05
2㈜희망하우징건설업사회서비스제공형집수리,리모델링,인테리어YNN2012-09-07제2012-44호강*경02-2069-3636서울특별시 동작구 여의대방로 44길 47 (대방동, 주공아파트)www.heemanghousing.co.kr2024-04-05
3㈜정인애드인쇄업일자리제공형기획디자인, 옵셋, 마스타인쇄, 임대YNN2016-09-07제2016-131호조*현02-3486-6791서울특별시 동작구 동작대로33길 28(사당동)<NA>2024-04-05
4㈜케이앤아츠예술, 스포츠 및 여가관련 서비스업일자리제공형예술, 교육YNN2018-03-08제2018-22호김*범070-8278-6984서울특별시 동작구 장승배기로10길49, 401호http://www.knarts.com/2024-04-05
5사회적협동조합 행복한학교희망교육교육서비스업사회서비스제공형교육서비스사업YNN2019-03-07제2019-37호고*훈070-7782-7056서울특별시 동작구 대림로28 ,3층http://h2edu.co.kr/2024-04-05
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